MRI Derived Quantitative Risk Maps for Prostate Cancer Diagnosis Using Targeted Biopsy
Phase: NA
Conditions: Prostate Cancer
Sponsor: University of Chicago

IRB17-1694 
 
Version Date: 06/10/2022 
Page 1 of 14 
 
MRI DERIVED QUANTITATIVE RISK MAPS FOR PROSTATE CANCER DIAGNOSIS 
USING TARGETED BIOPSY 
Principle Investigators: 
Aytekin Oto, M.D., Professor of Radiology 
 
 
Co-Investigators: 
Scott Eggener. MD 
Tatjana Antic, MD 
Greg Karczmar, Ph.D. 
Yulei Jiang, Ph.D. 
Ambereen Yousuf, M.D 
Aritrick Chatterjee, Ph.D. 
Ajit Devaraj, Ph.D. 
Milica Medved Ph.D. 
Xiaobing Fan Ph.D. 
Luke Reynolds, M.D. 
 
Location: University of Chicago Medical Center, Department of Radiology 
 
A. BACKGROUND AND RATIONALE 
Prostate cancer (PCa) is the most frequently diagnosed cancer and the second most 
common cause of cancer death in US men (3).  Approximately 26,730 men in the US will 
die of PCa in 2017 (3).  Current methods for detecting and diagnosing PCa are seriously 
flawed since they frequently produce inconsistent and unreliable results, often with high 
cost.  PCa screening is driven by the serum prostate specific antigen (PSA) test, with 
definitive diagnosis from histologic analysis of 12–24 tissue cores sampled randomly from 
the prostate with trans-rectal ultrasound (TRUS)-guided biopsy.  This approach is prone 
to under-sampling the prostate (only 1% of the prostate tissue is sampled) and under-
diagnosing clinically significant PCa.  Typically, only 30% of the first TRUS-guided biopsy 
is positive for PCa but unfortunately, a negative biopsy does not rule out PCa, and repeat 
biopsies are often required.  Furthermore, Gleason score—one of the most important 
prognostic factors for PCa—is not reliably assessed from TRUS-guided biopsy, and is 
upgraded in 30% of cases in repeat biopsies or prostatectomies (4, 5).  Every year, 
approximately 1.2 million prostate biopsies are performed in the US (6), which cost the 
US health care system an estimated $2 billion/year (7-10).  As a result, there are currently 
no effective, widely accepted and reliable methods for risk assessment, detection and 
diagnosis of PCa.  Consequently, the number of early cancers detected is also decreasing 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 2 of 14 
 
significantly, and therefore increased incidence of metastatic PCa and disease specific 
mortality is expected, beginning in approximately 2017 (11).  In addition, inefficient 
diagnosis algorithms and unreliable risk prediction leads to "overtreatment"—it is 
estimated that, for 30–40% PCa patients, prostatectomy does not impact survival but 
exposes them to significant complications (impotence and incontinence).  There is a 
critical and immediate need for accurate and non-invasive diagnostic tools to improve 
PCa diagnosis and grading.  At the time of initial diagnosis, we need a diagnostic tool for 
evaluation of the entire prostate, to identify PCa foci, and to differentiate clinically 
significant cancer (requires aggressive treatment) from indolent disease (does not require 
aggressive treatment), to reduce financial, logistical, and emotional costs from PCa and 
improve the outcome of PCa management. 
Currently there is no consensus on the definition of clinically significant prostate cancer.  
In this proposal we define significant cancer based on pathologic criteria.  For biopsy, 
based on the Canadian recommendations (12), clinically significant cancers include all 
tumors with Gleason score >6 (3+3) (ISUP grade group 1), and with Gleason score ≤6 
(3+3) (ISUP grade group 1) if not localized.   
Multi-parametric MRI (MP-MRI) is an MRI protocol optimized for PCa and embraced 
worldwide by the radiology community.  MP-MRI is a combination of two or more of the 
following imaging sequences: T2-weighted (T2w), diffusion-weighted (DW), and dynamic 
contrast enhanced (DCE).  One promising solution for improving PCa detection is 
targeted biopsy of the prostate using MP-MRI.  When performed by experts, Mp-MRI 
targeted biopsies result in higher detection rates of clinically significant cancer with a 
reduced upgrading of cancers at surgery, improving confidence in the biopsy results (13-
16).  MR-targeted biopsies can be performed either by fusing MR images to real time US 
images or directly under MR guidance (in-bore MR guided biopsy).  
A.1 Current status and shortcomings of prostate magnetic resonance imaging 
(MRI) 
Performance of MRI-targeted biopsy depends on accurate and reproducible interpretation 
of MR images leading to accurate identification of targets for biopsy.  Images from MP-
MRI are complementary and synergistic in diagnostic information, but they are also 
complex and difficult to decipher by radiologists.  T2w and DW MR images are the 
mainstay of MP-MRI, and can depict PCa with high sensitivity.  T2w and DW-MRI are the 
main imaging techniques for PI-RADS, the standardized reporting approach to MP-MRI 
(17).  Currently, all commercially available PCa MP-MRI protocols are based on 
subjective and qualitative interpretation by radiologists, and none is truly quantitative, well 
defined, and reproducible.  Interpretation of prostate MP-MRI varies greatly among 
radiologists, because of a lack of reproducible and quantitative MRI acquisition protocols, 
and because of a lack of decision support system (DSS) tools to assist radiologists 
interpret the images.  This problem is exacerbated by limited number of radiologists who 
have substantial experience and expertise in interpretation of prostate MP-MRI.  Success 
of MP-MRI achieved in select centers of excellence cannot be reproduced easily 
worldwide.  We propose to evaluate a quantitative prostate MRI acquisition protocol, 
and a novel Risk Map DSS tool for image interpretation, to enable widespread 
clinical translation of PCa MRI.  If these emerging results are reproduced widely, MRI 
has the potential to revolutionize PCa management, reduce unproductive biopsies and 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 3 of 14 
 
