Developing Quantitative Imaging and Other Relevant Biomarkers of Myofascial Tissues for Clinical Pain Management
Phase: NA
Conditions: Myofascial Dysfunction
Sponsor: Johns Hopkins University

Quantifying Myofascial Dysfunction in 
Post-Stroke Pain
NCT05762679
7/28/2023

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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1. 
Abstract 
a. Provide no more than a one page research abstract briefly stating the problem, 
the research hypothesis, and the importance of the research. 
   
 Shoulder pain is extremely common after stroke and occurs in 30-70% of patients [1, 2].  
The pain may begin as early as one week after stroke [3], although peak onset and severity 
occurs around four months [4, 5], and persists into the chronic stage [6, 7]. Chronic post stroke 
shoulder pain (PSSP) interferes with motor recovery, decreases quality of life, and contributes to 
depression [5, 8, 9]. PSSP is thought to be caused mainly by damage to the myofascial tissues 
around the shoulder joint [10-12]. Interestingly, an MRI study in patients with PSSP showed that 
the degree of structural damage to the muscles did not correlate with the degree of pain [13]. 
Thus, the pathophysiology of myofascial dysfunction and pain in PSSP has not been 
elucidated leading to missed opportunities for early diagnosis and variable success with pain 
management.  
The accumulation of hyaluronic acid (HA) in muscle and its fascia can cause myofascial 
dysfunction [14]. HA is a glycosaminoglycan (GAG) consisting of long-chain polymers of 
disaccharide units of glucuronic acid and N-acetylglucosamine and is a chief constituent of the 
extracellular matrix of muscle [15]. In physiologic quantities, HA functions as a lubricant and a 
viscoelastic shock absorber [16], enabling force transmission during contraction and stretch [17]. 
Reduced joint mobility [18] and spasticity [19] result in focal accumulation and alteration of HA 
in muscle. This can lead to the development of stiff areas and taut bands, dysfunctional gliding of 
deep fascia and muscle layers, reduced range of motion (ROM), and pain [20]. However, the 
association of muscle HA accumulation with PSSP has not been established. 
We have quantified the concentration of HA in muscle using T1rho (T1ρ) MRI and found 
that T1ρ relaxation time is increased in post stroke muscle stiffness [21-23]. Since HA is highly 
hydrophilic, HA-rich taut bands are hypoechogenic on grey-scale ultrasound (US) [24, 25], 
making it possible to develop a clinic-friendly quantitative US tool to infer the abnormal 
accumulation of HA. Furthermore, dynamic US imaging using shear strain mapping can quantify 
dysfunctional gliding of muscle that may generate pain during ROM [26]. Myofascial 
dysfunction can result in non-painful reduction in ROM (latent PSSP), which may become 
painful due to episodic overuse injury producing greater shear dysfunction (active PSSP). Hence, 
shear strain mapping may differentiate between latent versus active PSSP. Thus, quantitative 
MR and US imaging may serve as useful biomarkers to elucidate the pathophysiology of 
myofascial dysfunction. 
 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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IMPACT 
This proposal will develop quantitative imaging biomarkers of myofascial dysfunction in PSSP 
and assess their ability to monitor response to treatment. It aligns with the NIH HEAL Initiative 
to bolster research to improve treatment and enhance pain management.  
 
2. 
Objectives (include all primary and secondary objectives) 
AIM 1. Quantify the extent of HA accumulation in shoulder muscles using quantitative 
MRI and US. 
Research Hypothesis: Patients with PSSP will show increased T1ρ relaxation times in the 
paretic compared with the non-paretic muscles, which will correlate with a distinct echo texture 
pattern on US.  
AIM 2. Distinguish between latent versus active PSSP using US shear strain mapping in 
the paretic compared with the non-paretic muscles.  
Research Hypothesis: Shear strain will be lowest in active PSSP compared with latent PSSP, 
relative to the non-paretic side.   
 
 
3. 
Background (briefly describe pre-clinical and clinical data, current experience with 
procedures, drug or device, and any other relevant information to justify the research) 
 
Contribution of Myofascial Dysfunction to PSSP. A large proportion of post-stroke pain is 
musculoskeletal, with shoulder pain contributing the largest fraction [27]. The human shoulder 
is a complex shallow ball-and-socket joint, and its multidirectional mobility is highly dependent 
on the coordinated action of several muscles shown in Figure 1A. A key characteristic of 
shoulder movement is the scapulohumeral rhythm which is the ratio of glenohumeral motion to 
scapulothoracic motion during humeral elevation (Figure 1B) [28]. The scapulohumeral rhythm 
is disrupted after stroke due to a combination of impaired strength, increased tone, 
incoordination due to aberrant muscle recruitment, and fatigue [10], leading to reduced humeral 
elevation and scapular upward rotation and increased scapular internal rotation during arm 
elevation [29, 30], which predispose to shoulder pain [31] (Figure 1C).  
 
 
Figure 1. Shoulder girdle and arm muscles (A) largely responsible for the scapulohumeral rhythm (B). Characteristic posture with increased 
shoulder internal rotation during attempted arm elevation causing shoulder pain after stroke (C).   

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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Studies have reported that 85% of patients with spastic hemiplegia experience pain compared 
with 18% of those with flaccid hemiplegia [32]. Muscle shortening and decreased ROM 
associated with spasticity and muscle stiffness can exert tension on the muscles and cause pain 
during stretching. Reduced shoulder ER is strongly correlated with shoulder pain [33-35], which 
if left untreated can result in painful contracture of the shoulder [36]. Restricted muscle ROM, 
in turn, can increase the risk of muscle injury, nerve impingements and produce excessive shear 
and compressive joint forces that may also contribute to shoulder pain [13, 37, 38]. Despite the 
known involvement of the muscles in shoulder pain, the pathophysiology of myofascial 
dysfunction is unclear, which impedes both prevention and effective treatment of PSSP.  
 
Intramuscular HA and its Contribution to Myofascial Dysfunction. Even in the absence of 
any active force generation, the non-contractile elastic elements in muscle generate passive 
forces when stretched [39]. The endomysium, 
perimysium and epimysium collectively form the 
extracellular matrix (ECM) of muscle and are 
composed of collagens and elastic fibers 
embedded in a viscoelastic gel of proteoglycans, 
glycoproteins, and glycosaminoglycans (GAGs) 
such as HA. When the myofibrillar proteins and 
proteoglycans are removed, the honeycombed 3-D 
network of the collagenous connective tissue can 
be seen [40-42] (Figure 2A). When a muscle fiber 
contracts or is stretched, the preferred orientation 
of the collagen fibers in the endomysium changes 
accounting for the non-linear increase in passive 
resistance and leads to trans-laminar shear during 
force transmission through the ECM [42, 43]. HA 
is the most abundant molecule in the ECM – it is 
present around the endomysium of individual 
muscle fibers and in the perimysium and 
epimysium of human muscle [44] (Figure 2B). The perimysium and epimysium define slip 
planes between muscle fascicles and whole muscles, enabling them to slide past each other 
during stretch and contraction, causing large shear displacements and shape changes in the 
whole muscle [17]. The shear forces across adjacent muscle fibers, muscle bundles and whole 
muscles are strongly determined by the composition and viscoelastic properties of the 
proteoglycan matrix of the ECM, specifically of HA.  
 
Figure 2. Scanning electron micrographs of muscle after 
removal of myofibrillar proteins and proteoglycans 
showing the honeycombed ECM (A). Note brown staining 
of HA with HA binding protein adjacent to the endomysium 
(arrows) and especially in the perimysium (* in white 
circles) (B).   
A 
B 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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HA has been traditionally regarded as a space-filling 
ground substance [44, 45]. It is the only non-sulfated 
GAG composed of a repeating disaccharide of 
glucuronic acid and N-acetyl glucosamine that forms 
long chains or polymers assuming molecular weights 
of the order of 105 to 107 Da and an extended length of 
0.25–25 μm [46]. The chemical structure of HA makes 
it highly hydrophilic, enabling the molecule to retain 
water and swell. However, as the concentration and 
molecular weight of HA increases, it entrains more 
water and the viscosity of the solution increases 
exponentially [47, 48] (Figure 3A); a 10 mg/ml 
solution of 1.5 x 106 Da HA has a viscosity 5000x that 
of water. The molecular weight and viscosity of HA 
solutions affects tissue lubrication, hydration, and the 
physical stiffness of the tissues [49]. HA shows non-
linear viscoelastic behavior [50-54], implying that a 
muscle with higher HA concentrations, and hence 
higher viscoelasticity will show greater passive 
resistance to stretch or contraction. Thus, the 
concentration and rheological properties of the HA in 
the ECM of muscle can contribute significantly to 
increased passive resistance during movement [55, 
56], which may produce myofascial dysfunction. 
 
Muscle spindle receptors and nerve fibers, responsible for sensing and responding to stretch, 
reside within the HA-rich perimysium, and are also abundant in HA [57] (Figure 3B). The axial 
and periaxial spaces of the muscle spindles, all layers of the spindle capsule, as well as the 
endoneurium in the space between individual axons are rich in HA. The presence of HA in the 
periaxial fluid has been shown to be responsible for the transcapsular potential which increases 
the sensitivity of the sensory endings to mechanical stimuli [58]. Alteration in the viscosity of 
the HA solution in the muscle spindle and around the nerve endings can thus increase the 
sensitivity of the muscle spindles and nerves to stretch [59, 60], potentially causing dysesthesia 
and pain.  
 
Imaging HA Accumulation in Stroke and Myofascial Dysfunction using MRI. We proposed 
the hyaluronan hypothesis of muscle stiffness, which postulated that the deposition of HA in the 
ECM of muscle contributes to the development of muscle stiffness by dramatically altering its 
viscosity [19, 25]. This hypothesis was informed by a study where the ankle joint in rats was 
immobilized, which resulted in increased muscle HA content and muscle shortening 4 weeks 
post-immobilization compared to controls [18]. However, thickening and disorganization of 
endomysial collagen fibrils only became apparent by 12 weeks post immobilization. In a proof-
of-concept study to determine if patients with post-stroke arm immobility and muscle stiffness 
also show increased HA accumulation, we performed T1ρ MRI to quantify the T1ρ relaxation 
time in the upper arm muscles of patients post stroke compared to healthy controls [61] (Figure 
4). Note that the T1ρ relaxation time is non-uniformly increased in the muscle, with perhaps 
 
Figure 3. HA in physiological saline (experimental), 
shows marked increase in viscosity with increasing 
concentration – nonideal behavior (A). Muscle spindles 
(MS) and the perineural areas (N) are abundant in HA 
(brown stained) (B). The two sides show the same 
structures that are stained differently.  
A 
B 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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more accumulation in the perimysium, between the muscle fascicles. This may have caused an 
alteration in the shape of the muscles post stroke [17], which appear to be stuck together, giving 
the upper arm a triangular shape compared to controls. While the T1ρ MRI is not specific for 
HA, HA is the most abundant GAG, and subsequent studies showed that it can be reduced with 
the enzyme hyaluronidase (see Section A.5), suggesting that HA is responsible for the signal.   
 
Interestingly, histological studies in 
animal models of overuse injury also 
show increased levels of HA in the 
epimysium of the overused muscle - 
HA concentration increased 2.8-fold 
after 2 days of overuse and remained 
significantly increased at 7 days, and 
then decreased gradually towards 
control levels by 14 days [62].  
Overuse injury causing myofascial 
pain in humans has also been 
associated with HA accumulation [14]. 
The formation of taut bands that 
constitute trigger points is attributed to increased viscosity from focal accumulation of high 
molecular weight chains of HA [24]. This can result in dysfunctional gliding of deep fascia and 
muscle layers, forming the basis of myofascial pain [20]. We published a recent case series of 
patients with non-traumatic chronic myofascial pain in the lateral aspect of the elbow who 
showed imaging evidence of abnormally elevated GAGs using T1ρ MRI [21] (Figure 5, PRE). 
Note that this accumulation is primarily in the epimysium and in the extra-muscular fascia, 
and decreased 
after fascial 
manipulation 
treatment 
(Figure 5, 
POST). This data 
is consistent with 
the data from 
animal models of 
overuse injury 
[62], and 
suggests that HA 
synthesis is stimulated by muscle overuse, but it may not be a problem unless the stimulus 
persists, or is followed by immobility, for example due to paresis from a stroke. Exercise in 
healthy individuals has been shown to increase serum HA significantly, but the serum levels 
decrease rapidly to lower than resting levels by 30 min post exercise [44], suggesting that 
movement mobilizes HA from muscle into the circulation, which is cleared rapidly. Conversely, 
lack of movement, for example, overnight, can lead to morning stiffness which improves as HA 
is mechanically driven out into the circulation by physical activity upon awakening [63]. Taken 
together, these studies demonstrate that both immobility and muscle overuse can lead to HA 
accumulation in muscle and imaged using T1ρ MRI.  
 
Figure 4. Quantification of GAG in muscle using T1rho (T1ρ) MRI. Note 
increased intramuscular T1ρ relaxation times (more red) in patients with 
post stroke muscle stiffness compared to controls.  
 
Figure 5. Quantification of GAG using T1rho (T1ρ) MRI in myofascial pain. Note increased 
T1ρ relaxation times (red) in the extra-muscular fascia in patients with lateral elbow pain 
(pre, arrows) and its reduction after fascial manipulation (post, arrows).  