unnecessary radical therapies (e.g., prostatectomy and radiation), and achieve more 
accurate and efficient diagnosis, effective follow-up, and targeted eradication of 
aggressive disease.  
We will use a new MRI technique to obtain quantitative tissue composition maps based 
on a new hybrid multi-dimensional MRI (HM-MRI) approach that combines T2 and ADC 
measurements and detects tissue heterogeneity at the microscopic level in an innovative 
way.   
Our group has developed two novel approaches that have potential to substantially 
improve multi-parametric MRI in prostate: the kT-T2 sequence (18-21) and the hybrid 
multi-dimensional MRI (HM-MRI) (22-25). The kT-T2 sequence provides a direct 
assessment of the prostatic micro-environment and HM-MRI provides an assessment of 
the prostatic tissue micro anatomy which allows us to find water signals that are 
characteristic of cancers.  This is important new information that cannot be obtained 
from conventional T2 and ADC measurements. 
HM-MRI data can be analyzed to produce accurate tissue composition maps showing 
volume fractions of stroma, epithelia, and lumen.  These maps have been shown in 
preliminary studies from this laboratory to enhance diagnostic accuracy (26) , as 
summarized in Preliminary Results (Section A.3.1.).  Information from these tissue 
composition maps will be incorporated into the DSS tool. 
A.2. Protocol overview:  
We propose to test a Risk Map DSS image interpretation tool for automated interpretation 
of prostate MR using research sequences, which will include quantitative kT-T2, and HM-
MRI acquisition, in the clinical MRI protocol. This will also allow straightforward 
comparison of kT-T2 and HM-MRI vs. conventional T2 and ADC images.   This, in turn, 
will be used for reliable determination of clinically significant cancer in prostate which will 
be targeted by MR-targeted biopsies at the time of diagnosis.  The goal is to achieve 
clinical translation of advanced and innovative technology for accurate and reliable PCa 
diagnosis, to provide patients and treating physicians with quantitative and objective data, 
and to enable them to make informed treatment decisions.   
A.3. Preliminary results: 
Preliminary results and research accomplishments directly related to this proposal are 
listed below. 
A.3.1. Tissue composition estimate from HM-MRI data, and correlation with 
histology: 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 4 of 14 
 
A preliminary study demonstrates that HM-
MRI has potential to significantly enhance 
the diagnostic accuracy of PCa detection 
and diagnosis (26).  This analysis included 
21 
PCa 
patients 
who 
underwent 
preoperative 3T HM-MRI.  Axial images 
using HM-MRI were acquired with TE = 47, 
75, 100 ms and b-values of 0, 750, 1500 
s/mm2, resulting in a 3×3 array of data for 
each voxel.  Volume fractions of three tissue 
components—epithelium, 
stroma, 
and 
lumen—were estimated by fitting the HM-
MRI data to a three-component signal model 
(see section c.2.3.iv) with distinct ADC and 
T2 values for each component.  Figure 1 
shows an example Gleason 4+5 cancer 
outlined on H&E slides and superimposed on 
estimated ADC and T2 maps (top row), 
stromal, luminal, and epithelial volume 
fraction maps (2nd row, and 3rd row, left), and 
finally a tissue composition map (3rd row, 
right).  This aggressive cancer is clearly 
evident on conventional ADC and T2 
images, but is shown here with greater 
contrast in the tissue composition map.  We 
analyzed 28 PCa and 71 normal tissue ROIs 
outlined by an expert radiologist.  The 
volume fractions of normal tissue are similar 
to histological 
studies (27-29).  Stromal volume was highest 
in AFMS followed by transition zone, 
epithelium volume was highest in central 
zone, and lumen volume was highest in PZ (Fig. 1, 4th row).  The volume fractions were 
significantly different in cancers than in normal tissue (Table 1 for cancer and normal PZ, 
and Fig. 1, 4th row, for cancer vs. normal tissue in all zones).  PCa has significantly 
increased epithelium than normal tissue (48.8±9.2 vs. 23.2±7.1%), reduced lumen 
(14.0±5.2 vs. 26.4±14.1%), and 
reduced stroma (37.2±9.1 vs. 
50.5±15.7%) fractional volumes.  
The 
volume 
fractions 
also 
correlate more strongly with 
Gleason Score (ρ = 0.65 for 
epithelium, -0.44 for stroma, and 
-0.39 for lumen) than T2 (ρ = -
0.29) and ADC (ρ = -0.32).  The 
AUC value for differentiating 
Table 1.  Comparison of Tissue Composition 
 