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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US is more accessible than MRI for clinical imaging [64]. Healthy muscles look dark with sharp 
bright lines on grey-scale US. The dark signal is hypoechoic and the bright lines represent 
hyperechoic signal from collagen fibers in the endomysium and perimysium. The echogenicity 
of muscle tissue can describe alterations in the structure of muscles. Trigger points, which are 
stiff nodules in a taut band of muscle, present a hypoechoic signal [65, 66], which can be 
explained by the fact that HA is hydrophilic, and areas of HA accumulation entrain more water 
and become highly viscous [47, 48]. Increased ECM viscosity leads to “densification” or 
increased stiffness of the tissue [67]. Qualitative assessment of muscle echo, however, cannot 
provide an accurate measure of tissue properties [68]. Recently, quantitative US has emerged 
where the envelope statistics of the radiofrequency components of the backscattered US signal 
can be used to objectively differentiate tissue properties [69]. US scattering occurs primarily at 
interfaces, such as connective tissues of the endomysium, perimysium, and fascia and other 
components, including muscle cells, fat, and fibrous tissue; the mismatch of acoustic impedance 
can be quantified to provide echo texture maps to characterize tissue properties [70, 71], and 
statistical maps of muscle echo texture can be used to diagnose myofascial dysfunction [72]. 
Thus Aim 1 will quantify the extent of HA accumulation in paretic shoulder muscles 
compared with the non-paretic side in patients with PSSP using T1ρ MRI, and secondarily 
correlate the T1ρ MRI measures with US echo texture to develop a clinic-friendly tool to 
infer extent of HA accumulation.   
 
Imaging Myofascial Dysfunction and Differentiating Latent and Active Pain Using 
Quantitative US. The relationship of abnormal HA accumulation in muscle to pain is likely to 
be dependent on muscle use. An MRI study of 89 patients with chronic PSSP showed that 35% 
of subjects exhibited a tear, and 53% of subjects exhibited tendinopathy of at least one rotator 
cuff, biceps or deltoid muscle. However, the tears and tendinopathies were not related to the 
severity of PSSP; instead, the degree of muscle atrophy was related to reduced severity of PSSP 
[13]. Since patients with PSSP also have greater motor impairment [12], they are likely to move 
it less, leading to more atrophy, and less pain. A study of the incidence and prevalence of PSSP 
among different regions of the world suggests that it is more prevalent in regions that offer more 
rehabilitation, suggesting that PSSP may be triggered by microtrauma during movement [73]. A 
stiff, shortened muscle is more likely to resist stretch, and become injured and inflamed during 
use. Shoulder pain during movement, especially during shoulder ER after stroke, predicts long 
term shoulder pain [74], suggesting that active PSSP is perhaps provoked by overuse of already 
dysfunctional, stiff shoulder muscles, making it distinguishable from latent PSSP.  
 
Strain is the most commonly encountered muscle injury and characteristically occurs at the 
musculotendinous junction, where maximal stress accumulates, especially during eccentric 
(stretching) exercise [75]. The epimysium is continuous with the musculotendinous junction 
[76], and overuse injury is associated with accumulation of HA in the epimysium [21]. Since 
alteration in the viscoelastic properties of the accumulated HA can dramatically alter the shear 
plane motion [17],  post-stroke muscle stiffness overlaid by overuse injury may cause greater 
shear dysfunction. However, the shear dysfunction and strain injury from microtrauma or 
overuse injury may not be detected using routine MRI or US [77, 78]. Shear strain can be 
quantified by US shear strain mapping -- a computational technique where a series of ultrasound 
images are acquired in rapid succession and cross correlation methods are used to quantify the 
relative mobility of layers within inter- and intramuscular fascia during motion [26]. Using this 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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technique, it was found that shear strain was reduced by 20% in the thoracolumbar fascia during 
passive movement in individuals with low back pain versus those without low back pain. Hence 
it is possible that quantification of shear strain will be able to distinguish between latent and 
active PSSP compared with the healthy state. Thus Aim 2 will distinguish between latent 
versus active PSSP using US shear strain mapping during passive shoulder ER in the 
paretic shoulder muscles compared with the non-paretic side.  
 
INNOVATION 
This proposal is innovative in several ways:  
MR/US Imaging Innovation: T1ρ relaxation mapping of muscle will quantify GAG content 
in muscle non-invasively. Direct methods using muscle biopsy and staining for HA are not 
ethical or practical to perform before and after injections in humans. Our research team has 
shown that it is feasible to use 3D-T1ρ to map GAG content in muscle in patients with stroke and 
myofascial dysfunction non-invasively [21-23], without the use of exogenous contrast agent 
injection or radiofrequency hardware modifications. In addition, we will correlate T1ρ relaxation 
times with statistical echo texture maps obtained using quantitative US to develop a clinic-
friendly tool to infer extent of HA accumulation. These innovations will establish the 
pathophysiology of myofascial dysfunction in PSSP to enable appropriate treatment and 
monitoring.    
Quantitative US Innovation 2: Shear strain mapping has the potential to differentiate 
between latent pain and active pain in PSSP. Movement restriction reduces shear strain 
measured using quantitative US in a porcine model of back pain. However, the combination of 
movement restriction and local injury leads to an additive, and quantifiable reduction in US shear 
strain [79], suggesting that US shear strain mapping may be able to differentiate latent PSSP (due 
to movement restriction alone) from active PSSP (due to a combination of movement restriction 
and local injury). Using this method in PSSP will enable the quantification of the underlying 
pathophysiology that leads to latent and active PSSP. This will enhance pain management to 
address the underlying pathophysiology rather than just provide symptomatic relief.  
Approach Innovation: We will use the Bimanual Arm Trainer (BAT) to provide passive 
shoulder ER and assess pain-free shoulder ER. Several 
studies show a strong association between shoulder immobility 
and non-use, stiffness in the pectoralis major muscle, 
limitation in shoulder ER and PSSP [33-35] (Figure 6). We 
will use the BAT – an FDA-cleared device designed 
specifically to provide gentle, controlled passive ER-ROM 
(unimanual mode) at a fixed rate during shear strain mapping. 
For precise quantification of pain-free passive ER-ROM 
before and after treatment in the clinical trial, patients will use 
the non-paretic limb as the actuator (bimanual mode) enabling safe movements that are patient-
controlled [80]. 
 
APPROACH 
Overview: The primary objective of the R61 phase is to identify and develop quantitative 
measures that can differentiate abnormal myofascial tissues in latent versus active PSSP from 
relatively healthy tissues on the non-paretic side along with cross-sectional correlations with 
 
Figure 6. Immobility and non-use of the 
paretic upper limb leads to stiffness and 
shortening in the pectoralis major muscle, 
limiting shoulder ER-ROM. 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
Application Number: IRB00354876 
 
 
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clinical signs and symptoms. In addition, we will build the team to plan the R33 phase clinical 
trial during this first phase. 
Definition of latent PSSP: The latent phase includes myofascial dysfunction, including soft tissue 
stiffness and non-painful reduction in ROM, which may be accompanied by focal palpable 
nodules that are tender to palpation. We will define latent PSSP as a difference of more than 10 
degrees of passive ER-ROM between the non-paretic and paretic shoulders, with focal 
palpable nodules that may be tender on palpation with pain rating of <5/10 [81].   
Definition of active PSSP: During the active phase, the patient has painful reduction in ROM, 
spontaneous pain, and localized, tender 
indurated nodules on palpation of muscles 
that reproduces the local and/or radiating 
pain. Rajaratnam et al. found that a positive 
Neer test, which elicits pain on passive 
forward elevation of the arm with the scapula 
stabilized (Figure 7A), combined with the 
hand-behind-neck (HBN) maneuver eliciting 
a pain rating of > 5/10 (Figure 7B), and a 
difference of more than 10 degrees of passive 
ER-ROM between the non-paretic and paretic shoulders has a 98% probability of predicting 
PSSP with 96.7% sensitivity and 99.0% specificity [81]. We will define active PSSP as a 
difference of more than 10 degrees of passive ER-ROM between the non-paretic and paretic 
shoulders, with focal palpable nodules that are tender on palpation, reproducing the pain, and 
eliciting a pain rating of ≥5/10 when combined with the HBN maneuver.  
 
4. 
Study Procedures 
a. Study design, including the sequence and timing of study procedures   
(distinguish research procedures from those that are part of routine care). 
 
All procedures will be conducted solely for study purposes. We will conduct a cross-sectional 
observational study in 40 patients for the R61 phase. 20 patients will have latent PSSP with non-
painful restriction in passive shoulder ER-ROM in their paretic arm, and 20 will have active 
PSSP with painful (> 5/10) restriction in passive shoulder ER-ROM as defined above. All 40 
subjects will also undergo testing on their non-paretic arm which will serve as a proxy for 
“healthy” control. All subjects will undergo 3 types of quantitative imaging of the pectoralis 
major (key internal rotator) and infraspinatus (key external rotator) muscles of both arms: (1) 
3-D T1ρ MRI to quantify the extent of HA accumulation (primary outcome for Aim 1), (2) 
Quantitative US statistical echo texture mapping (secondary outcome for Aim 1), and (3) 
Quantitative US shear strain mapping to distinguish between latent and active PSSP on the 
paretic side compared with the non-paretic side (primary outcome for Aim 2).  
 
After obtaining informed consent, subjects will be screened to ensure that they meet inclusion-
exclusion criteria. They will then undergo the following clinical and imaging assessments.  
Clinical Assessments: All clinical assessments will be performed on both arms and be used to 
correlate with the imaging measures. 
 
Figure 7. Depiction of Neer test (A) and Hand-behind-neck 
(HBN) test (B) used to diagnose active PSSP (8). 
A 
B 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
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Passive ROM in the upper limb  will be measured at the shoulder (flexion-extension, abduction-
adduction, internal and external rotation) in the standard sagittal, horizontal and coronal planes 
using video and/or 3-D motion capture techniques (Motion Monitor, Innovative Sports Training, 
Inc., Chicago, IL) [82]. This system uses the trackSTAR 800 sensor (Ascension Technology 
Corp., VT ) that has a static resolution of 0.5 mm for position and 0.1° for angular orientation 
[83]. During passive ROM, we will also assess muscle stiffness with the Modified Ashworth 
Scale [84] to determine the degree of resistance [85]. 
Shoulder pain characteristics will be measured by assessing shoulder pain onset, pain location, 
pain during movements and/or at rest, pain at touch, pain intensity, pain quality and intake of 
medication for the shoulder pain. The pain quality will be assessed as dull ache, stabbing/ 
cutting, scurrying/radiating, burning, muscle cramps or tiredness, or described by the patient. 
Sensory testing for light touch will be assessed using a cotton swab in the upper arm and 
forearm, hands and fingers, and recorded as normal, diminished, increased or absent. 
Hypoesthesia (decreased sensitivity to tactile stimulation), Hypoalgesia (diminished pain in 
response to a normally painful stimulus), Hyperesthesia (increased sensitivity to tactile 
stimulation), Dysesthesia (an unpleasant abnormal sensation, whether spontaneous or evoked), 
and Allodynia (pain due to a stimulus that does not normally provoke pain) will be defined as per 
the taxonomy of the International Association for the Study of Pain (IASP) [86]. We will assess 
for vasomotor changes such as limb edema and color, and alterations in skin temperature 
between the paretic and non-paretic limbs due to local hyperactivity of the sympathetic nervous 
system [89, 90]. We will also assess local stiffness, using the stiffness rating scale [24] and the 
Pact sense muscle scanner which quantifies “haptic feeling” or what the muscle feels like when 
probed with the hand (https://www.thepact.com/technology). The Pact sense quantifies stiffness, 
measured in units of [N/m] and damping, measured in units of [Ns/m], as well as their slopes, 
and the symmetry across the measurements of the two sides of the body. The measurement 
process is purely mechanical and non-invasive, and includes no optical, electrical, or chemical 
interactions with the skin or muscles. In addition, we will measure pressure sensitivity thresholds 
using an algometer and rate the pain elicited on a pain rating scale. 
Upper limb motor impairment will be measured using the upper limb Fugl-Meyer Scale (FMS) 
[91], a validated, widely used, standard scale of motor impairment post-stroke. It consists of 33 
tasks, each is scored on a 3-point scale (0 unable to perform, 1 partially perform, 2 faultless 
performance); the maximum score for the upper extremity is 66. The FMS score reflects the 
degree to which joint movements can be isolated. 
Upper limb function will be measured with the Wolf motor function test (WMFT) [92], a battery 
of functional tasks that are timed and scored on movement quality. We will use the streamlined 
version, which has six tasks [93], and has been validated for use in the subacute stage post-stroke 
[94].  
Stroke-specific quality of life will be measured using the Stroke Impact Scale [95, 96], a self-
reported health status measure that assesses multidimensional stroke outcomes in eight domains: 
strength, hand function, mobility, activities of daily living, emotion, memory, communication, 
and social participation. Additionally we will assess depression using the PHQ-2, as pain and 
depression are strongly associated [97].  
HEAL core pain clinical patient reported outcomes: The following pain-related patient-reported 
outcomes will be collected-- Pain, Enjoyment of life and General Activity (PEG) scale, PROMIS 
Physical Function Short Form 6b, PROMIS Sleep Disturbance form 6a and sleep duration 
question, Pain Catastrophizing Scale Short Form 6, Patient Health Questinnaire-2, Generalized 