Study 
Stroma (%) Epithelium (%) 
Lumen (%) 
Normal 
Peripheral 
Zone  
Tissue 
Langer et al 2010 
38.2 
31.2 
29.6 
Chatterjee et al 2016 
38.3±1.4 
32.0±1.5 
30.1±1.2 
HM-MRI 
39.0±13.6 
21.5±4.6 
39.4±14.1 
Prostate 
Cancer 
Langer et al 2010 
38.6 
46.2 
13.5 
Chatterjee et al 2016 
27.9±1.0 
60.9±1.9 
11.2±1.1 
HM-MRI 
37.2±9.1 
48.8±9.2 
14.0±5.2 
 
Figure 1.  Representative tissue composition maps 
estimated from HM-MRI for an ROI of histologically 
confirmed Gleason Grade 4+5 cancer.  The red color in the 
"composition map" which combines the stroma (1), lumen 
(blue), and epithelium (2) maps is consistent with  
increased epithelial and reduced lumen and stromal 
volume fraction in this cancer.  The box plots show 
epithelial, stromal, and luminal volume fractions in the 
AFMS, CZ, PZ, TZ, and cancer. 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 5 of 14 
 
PCa from normal tissue was 0.99 for epithelium, 0.80 for lumen, 0.79 for stroma, and 0.71 
for T2 (AUC for ADC was not evaluated because cancer ROIs were outlined in ADC 
maps).  These results suggest that HM-MRI non-invasively provides 3-dimensional 
information that is similar to the information obtained from 2D ex vivo histology slices, and 
that prostate tissue composition measured non-invasively by using HM-MRI have 
potential to improve PCa diagnosis and assessment of PCa aggressiveness.  The study 
also resulted in a filed patent application (30). 
A.3.2. PCa risk maps derived from quantitative MRI data 
We have developed a preliminary risk map based 
on mpMRI: ADC, T2, and DCE signal enhancement 
rate (α).  These parameters were calculated on a 
voxel-by-voxel basis for the entire, co-registered 
prostate.  Each parameter was normalized (to 0-
100) with low T2, low ADC, and high α signify high 
risk.  The final risk score is a weighted sum of the 
parameters (ADC 40%, T2 40%, DCE 20%) with 
higher risk for low T2, low ADC, and high α values.  
We analyzed preoperative 3T mpMRI of 22 PCa 
patients, and used five patients as the training set 
to find the optimal threshold for predicting PCa and 
17 patients as the test set.  A sector-based analysis 
(18 sectors per prostate) on the 17 test patients 
showed the following PCa detection performance: 
sensitivity 
75% 
(105/140), 
specificity 
89% 
(147/166), positive predictive value 85% (105/124), 
negative predictive value 81% (147/182), and AUC 0.82 (95% CI [0.77, 0.87]).  
Importantly, the risk map correctly identified all index lesions.  This study suggests that 
the risk map can detect PCa and guide targeted biopsies for improved PCa diagnosis. 
A.3.3. Pilot DSS study: 
We developed a pilot DSS based on T2w and DW-MRI (31).  A radiologist and a 
pathologist identified 104 ROIs (61 cancer and 43 normal tissue) based on correlation of 
histological and MR findings.  AUC values in the differentiation of PCa from normal tissue 
foci of 10th percentile ADC, average ADC and T2w skewness were 0.92, 0.89, and 0.86 
respectively.  The combination of the 10th percentile ADC, average ADC, and T2w 
skewness yielded an AUC value of 0.95 for the same task.  Gleason score correlated 
moderately with the 10th percentile ADC (ρ=-0.34, p=0.008) and with the average ADC 
value (ρ=-0.30, p=0.02).  The combination of 10th percentile ADC, average ADC, and 
T2w skewness were promising in differentiation of PCa from normal tissue, and ADC 
image features correlated moderately with Gleason score (31). 
A.3.4. Validation study of pilot DSS:  
We validated the pilot Risk Map DSS on preoperative 1.5T MP-MR images (with 
endorectal coil) of 119 PCa patients (GE scanners, n=71; Philips scanners, n=48) and 
265 PCa and normal peripheral zone ROIs identified through histology-MR consensus 
review (32).  AUC values of the pilot DSS image features combined were 0.95 and 0.88 
Figure 2.  Representative example of developed risk map
tool showing a slice from mid prostate where the tool 
detected the index lesion (Gleason 4+3). 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 6 of 14 
 
on the Philips and GE dataset (leave-one-patient-out evaluation), respectively, and 0.96 
and 0.89 when training on the GE dataset and testing on the Philips dataset, and vice 
versa, respectively.  Spearman correlation coefficients between ROI-specific Gleason 
scores and the ADC features were between -0.27 and -0.34.  This previous work (32) 
demonstrates that a pilot DSS tool developed based on data from Philips scanners can 
be effective with data from other scanners, and supports the feasibility of the proposed 
Risk Map DSS tool. 
 