 
Date: August 28, 2023 
Principal Investigator: Preeti Raghavan 
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Anxiety Disorder-2, Patients’ Global Impressions of Change (PGIC) scale, and the Tool’s First-
Stage Screening Component (TAPS-1).  
Imaging Assessments: All imaging assessments will be performed on both arms.  
Aim 1: Quantify the extent of HA accumulation in shoulder muscles using quantitative 
MRI and US.  
(a) T1ρ MRI: All images will be acquired using a 3T Prisma whole-body MRI scanner (Siemens 
Healthcare, Erlangen, Germany) in the Nelson/Harvey building, employing a body coil (Tx)/ flex 
wrap receive array coil with 8 coil-elements over the pectoralis major and infraspinatus muscles. 
Anatomical muscle MR images (proton density, T1-w and T2-W) will be acquired using 2D-FSE 
sequences. A 3D-turbo-FLASH (fast, low angle shot) MRI sequence with a customized T1ρ 
preparation module will be used to enable varying spin lock durations (TSL). A paired self-
compensated spin-lock pulse will be used to minimize B0 and B1 variations [98]. The sequence 
parameters will include FOV = 130 mm, matrix size = 256 × 64 × 64, TR = 1500 ms, resolution 
= 0.5 × 2 × 2 mm2, spin-lock frequency = 500 Hz, 10 TSL durations = 2, 4, 6, 8, 10, 15, 25, 35, 
45, 55 ms. acquisition duration = ~18 minutes for each arm. The MRI body coil will be used for 
transmission, and vendor supplied flexible receive array coils (8 coil elements each) will be used 
to image the non-paretic and paretic sides in all subjects. To investigate the extent to which fatty 
infiltration in skeletal muscle plays a role, Dixon based methods will be used to separate fat and 
water distribution using the iterative decomposition of water and fat with echo asymmetry and 
least-squares estimation (IDEAL) technique [99, 100]. The Dixon water/fat imaging parameters 
will include TR = 9.3 ms, TE = (2.26, 3.08, 3.90) ms, FOV = 180 mm, matrix size = 128 × 128, 
resolution = 1.4 × 1.4 mm2, total acquisition time ~ 4.5 min for each arm. Total scan time for 
both arms will not exceed 90 min.  
MRI Data Processing: Manual ROIs will be drawn for the pectoralis major and infraspinatus 
muscles. The mono-exponential T1ρ mapping will be performed by fitting the signal intensity at 
different spin-lock durations for each pixel using a three-parameter non-linear mono-exponential 
model (Equation 1) where S is the signal intensity, A is the amplitude, TSL is the spin lock 
duration, T1ρ is the mono-exponential relaxation time in the rotating frame, and A0 is the 
average noise level [22, 23]. For the Dixon water-fat imaging, 
IDEAL post-processing will be used to separate the water and fat 
images from the 3-echo images. Water-fractions and fat-fractions 
will be calculated from the water and fat images. The fat-fraction 
maps will be used to quantify fat infiltration in the muscles.  
MRI Data Analysis: The mean values and standard deviations of T1ρ relaxation times (ms) will 
be obtained from the defined regions of interest in the pectoralis major and infraspinatus muscles 
and will be compared on the paretic and non-paretic sides using mixed model analysis wherein 
the two sides are nested within one person, and healthy (non-paretic) versus latent PSSP versus 
active PSSP are examined as fixed effects. Prior to final analysis we will perform model 
diagnostics to assure that model assumptions regarding the fixed and random effects are met. 
The mean water and fat fractions of the muscles will also be obtained in percentages to quantify 
fat infiltration in the muscles, which will be used as predictors in the analysis. We will use 
Pearson’s correlations to correlate the clinical and imaging measures. 
Expected results, potential pitfalls & solutions: We expect an increase in T1ρ relaxation times in 
the paretic pectoralis major and infraspinatus muscles compared with the non-paretic side. We 
may also see a difference in location of the signal and/or relaxation times between latent and 
active PSSP. For example, subjects with active PSSP may show higher relaxation times in the 
Equation 1 

 
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epimysial regions as seen with overuse injury, whereas subjects with latent PSSP may show 
higher relaxation times in the perimysial region. A two-compartment model of T1ρ mapping (bi-
exponential model) can separate out the signal from the GAG content and the free water content 
of the ECM, and delineate a clearer picture of the extracellular environment of the muscle [23]. 
We can also analyze the data collected using this model, which may differentiate latent form 
active PSSP.  
All the MRI data will be collected and analyzed in collaboration with co-I Dr. Laura Fayad at 
Johns Hopkins in conjunction with Dr. Rajiv Menon at NYU Langone. 
(b) US Echo Texture Mapping: Ultrasound imaging will be performed with an Alpinion E-
CUBE12R US system (Seoul, South Korea) equipped with an L8-17 transducer with a frequency 
range of 8 to 17 MHz and a 20-mm width or the Clarius C3 Scanner HD (Vancouver, Canada) in 
the Motor Recovery Research Lab. The participant will be seated comfortably with the arm 
supported on an arm rest. The skin surface over the pectoralis major muscle will be marked with 
the muscle relaxed. All images were acquired with the same US system settings. The 
musculoskeletal imaging preset will be used with a 10-MHz center frequency, 3-cm depth, and 
76-dB dynamic range. The pectoralis major muscle will be visualized in cross section at the 
location of the skin mark, and images will be acquired with the muscle relaxed, with the US 
transducer held steadily at the same anatomic location, in a direction perpendicular to the skin 
surface. Raw RF US data will be saved at a sampling frequency of 40 mega-samples/s. 
US Data Processing: The intensity of the raw RF US data will be calculated using the Hilbert 
transform. For each participant, a single B-mode image frame at rest will be selected. Two 
different types of analyses will be performed. First, we will create spatial parameter maps by 
estimating the statistical model parameters from the histogram of echo intensities within a 
moving rectangular window. The window size will be varied from 3 times the acoustic 
wavelength to 7 times the wavelength. Second, we will select the entire muscle as the ROI for 
estimating the model parameters. For this analysis, the muscle will be identified manually in the 
corresponding B-mode images, and the muscle boundary will be manually marked by identifying 
the hyperechoic fascia boundaries. The entire muscle will be considered the ROI for analysis, 
including all fascia interfaces inside the 
muscle boundaries. The backscattered 
intensities within this muscle ROI will 
be normalized by the maximum value 
within the ROI and analyzed as per the 
theoretical models described in [69].  
US Data Analysis: The model 
parameters (signal to noise ratio (SNR), 
shape and rate of the single gamma 
distribution, and shape, rate, and 
mixture probability of the gamma 
distributions (for example, Figure 8) 
will be estimated from the muscle 
images at rest in the non-paretic and paretic pectoralis major and infraspinatus muscles. We will 
use the SNR parameters to investigate the deviation from purely diffuse scattering. We will then 
investigate whether the gamma distributions are a good fit to the underlying data using 
descriptive statistics and the Chi-square goodness-of-fit statistic. The estimated parameters will 
be compared between the non-paretic and paretic sides. Log transformations will be applied to 
Figure 8. Histogram of backscattered US intensities in a healthy volunteer and 
in a patient with cerebral palsy.   