B. PURPOSE 
The purpose of the proposed research is to test and validate an artificial intelligence-
based Risk Map decision-support system (DSS) for PCa MRI interpretation and 
identification of clinically significant tumor site based on MRI acquisition of a 
protocol covering the entire prostate which will include the kT-T2 and the hybrid 
multi-dimensional MRI (HM-MRI) sequences.   
We will test an artificial intelligence-based Risk Map DSS tool we have developed, which 
is based on and expanded from previously identified key MR image features that are 
effective for identifying PCa from normal prostate tissue, and which also correlates 
moderately with Gleason scores (ADC, T2, and tissue composition maps).  The DSS tool 
will assist radiologists interrogate suspicious areas in the prostate that are potentially 
clinically significant PCa foci, and will identify up to two potential clinically significant tumor 
sites.  In addition to systematic biopsies and the targets identified by the radiologist, up 
to two targets determined by the DSS tool will be biopsied.  Biopsy histology results of all 
cores will be used as the reference standard to evaluate the performance of the Risk Map 
DSS tool. 
 
C. METHODOLOGY 
C.1. Study Design:  
This is a prospective, single-arm, unblinded study of patients with known or suspected 
prostate cancer. A total of 125 patients will be enrolled.  
Recruitment: We will recruit patients with known or suspected prostate cancer who have 
been referred to the Department of Radiology at the University of Chicago Medical Center 
for a diagnostic MRI exam of the prostate, to be followed by an MRI-guided fusion biopsy 
of the prostate, per standard clinical protocol. 
All patients will be scanned using a standard clinical prostate MRI protocol. Research 
sequences will be added to the routine clinical exam. The research sequences will not 
exceed 15 minutes. The patients will not receive intravenous contrast agent as part of the 
research protocol.  
All patients will then undergo a 12-core TRUS-guided or transperineal US-guided sextant 
random biopsy by their urologist at the Urology Clinic as their standard of care treatment. 
Additional biopsy targets may be selected based on an expert radiologist's interpretation 
of the patient’s clinical MRI, as part of the clinical, standard of care MR targeted biopsy 
procedure.  Up to two additional biopsy targets per patient will be selected by the Risk 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 7 of 14 
 
Map DSS tool, if different from the already selected targets by the radiologist per standard 
of care.  Ultimately, the clinical radiologist will make the final decision on the targets to be 
biopsied.  MR-targeted biopsies will be done by using a Uronav MR-US fusion device.  
The following results will be recorded for each core: (1) the reason of biopsy (random 
biopsy; DSS tool alone; radiologist alone) (2) location (sextant and zone), and (2) 
histology result.  Research cores will be evaluated by expert genitourinary pathologist, 
Dr. Antic, and results will be communicated to the urologist.  
Studies will be carried out using FDA approved 3 Tesla Philips, GE and Siemens MRI 
units at the University of Chicago Medical Center. All of the research MR sequences will 
be in compliance with FDA safety requirements and MR contrast agents will not be 
injected for research purposes. 
C.2. MRI Data acquisition methods: 
The data acquisition will consist of obtaining the standard clinical protocol and research 
sequences, in compliance with FDA safety requirements. Research sequences may 
include, but will not be limited to (1) kT-T2 sequence (high spatial resolution axial ME-
TSE for T2 measurements and anatomy visualization), and (2) axial HM-MRI with 4 b-
values and 4 TEs for diffusion and T2 measurements. MR images will be acquired using 
Philips, GE or Siemens 3T clinical MR systems with a phased array surface receiver coil. 
C.3. Study Endpoints and Statistical Analysis 
The major goal of this study is to compare the accuracy of the Risk Map DSS tool against 
the clinical accuracy of experienced radiologists in the context of the reference standard 
of biopsy histology.  The primary endpoints will be ROC curve, AUC value, the secondary 
endpoint will be sensitivity, specificity, PPV, and NPV, and the tertiary endpoint will be 
correlation strength between the DSS tool output and tumor-specific Gleason scores.  
Both per-patient and per-tumor analyses will be conducted.  For the per-patient analysis, 
patients who are diagnosed with PCa from the biopsy procedure will be considered as 
positive for PCa, and patients who are not diagnosed with PCa from the biopsy procedure 
will be considered as negative for PCa.  For the per-tumor analysis, each individual PCa 
tumor diagnosed from the biopsy procedure will be analyzed separately, and biopsy sites 
that do not yield PCa diagnosis will be considered as negative for PCa.  To ascertain a 
true positive biopsy, the finding and the biopsy must match in sextant and zone.  If 
ambiguity in biopsy site arises with regard to indications from the DSS tool, or the 
radiologist's opinion, and the biopsy, expert radiologist (Dr. Oto) and pathologist (Dr. 
Antic) will review each case to make the determination.  This will allow us to calculate the 
performance of: (1) the Risk Map DSS tool, (2) the radiologist, and (2) the standard 
sextant biopsy.  We will evaluate these performance endpoints on clinically significant 
PCa (but we will have data for all tumors).  Spearman correlation coefficient will be 
estimated in the usual manor. 
C.4. Statistical power consideration 
We expect the following level of performance: AUC 0.90±0.03, sensitivity 90±5%, 
specificity 90±4%, and statistically significant (Spearman's) correlation strength of 0.8 
with tumor-specific Gleason scores.  Variances are estimated based on the expectation 
of PCa diagnosis in 35% of 125 patients, and based on an empirical rule-of-thumb formula 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 8 of 14 
 
for AUC and binomial probability for sensitivity and specificity.  The estimated 95% 
confidence intervals (CIs) are: for AUC [0.87, 0.93], for sensitivity [0.85, 0.95], and for 
specificity [0.86, 0.94].  These uncertainty estimates do not include analysis of biopsy by 
sextant and zone of the 12-20 cores per patient; estimates of 12 by-location-analyses per 
patient reduce all uncertainties to about 1%.  These estimates suggest that this protocol 
will produce meaningful performance estimates.   
 