 
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the rate parameters to approximate normality. Pearson’s r will also be used to assess the 
correlation between the T1ρ relaxation times, and the shape and rate parameters of the gamma 
distributions with sufficiently high signal to noise ratio (SNR) obtained from the statistical echo 
texture maps US. 
Expected results, potential pitfalls & solutions: We expect that at least one of the shape and/ or 
rate parameters for a mixture of two gamma distributions from the backscattered echo intensity 
of the muscles will correlate strongly with the T1ρ relaxation times. If so, this will provide a 
quantitative clinic-friendly tool to infer the GAG/HA accumulation in the muscle, which will 
enable treatment monitoring. A limitation of using a mixture of gamma distributions is that the 
quantitative US model parameters cannot directly be linked to some tissue characteristics such as 
the effective scatterer size or coherent scatterer power, which may be possible with the use of 
more sophisticated model fits such as the homodyne K distribution. However, the parameters of 
the gamma distribution do relate to tissue characteristics that affect coherent and diffuse 
scattering, and changes in the parameters are directly related to changes in the tissue composition 
and microarchitecture. One advantage of using the mixture of gamma distributions is that the 
parameter estimation can be performed robustly by using well-established approaches. 
 
Aim 2: Distinguish between latent versus active PSSP using US shear strain mapping in the 
paretic compared with the non-paretic muscles.  
(c) US Shear Strain Mapping: We will use the Bimanual Arm Trainer to passively move the 
shoulder repeatedly into ER at a steady rate set by a metronome (Figure 9, unimanual mode). 
This has the 
advantage of 
creating a 
reproducible rate 
and amplitude of 
input motion 
which is difficult 
to achieve 
otherwise. The 
movement can be 
performed by 
moving the trough 
for one arm which 
is transduced to 
the other arm. The 
subject will be 
positioned in a seated position as shown in Figure 9B so that the infraspinatus muscle is 
accessible from the back, and the pectoralis major muscle will be accessible from the front. The 
skin over the muscles will be marked and the transducer will be stabilized so that the tissues are 
not compressed at any time. Shoulder ER will be performed repeatedly at 0.5 Hz starting from a 
position of internal rotation with a range of 30° excursion for each cycle. This is ~1/3rd of the full 
range of motion and will bring the forearm into neutral position. During this motion, we will 
collect an ultrasound cine-loop, sampled at 1 Hz over a 30 second period also using the scanner 
system used in Aim 1.  
Figure 9. The Bimanual Arm Trainer is an FDA-cleared device that facilitates rate controlled 
passive shoulder ER-ROM on the paretic side for shear strain mapping, as well as for precise 
assessment of pain-free shoulder ER-ROM before and after treatment for Aim 3.  

 
Date: August 28, 2023 
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US Data Processing: US data acquired from the non-paretic and paretic sides will be processed 
with a custom program written in Matlab (Natick, MA). Tissue displacements between 
successive US frames will be estimated from the “raw” US radio frequency (RF) data using 
cross-correlation techniques [101, 102] with a 1 mm window incremented with a 90% overlap. 
The term “US frame” refers to the RF data acquired at each time point in the cine-loop. Tissue 
lateral displacement will be computed for each successive pair of US frames in a 1 × 1.5 cm ROI 
centered laterally on the midpoint of the image. To visually document the presence of a shear 
plane within the muscle, we will generate successive displacement maps as a spatial 
representation of the displacement within the ROI for each pair of US frames. Corresponding 
cumulative lateral displacement maps will be obtained by summing tissue displacements over 
time. To calculate the magnitude of shear deformation at a standardized location across subjects, 
we will use a reference echolucent plane that is relatively stable during the movement and define 
sub-ROIs each 2 mm × 10 mm for analysis. The maximum shear strain in the sub-ROIs will be 
averaged and used for statistical analysis.  
US Data Analysis: The mean values and standard deviations of the maximum shear strain will be 
obtained from the defined regions of interest in the pectoralis major and infraspinatus muscles 
and will be compared for latent and active PSSP on the paretic and non-paretic sides using mixed 
model analysis, as described above for Aim 1. We will use Pearson’s correlations to correlate the 
clinical and imaging measures.  
Expected results, potential pitfalls & solutions: We expect that the mean maximum shear strain 
will be statistically significant between the healthy (non-paretic) and paretic latent and active 
PSSP groups to proceed to the R33 phase. We will have twice as much data for the non-paretic 
arm than for the latent and active PSSP groups. Since some subjects with stroke may not have 
perfectly healthy non-paretic sides, we will use the data from the healthiest subjects based on 
their clinical testing, which may provide a greater separation between these groups. The 
quantitative US data will be collected and analyzed in collaboration with Co-I Dr. Muyinatu 
Bell at Johns Hopkins with Co-I Dr. Siddhartha Sikdar at George Mason University.  
 
b. Study duration and number of study visits required of research participants. 
This study is cross-sectional and will take place over two-years. Each participant will come to 
the lab for three sessions (for clinical assessment, ultrasound and MRI), each of which will take 
around 3-4 hours.  
 
c. Definition of treatment failure or participant removal criteria. 
Patients will be advised verbally and in the written ICF that they have the right to withdraw from 
the study at any time without prejudice or loss of benefits to which they are otherwise entitled. 
The investigator may discontinue a patient from the study in the event of an intercurrent illness, 
adverse event, and other reasons concerning the health or well-being of the patient, or in the case 
of lack of cooperation, non-compliance, protocol violation, or other administrative reasons. If a 
patient does not return for a scheduled visit, every effort will be made to contact the 
patient/caregiver. Regardless of the circumstance, every effort will be made to document patient 
outcome. The investigator / study team will inquire about the reason for withdrawal, and follow-
up with the patient/ regarding any unresolved adverse events.  If the patient withdraws from the 
study, no further evaluations will be performed and no additional data will be collected, but vital 
status will be documented at the end of the study period. 
 

 
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d. Description of what happens to participants receiving therapy when study ends 
or if a participant’s participation in the study ends prematurely. 
The unique identifier key will be retained and will be destroyed two years after the study ends.  
 
e. If biological materials are involved, please describe all the experimental 
procedures and analyses in which they will be used. 
Not Applicable 
 
5. 
Inclusion/Exclusion Criteria 
Inclusion Criteria 
● 
18 years or older 
● 
Hemiparesis from Ischemic or Hemorrhagic Stroke 
● 
4- 180 months post-stroke with Hemiparesis since the incidence and intensity of PSSP 
● 
Show a difference of more than 10 degrees of passive ER-ROM between non-paretic and        
paretic shoulders with or without pain 
● 
Able to provide informed consent and comply with testing protocols 
 
Exclusion Criteria 
● 
Received treatment for spasticity with Botulinum Toxin or Intrathecal Baclofen within 
the past three months 
● 
Have another neurologic condition that may affect motor response (e.g. Parkinson’s 
disease, ALS, MS) 
● 
Have a contraindication to MRI (claustrophobia, magnetic pacemakers and clips) 
● 
Have non-musculoskeletal PSSP such as only central pain or chronic regional pain 
syndrome (CRPS) 
● 
Have a complicated medical condition, or significant injury to either upper limb. 
 