D. DURATION OF THE PROTOCOL 
The probable duration of the study will be 3 years with review, at least annually, to recruit 
the target number of patients and complete all data analysis. 
 
E. LOCATION WHERE RESEARCH WILL BE CONDUCTED 
The study will be conducted on the FDA approved 3 Tesla Philips, GE or Siemens MRI 
scanners at the University of Chicago Medical Center, 5841 South Maryland Avenue, 
Chicago, IL 60637. 
 
F. SAFETY MONITORING 
We do not anticipate any adverse events. However, adverse events related directly to the 
study will be reported to the Cancer Center Clinical trials office following standard 
operating procedures outlined in the Cancer Center data safety and monitoring plan. 
 
G.  DESCRIPTION OF EXPERIMENTAL CONTROLS AND USE OF PLACEBOS 
N.A. 
 
H.  TYPE AND NUMBER OF EXPERIMENTAL SUBJECTS 
We will recruit 125 patients who will receive a diagnostic MRI exam of the prostate, to be 
followed by an MRI-guided fusion biopsy of the prostate. 
Inclusion Criteria 
We will recruit patients with known or suspected prostate cancer who have been referred 
to the Department of Radiology at the University of Chicago Medical Center for a 
diagnostic MRI exam of the prostate, to be followed by an MRI-guided fusion biopsy of 
the prostate.  Written informed consent will be signed by the patients before the MRI 
examination. 
Exclusion Criteria 
Subjects will be screened and excluded per standard clinical protocol. 
Also excluded are: 
 
Subjects incapable of giving informed written consent; 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 9 of 14 
 
 
Subjects who cannot adhere to the experimental protocols for any reason, 
or have an inability to communicate with the researcher; 
 
Subjects with psychiatric disorders that affect their ability to consent for 
themselves will be excluded and not the entire population of patients with 
psychiatric disorders.  
 
Prisoners; 
 
Minor children (under the age of 18 years old). 
 
Previous treatments (surgery, radiation, focal ablation, hormone or other 
chemotherapy) for prostate cancer. 
 
Data to be collected 
Demographic information will be collected from each recruited subject. The research team 
will also collect clinic visit, laboratory, imaging and pathology results relevant to the clinical 
question for each subject. 
 
J. SHARING RESEARCH RESULTS: 
At times, the advancement of research or the development of healthcare devices is aided 
by the sharing of de-identified image data, pathology data, genetic data and clinical 
information with other organizations. De-identified copies of image data, pathology data, 
genetic data and clinical information may be sent outside of The University of Chicago for 
such purposes, including as part of an image library. If this occurs, scientists outside of 
The University of Chicago will be unable to identify the subject from medical images, 
pathology data, genetic data or from clinical information, because all identifying 
information will have been removed from the images and records. Insurance agencies 
will not have access to this information. 
 
K. POTENTIAL RISKS AND BENEFITS TO SUBJECTS 
Risks Associated with Magnetic Resonance Imaging 
The risks below are the risks of standard MR imaging which the patients will undergo for 
clinical indications. The research component will not cause any additional risk to the 
existing minimal risks of clinical MR imaging. The research sequences will be designed 
in compliance with FDA requirements, and intravenous contrast material will not be 
administered for research purposes.    
The presence of devices, implants, or other objects containing metal: Metal objects pose 
a serious risk to all patients undergoing MRI exams. This includes internally implanted 
objects such as surgical clips, biosupport devices (e.g., pacemakers), and artificial joints 
which contain metal. 
Claustrophobia:  Some individuals may experience claustrophobia during the MRI exam 
due to the limited space available inside the bore of the magnet. 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 10 of 14 
 
Breach of confidentiality: There is a minimal risk that patient confidentiality may be 
breached. 
 
Protection against risks associated with MRI 
Protection against risks related to presence of metals, devices and other metal containing 
material: Participants are questioned carefully before MRI imaging to insure that they do 
not have metal implants. Prospective study participants who have such implants will be 
excluded from the study.  Patients who have worked in or near machine shops and 
electronics shops and may have had metal slivers become trapped in their eyes, posing 
a potential hazard if exposed to a strong magnetic field, will also be excluded from the 
study.  In addition, metal objects such as heavy key chains that are carried into the scan 
room can cause serious accidents.   Participants will be cautioned to remove all metal 
objects before entering the scan room.  Access to the scan room is carefully controlled to 
insure that no ferrous metal is inadvertently brought in. 
Protection against claustrophobia: Prospective participants will be counseled about this 
possibility before the exam.  The magnet is equipped with an intercom system enabling 
study subjects to communicate with the operators at any time during the exam. If they 
report any discomfort during the MRI examination they will be removed from the magnet 
immediately. 
Protection against the breach of confidentiality: Patient identifiers will be kept and used 
only for the purpose of correlating patient data between radiology, urology and pathology.  
Patient identifiers will be removed from data analysis unless it becomes necessary to 
correlate results of the analysis to other clinical data, which we do not expect.  Patient 
identifiers will be removed from all presentations and publications; only data from a group 
of patients will be reported so that data from any individual patient cannot be identified. 
 