6. 
Drugs/ Substances/ Devices 
a. The rationale for choosing the drug and dose or for choosing the device to be 
used. 
b. Justification and safety information if FDA approved drugs will be administered 
for non-FDA approved indications or if doses or routes of administration or 
participant populations are changed. 
c. Justification and safety information if non-FDA approved drugs without an IND 
will be administered.  
 
There is no drug or device intervention in this observational study.  
 
7. 
Study Statistics 
a. Primary outcome variable. 
This study has two primary outcomes. The first, which is the primary outcome for AIM 1, is to 
quantify the extent of HA accumulation using 3-D T1ρ MRI in both arms. The second, which is 
the primary outcome for AIM 2, is to use Quantitative Shear Stain Mapping to distinguish 
between latent and active PSSP on the paretic side compared with the non-paretic side.  
 
b. Secondary outcome variables. 

 
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For AIM 1, the secondary outcome is the imaging that results from the Quantitative US 
Statistical Texture Mapping.  
 
c. Statistical plan including sample size justification and interim data analysis. 
We determined our sample size for the R61 Phase based on the more stringent sample 
size requirement for Aim 2, which will compare two independent groups, i.e., patients with latent 
PSSP vs. patients with active PSSP in the paretic arm. Because Aims 1 and 2 have different 
measurements, we present our power analysis in terms of standardized effect sizes (Cohen’s d), 
which would be applicable to either measurement (26).  
 
Langevin et al’s data on shear strain mapping in patients with and without low back pain 
(LBP), showed that the shear strain was reduced in the LBP group (56.4% ± 3.1%) compared 
with the No-LBP group (70.2% ± 3.6%), i.e., an extremely large effect size of 3.8, suggesting 
that large effect sizes are biologically plausible. 
The effect sizes in Bishop et al’s follow up 
porcine study (83), showed equally large effect 
sizes comparing shear strain in control animals 
versus animals with restricted movement (similar 
to latent PSSP in our study), versus animals with 
restricted movement plus injury (similar to 
active PSSP in our study). We conservatively 
assume a Cohen’s d of 1, which though large is 
not as large as the cited numbers. To detect a 
difference between latent PSSP versus active 
PSSP, a sample size of 17 per group is adequate for statistical significance at the 0.05 level with 
80% power. For comparisons between paretic versus non-paretic shoulders, we expect greater 
power for within-person paired comparisons. However, conservatively assuming no advantage 
due to within-person correlations, we will also have 80% power to detect differences between 
latent PSSP versus healthy (non-paretic) shoulders and active PSSP versus healthy shoulders 
(non-paretic). Since we will be making multiple MRI and US measurements in a population that 
is disabled and in pain, it is possible that there will be some attrition. Hence accounting for 15% 
attrition, we will enroll 20 patients per latent PSSP and active PSSP group.  
 
d. Early stopping rules. 
Not expected since this is an observational study.  
 
8. 
Risks 
a. Medical risks, listing all procedures, their major and minor risks and expected 
frequency. 
 
Expected risks to the subject are as follows: 
Risks from the clinical assessments: The clinical assessments pose minimal risk. However, 
stroke patients may fatigue easily. Subjects may experience discomfort when markers are placed 
on the skin using adhesives. For range of motion assessment, the subjects may develop erythema 
and skin irritation. These reactions are temporary and will subside in a few hours.  
 
Figure 10. Overview of study design for the R61 Phase. 

 
Date: August 28, 2023 
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During shear plane motion assessments, the Bimanual Arm Trainer (BAT) will move the arm 
passively repeatedly through a small range of motion which may feel awkward or uncomfortable 
for individuals with abnormal muscle tone. Fatigue can also be a factor from sitting at the BAT 
during the assessments. 
 
Risks from the ultrasound assessments: The placement of the transducer on the skin requires 
the use of ultrasound gel which may cause minimal discomfort due to the mild cold sensation on 
the skin. The ultrasound system uses low frequency ultrasound and subjects cannot feel any 
sensation from the ultrasound transducer.  
 
Risks from the muscle MRI scan: There are no known harmful effects due to exposure to the 
magnetic field used. Some people may feel confined and experience anxiety in the scanner. The 
scanner produces tapping sounds during operation, which may reach very loud levels. In 
extremely rare cases, a magnet can lose its magnetism, in which case cooling fluids may be 
released noisily through escape valves and may collect in gas form in the scan room.  The gas is 
not harmful in itself as long as fresh air is available. Some individuals may experience muscle 
twitches or tingling sensations and/or a slight increase in body temperature during some types of 
scan activity. These are very unlikely under current MRI guidelines.  
Incidental findings: The MRI scans are for research purposes only and not directed toward, nor 
designed for, clinical diagnosis. However, individuals may be concerned about unexpected 
findings on their scans. The discovery of these abnormalities may lead to feeling anxious and 
additional tests with costs and risks not covered by this research. There is a risk of injury during 
MRI if there are metal objects in the body.  
 
Risk from questionnaires: Subjects will be asked to provide information about their self-
reported physical and mental well-being. These questions have a small likelihood of low 
psychological risk if participants are upset by the questions. Their range-of-motion will also be 
recorded using video. Since patients will be providing information about their medical history 
and health status, and their movements will be recorded, there is the potential risk of loss of 
confidentiality. 
 
Risks related to data privacy: Private, identifiable information will be collected. While every 
reasonable effort will be made to ensure confidentiality of protected and sensitive personal 
medical information, there is a risk that this confidentiality is compromised, although the study 
doctors do not expect this to occur. 
b. Steps taken to minimize the risks. 
 
Risks from the clinical assessments: During clinical assessments, we will ensure that subjects 
are given adequate rest breaks to prevent them from becoming fatigued. Each testing session will 
not last longer than four hours. Discomfort from markers and adhesives will be mitigated by 
ensuring comfort and using hypoallergenic adhesives that are less likely to cause a skin irritation. 
If they develop irritation or discomfort from the electrodes or adhesives, they will be offered ice 
packs for relief of symptoms. Mechanical stops are in place to avoid any abnormal or excessive 
range of motion of the joints of the arm when moving with the BAT. If the arm position were to 
ever become uncomfortable the subject can unstrap the paretic arm using the non-paretic arm.  

 
Date: August 28, 2023 
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Risks from the ultrasound assessments: No adverse effects have been associated with 
ultrasound measurements. 
 
Risks from the muscle MRI scan:  Standard screening procedures and restricted access 
minimize the risk associated with MRI. All subjects will be required to fill out a questionnaire 
indicating if they have any metallic implants prior to entering the scanner for an MRI. All 
participants will be checked to ensure that no metallic objects remain on their body before 
entering the magnet room. These include any loose metal snaps, watches, keys, hair pins, 
electrodes, and hearing aids. Participants with pacemakers or clips will be excluded from the 
study.  During the MRI, the participant will be monitored through a voice box and visually 
observed using multiple CCD cameras. The greatest risk of the magnetic field is that a metal 
object could be pulled into the scanner. To reduce this remote risk, everyone near the magnet 
will remove all metal from their clothing or pockets when in the scanning environment and the 
door to the scan room will remain closed during the exam. Some people may feel confined and 
experience anxiety in the scanner. If any problems arise, the scan will be terminated 
immediately.  
Incidental findings: If any incidental abnormalities are found, we will notify subjects and/or their 
primary physician.  
 
Risk from questionnaires: These questions have a small likelihood of low psychological risk if 
participants are upset by the questions. The participant does not have to answer any question that 
they do not wish to.  
 
Risks related to data privacy:  All subject information will be coded.  
 
c. Plan for reporting unanticipated problems or study deviations. 
 
Reportable events defined by the JHM IRB will be reported to the IRB using the: “Protocol 
Event Report” submission or as a written report of the event (including a description of the event 
with information regarding its fulfillment of the above criteria, follow-up/resolution and need for 
revision to consent form and/or other study documentation). Copies of each report and 
documentation of IRB notification and receipt will be kept in the Clinical Investigator’s study 
file. 
d. Legal risks such as the risks that would be associated with breach of 
confidentiality. 
 
We expect minimal risk to confidentiality. Data are coded, and no identifying information will be 
used in any analyses or publication. The master list containing the link between the data and the 
identity will be password-protected and kept on computers that are also password protected. All 
printed health information and study data gathered during performance of the study are kept in 
locked files, accessible only to study personnel. Electronic data is coded to protect subject 
identity and stored on password-protected computer workstations. We adhere to all HIPAA 
privacy rules that affect research protocols. 
 
e. Financial risks to the participants. 

 
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There are minimal financial risks to the participant. The risks include lost time from school or 
work and travel expenses. 
 
9. 
Benefits 
a. 
Description of the probable benefits for the participant and for society. 
The subjects may or may not derive personal benefits from this study. The detailed evaluation 
procedures will provide insight into mechanisms to further understand myofascial pain in 
patients post-stroke, and may be applicable to patients with myofascial pain in general.  
 
10. 
Payment and Remuneration 
Transportation to and from the lab will be paid for by the grant, through Uber/Lyft rides or 
parking passes. Participants will be paid $100 at the completion of the procedures at the end of 
the study.  
 
11. 
Costs 
This study will be of no cost to the subject or their insurance provider.  
 
12. 
Transfer of Materials 
Transfer of biospecimens from Johns Hopkins to another organization for research 
purposes and receipt of biospecimens from an outside organization for your research 
must adhere to JHU policies for material transfer (https://ventures.jhu.edu/faculty-
inventors/forms-policies/ ) and biospecimen transfer 
(https://hpo.johnshopkins.edu/enterprise/policies/176/39187/policy_39187.pdf?_=0.622
324232879).  
There will be no transfer of biospecimens. 
 
Please complete this section if your research involves transfer or receipt of biospecimens. 
 
a. Will you receive biospecimens from an external entity for this research? [Yes/No].  
 
If “Yes”, please confirm you will secure an MTA/research agreement from the 
appropriate office  (JHTV/ORA) prior to transfer.  
 
See: https://ventures.jhu.edu/technology-transfer/material-transfer-agreements/ . 
 
b. Will you transfer biospecimens to an external entity as part of this research? [Yes/No] 
 
If “Yes”, please address each of the following: 
1) Describe the nature of the research collaboration with the external entity and the 
rationale for the transfer. (Include an explanation of your intellectual contribution to 
the design of the research study, resulting data and sharing, and participation in the 
planned publications.) 
2) Please confirm you will secure an MTA through the appropriate office (JHTV or 
ORA) prior to transfer. 
(See: https://ventures.jhu.edu/technology-transfer/material-transfer-agreements/.) 
  
3) If the biospecimens you intend to transfer were obtained through clinical or research 
procedures at Johns Hopkins and “Other” is selected in Item 4, Section 23, please 
submit the following items in that Section: 

 
Date: August 28, 2023 
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a. A pdf version of a completed JHTV Online “Material Transfer Agreement 
Request Form for Outbound Material” https://ventures.jhu.edu/technology-
transfer/material-transfer-agreements/ OR a copy of the COEUS PD (Proposal 
Development Summary). 
b. A completed Biospecimen Transfer Information Sheet 
https://www.hopkinsmedicine.org/institutional_review_board/forms/.   
c. A signed and dated “De-identified Human Subject Certification” 
https://www.hopkinsmedicine.org/institutional_review_board/forms/  
d. Approval documents from recipient site, if applicable. 
e. Copies of the consent forms associated with the IRB protocols under which 
the biospecimens were collected, with language appropriate to this transfer 
highlighted.  
f. The name of the specialist you are working with in ORA to complete a 
contract/MTA. 
Please see the following website for more information about transferring human 
biospecimens to outside entities: 
https://www.hopkinsmedicine.org/institutional_review_board/news/announcement_transf
er_human_biospecimens_outside_entities.html/ .   
 
References 
 
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Bender, L. and K. McKenna, Hemiplegic shoulder pain: defining the problem and its management. Disabil 
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3. 
Ratnasabapathy, Y., et al., Shoulder pain in people with a stroke: a population-based study. Clin Rehabil, 
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4. 
Adey-Wakeling, Z., et al., Incidence and associations of hemiplegic shoulder pain poststroke: prospective 
population-based study. Arch Phys Med Rehabil, 2015. 96(2): p. 241-247 e1. 
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Adey-Wakeling, Z., et al., Hemiplegic Shoulder Pain Reduces Quality of Life After Acute Stroke: A 
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Paolucci, S., et al., Prevalence and Time Course of Post-Stroke Pain: A Multicenter Prospective Hospital-
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Lindgren, I., et al., Shoulder pain after stroke: a prospective population-based study. Stroke, 2007. 38(2): 
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Vasudevan, J.M. and B.J. Browne, Hemiplegic shoulder pain: an approach to diagnosis and management. 
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Gamble, G.E., et al., Poststroke shoulder pain: a prospective study of the association and risk factors in 
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De Baets, L., et al., Characteristics of neuromuscular control of the scapula after stroke: a first 
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Nadler, M., et al., Shoulder pain after recent stroke (SPARS): hemiplegic shoulder pain incidence within 
72hours post-stroke and 8-10 week follow-up (NCT 02574000). Physiotherapy, 2020. 107: p. 142-149. 
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Torres-Parada, M., et al., Post-stroke shoulder pain subtypes classifying criteria: towards a more specific 
assessment and improved physical therapeutic care. Braz J Phys Ther, 2020. 24(2): p. 124-134. 
13. 
Shah, R.R., et al., MRI findings in the painful poststroke shoulder. Stroke, 2008. 39(6): p. 1808-13. 
14. 
Pratt, R.L., Hyaluronan and the Fascial Frontier. Int J Mol Sci, 2021. 22(13). 

 
Date: August 28, 2023 
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15. 
Infante, J.R., et al., Phase 1 trials of PEGylated recombinant human hyaluronidase PH20 in patients with 
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