Risks associated with Transrectal and Transperineal Ultrasound-Guided Prostate 
Biopsy: 
The risks will be those associated with standard MRI-guided fusion biopsy of the prostate, 
which the patients will undergo for clinical indications. The research component (upto two 
additional biopsy targets) will cause a minimal increase in the risk of bleeding and 
infection. 
 
Benefits 
There may or may not be any direct medical benefit to patients who are enrolled in the 
study.  
There will be a long-term benefit to society in general if this research leads to the 
development of a new technology that improves clinical practice. 
 
Alternatives 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 11 of 14 
 
If patients decide not to participate in this study, they will undergo routine clinical 
examination ordered by their referring physician. 
 
L. PAYMENT TO SUBJECTS 
Patients will not be paid or compensated for their participation in this study. 
 
M.  OBTAINING WRITTEN CONSENT 
The Principal Investigator or Co-Investigators or the Clinical Research Coordinator will be 
responsible for obtaining written informed consent signatures from the patients based on 
the research plan and consent form approved by University of Chicago Institutional 
Review Board.  
Confidentiality will be insured by use of an encrypted patient ID numbering system for all 
research data to maintain confidentiality and anonymity. 
 
N. CONFIDENTIALITY OF RECORDS 
In accordance with the regulations promulgated by the Federal Food and Drug 
Administration, all records will be treated with strict adherence to professional standards 
of confidentiality. Care will be taken during the review of medical records to maintain as 
much privacy as possible. Only the treating physician or study staff will review the medical 
records. Records will be kept locked, and the database will have restricted access 
(password protected). 
Security and Privacy: 
This protocol is designed to respect proper attention to patient privacy and prevention of 
breach of confidentiality. For each patient, the study protocol number and the patient`s 
medical record number will be entered into a restricted database by selected research 
personnel. Additional relevant general clinical information will be included. Access to the 
database will be password protected. All personnel are trained to maintain confidentiality 
of patient information according to HIPAA regulations. All of the images will be maintained 
in the password protected University of Chicago PACS. 
Research charts, including signed consent forms, will be stored in a locked file cabinet in 
the clinical research coordinator’s office at University of Chicago Medical Center, Room 
Q200.  Although each chart, radiographic study, and MRI examination will contain the 
patient’s name, and as such will not be anonymous, no individual identities will be used 
in any publications resulting from this study.  Officials from examining bodies such as the 
U.S. Food and Drug Administration or NIH may inspect records pertaining to this study.  
 
O. PATIENT RECRUITMENT:  
We will recruit patients referred by the UCMC Urology Department, who are scheduled 
for diagnostic MRI exam of the prostate, to be followed by an MRI-guided fusion biopsy 
of the prostate. In addition, patients may also be referred to the study team from other 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 12 of 14 
 
medical centers/hospitals.  The study protocol will be discussed with the patient and the 
study coordinators will consent the patient. 
 
 
BIBLIOGRAPHY AND LITERATURE CITED 
1. Greenhall AM. House bat management. Jamestown, ND: Northern Prairie Wildlife Research 
Center Online; 1982. 
2. Andriole GL, Crawford ED, Grubb RL, 3rd, Buys SS, Chia D, Church TR, Fouad MN, 
Gelmann EP, Kvale PA, Reding DJ, Weissfeld JL, Yokochi LA, O'Brien B, Clapp JD, Rathmell 
JM, Riley TL, Hayes RB, Kramer BS, Izmirlian G, Miller AB, Pinsky PF, Prorok PC, Gohagan 
JK, Berg CD, Team PP. Mortality results from a randomized prostate-cancer screening trial. N 
Engl J Med. 2009;360(13):1310-9. doi: 10.1056/NEJMoa0810696. PubMed PMID: 19297565; 
PMCID: PMC2944770. 
3. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7-30. 
doi: 10.3322/caac.21332. PubMed PMID: 26742998. 
4. Montironi R, Mazzuccheli R, Scarpelli M, Lopez-Beltran A, Fellegara G, Algaba F. Gleason 
grading of prostate cancer in needle biopsies or radical prostatectomy specimens: 
contemporary approach, current clinical significance and sources of pathology discrepancies. 
BJU Int. 2005;95(8):1146-52. doi: 10.1111/j.1464-410X.2005.05540.x. PubMed PMID: 
15877724. 
5. Kvale R, Moller B, Wahlqvist R, Fossa SD, Berner A, Busch C, Kyrdalen AE, Svindland A, 
Viset T, Halvorsen OJ. Concordance between Gleason scores of needle biopsies and radical 
prostatectomy specimens: a population-based study. BJU Int. 2009;103(12):1647-54. Epub 
2009/01/22. doi: 10.1111/j.1464-410X.2008.08255.x. PubMed PMID: 19154461. 
6. Weiner AB, Matulewicz RS, Eggener SE, Schaeffer EM. Increasing incidence of metastatic 
prostate cancer in the United States (2004-2013). Prostate cancer and prostatic diseases. 
2016;19(4):395-7. doi: 10.1038/pcan.2016.30. PubMed PMID: 27431496. 
7. U. S. Preventive Services Task Force. Screening for prostate cancer: U.S. Preventive 
Services Task Force recommendation statement. Ann Intern Med. 2008;149(3):185-91. PubMed 
PMID: 18678845. 
8. Sammon JD, Abdollah F, Choueiri TK, Kantoff PW, Nguyen PL, Menon M, Trinh QD. 
Prostate-Specific Antigen Screening After 2012 US Preventive Services Task Force 
Recommendations. JAMA. 2015;314(19):2077-9. doi: 10.1001/jama.2015.7273. PubMed PMID: 
26575066. 
9. Drazer MW, Huo D, Eggener SE. National prostate cancer screening rates after the 2012 US 
Preventive Services Task Force recommendation discouraging prostate-specific antigen-based 
screening. J Clin Oncol. 2015;33(22):2416-23. doi: 10.1200/JCO.2015.61.6532. PubMed PMID: 
26056181. 
10. 
Thompson IM, Goodman PJ, Tangen CM, Lucia MS, Miller GJ, Ford LG, Lieber MM, 
Cespedes RD, Atkins JN, Lippman SM, Carlin SM, Ryan A, Szczepanek CM, Crowley JJ, 
Coltman CA, Jr. The influence of finasteride on the development of prostate cancer. N Engl J 
Med. 2003;349(3):215-24. doi: 10.1056/NEJMoa030660. PubMed PMID: 12824459. 
11. 
Pondman KM, Futterer JJ, ten Haken B, Schultze Kool LJ, Witjes JA, Hambrock T, 
Macura KJ, Barentsz JO. MR-guided biopsy of the prostate: an overview of techniques and a 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 13 of 14 
 
systematic review. Eur Urol. 2008;54(3):517-27. doi: 10.1016/j.eururo.2008.06.001. PubMed 
PMID: 18571309. 
12. 
Morash C, Tey R, Agbassi C, Klotz L, McGowan T, Srigley J, Evans A. Active surveillance 
for the management of localized prostate cancer: Guideline recommendations. Can Urol Assoc 
J. 2015;9(5-6):171-8. doi: 10.5489/cuaj.2806. PubMed PMID: 26225165; PMCID: PMC4479637. 
13. 
Pokorny MR, de Rooij M, Duncan E, Schroder FH, Parkinson R, Barentsz JO, Thompson 
LC. Prospective study of diagnostic accuracy comparing prostate cancer detection by 
transrectal ultrasound-guided biopsy versus magnetic resonance (MR) imaging with subsequent 
MR-guided biopsy in men without previous prostate biopsies. Eur Urol. 2014;66(1):22-9. doi: 
10.1016/j.eururo.2014.03.002. PubMed PMID: 24666839. 
14. 
Le JD, Stephenson S, Brugger M, Lu DY, Lieu P, Sonn GA, Natarajan S, Dorey FJ, 
Huang J, Margolis DJ, Reiter RE, Marks LS. Magnetic resonance imaging-ultrasound fusion 
biopsy for prediction of final prostate pathology. J Urol. 2014;192(5):1367-73. doi: 
10.1016/j.juro.2014.04.094. PubMed PMID: 24793118; PMCID: PMC4201866. 
15. 
Salami SS, Ben-Levi E, Yaskiv O, Ryniker L, Turkbey B, Kavoussi LR, Villani R, 
Rastinehad AR. In patients with a previous negative prostate biopsy and a suspicious lesion on 
magnetic resonance imaging, is a 12-core biopsy still necessary in addition to a targeted 
biopsy? BJU Int. 2015;115(4):562-70. doi: 10.1111/bju.12938. PubMed PMID: 25252133. 
16. 
Arsov C, Becker N, Rabenalt R, Hiester A, Quentin M, Dietzel F, Antoch G, Gabbert HE, 
Albers P, Schimmoller L. The use of targeted MR-guided prostate biopsy reduces the risk of 
Gleason upgrading on radical prostatectomy. J Cancer Res Clin Oncol. 2015;141(11):2061-8. 
doi: 10.1007/s00432-015-1991-5. PubMed PMID: 26013424. 
17. 
Barentsz JO, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, Rouviere O, 
Logager V, Futterer JJ. ESUR prostate MR guidelines 2012. Eur Radiol. 2012;22(4):746-57. 
Epub 2012/02/11. doi: 10.1007/s00330-011-2377-y. PubMed PMID: 22322308; PMCID: 
3297750. 
18. 
Agarwal HK SJ, Turkbey B, Bernardo M, Nielsen T, Keupp J, Choyke PL, editor. Whole-
prostate T2 mapping in under 6 minutes using autocalibration and partial-Fourier MRI. Proc of 
the 20th Annual Meeting of ISMRM; 2012; Melbourne, Australia. 
19. 
Agarwal HK TB, Alexander V, Bernardo M, Daar D, Sénégas J, Kruecker J, Linehan WM,  
Merino MJ, Pinto P, Wood B, Choyke PL, editor. Fast T2 mapping during MRI for prostate 
cancer. Proc of the 98th Scientific Assembly and Annual Meeting of the RSNA; 2012; Chicago, 
Illinois. 
20. 
Liu W, Turkbey B, Senegas J, Remmele S, Xu S, Kruecker J, Bernardo M, Wood BJ, 
Pinto PA, Choyke PL. Accelerated T2 mapping for characterization of prostate cancer. Magn 
Reson Med. 2011;65(5):1400-6. doi: 10.1002/mrm.22874. PubMed PMID: 21394778; PMCID: 
PMC3079019. 
21. 
Senegas J, Liu W, Dahnke H, Song H, Jordan EK, Frank JA. Fast T(2) relaxometry with 
an accelerated multi-echo spin-echo sequence. NMR Biomed. 2010;23(8):958-67. doi: 
10.1002/nbm.1521. PubMed PMID: 20878973. 
22. 
Does MD, Gore JC. Compartmental study of diffusion and relaxation measured in vivo in 
normal and ischemic rat brain and trigeminal nerve. Magn Reson Med. 2000;43(6):837-44. 
PubMed PMID: 10861878. 
23. 
Sadinsky MS KG, Peng Y, Medved M, Wang S, Oto A., editor. Evaluation of a Novel 
Combined T2-weighted and Diffusion-weighted MR Imaging Sequence for Diagnosis of Prostate 

IRB17-1694 
 
Version Date: 06/10/2022 
Page 14 of 14 
 
Cancer and Determination of Its Aggressiveness: Correlation with Histopathology Following 
Prostatectomy. RSNA, ed Radiological Society of North America; 2014; Chicago, Illinois. 
24. 
Wang S, Peng Y, Medved M, Yousuf AN, Ivancevic MK, Karademir I, Jiang Y, Antic T, 
Sammet S, Oto A, Karczmar GS. Hybrid multidimensional T(2) and diffusion-weighted MRI for 
prostate cancer detection. J Magn Reson Imaging. 2014;39(4):781-8. doi: 10.1002/jmri.24212. 
PubMed PMID: 23908146; PMCID: PMC4251798. 
25. 
Wang S PY, Medved M, Yousuf A, Ivancevic M, Karademir I, Jiang Y, Antic T, Sammet S, 
Oto A, Karczmar G, editor. Hybrid T2 and diffusion weighted MRI for prostate cancer detection. 
Proc Intl Soc Mag Reson Med 21; 2013. 
26. 
Chatterjee A, Bourne R, Wang S, Devaraj A, Gallan AJ, Antic T, Karczmar GS, Oto A. 
Diagnosing prostate cancer through non-invasive estimation of prostate tissue composition 
using Hybrid Multidimensional MRI: A feasibility study. Radiology. (provisionally accepted). 
27. 
Chatterjee A, Watson G, Myint E, Sved P, McEntee M, Bourne R. Changes in Epithelium, 
Stroma, and Lumen Space Correlate More Strongly with Gleason Pattern and Are Stronger 
Predictors of Prostate ADC Changes than Cellularity Metrics. Radiology. 2015;277(3):751-62. 
doi: 10.1148/radiol.2015142414. PubMed PMID: 26110669. 
28. 
Langer DL, van der Kwast TH, Evans AJ, Plotkin A, Trachtenberg J, Wilson BC, Haider 
MA. Prostate tissue composition and MR measurements: investigating the relationships 
between ADC, T2, K(trans), v(e), and corresponding histologic features. Radiology. 
2010;255(2):485-94. doi: 10.1148/radiol.10091343. PubMed PMID: 20413761. 
29. 
Helfrich O, Puech P, Betrouni N, Pincon C, Ouzzane A, Rizk J, Marcq G, Randazzo M, 
Durand M, Lakroum S, Leroy X, Villers A. Quantified analysis of histological components and 
architectural patterns of gleason grades in apparent diffusion coefficient restricted areas upon 
diffusion weighted MRI for peripheral or transition zone cancer locations. J Magn Reson 
Imaging. 2017. doi: 10.1002/jmri.25716. PubMed PMID: 28383776. 
30. 
; The University of Chicago 
Koninklijke Philips N.V., assignee. Non-invasive estimation of prostate tissue composition. 
31. 
Peng Y, Jiang Y, Yang C, Brown JB, Antic T, Sethi I, Schmid-Tannwald C, Giger ML, 
Eggener SE, Oto A. Quantitative analysis of multiparametric prostate MR images: differentiation 
between prostate cancer and normal tissue and correlation with Gleason score--a computer-
aided diagnosis development study. Radiology. 2013;267(3):787-96. doi: 
10.1148/radiol.13121454. PubMed PMID: 23392430. 
32. 
Peng Y, Jiang Y, Antic T, Giger ML, Eggener SE, Oto A. Validation of quantitative analysis 
of multiparametric prostate MR images for prostate cancer detection and aggressiveness 
assessment: a cross-imager study. Radiology. 2014;271(2):461-71. doi: 
10.1148/radiol.14131320. PubMed PMID: 24533870.