(325 Words Max) 4 Background: Quantitative outcomes assessment remains a persistent challenge in orthopaedic 5 trauma. Although patient -reported outcomes measures (PROMs) and radiographic assessments 6 such as RUST scores are frequently used, very little evidence has been presented to support their 7 validity for measuring structural bone formation or biomechanical integrity . 8 Methods: A sequential cohort of tibial shaft fracture patients was prospectively recruited for 9 observation following standard reamed intramedullary nailing in a Level I trauma center . Follow - 10 ups at 6, 12, 18, and 24 weeks included X -rays and completion of PROMs (EQ -5D and pain 11 scores). Low -dose computed -tomography ( CT) scans were also completed at 12 weeks. Scans 12 were reconstructed in 3D and subjected to virtual mechanical test ing via the finite element method 13 to assess fracture limb torsional rigidity relative to intact bone. 14 Results: Patients reported progressive longitudinal improvement in mobility, self -care, activity, 15 and health over time, but the PROMs were not correlated with structural bone healing . RUST 16 scoring showed moderate int ra-rater agreement (ICC = 0.727), but the scores at 12 weeks were not 17 correlated with time to union ( R2 = 0.103, p = 0.193) and were only moderately correlated with 18 callus structural integrity ( R2 = 0.346, p = 0.010). In contrast, patient -specific virtual torsional 19 rigidity (VTR) was significantly correlated with time to union ( R2 = 0.383, p = 0.005) and clearly 20 differentiated one case of delayed union (VTR = 10%, union at 8 months ) from the rest of the 21 normally healing cohort (VTR > 60%, median union time 19 weeks ) using CT data alone. 22 Conclusions: PROMs provide insight into the natural history of the patient experience after tibial 23 fracture, but have limited utility as a measure o f structural bone healing. RUST scoring, although 24 repeatable , is not a valid longitudinal predictor of time to union . In contrast, v irtual mechanical 25 Page 3 of 19 testing from low -dose CT scans prov ides a quantitative and objective structural callus assessment 26 that reliably predicts time to union and may enable early diagnosis of compromised healing . 27 Level of Evidence: Diagnostic Level II. 28 Page 4 of 19 Introduction 29 Clinical research in o rthopaedic trauma requires assessments that can capture the gradual 30 progress of bone healing in the context of the patient’s return to normal activit y. Patient -reported 31 outcome measures (PROMs) such as pain scores and multi -dimensional health status instruments 32 are becoming increasingly central to robust trial design.1–3 Unfortunately, interpreting PROMs 33 data can be challenging in trauma research . For example, in a trial of angular -stable nailing of 34 distal tibia fracture s, pain scores were highly variable and showed a strong trend toward decreasing 35 pain over time without a detectable difference in pain between groups based on fixator type .4 36 Similarly, p ilot data for the Warwick Hip Trauma Evaluation (WHiTE) trial indicated that nearly 37 1,000 patients would be needed detect a clinically significant difference in EuroQol 5-Dimension 38 (EQ-5D) scores between implant groups.5 PROMs data can also lead to non -inferiority 39 conclusions, such as in a recent trial of immediate versus delayed weight -bearing after tibial 40 nailing .6 41 In contrast to PROMs, radiographic asses sments offer the promise of objectivity , but 42 historically have been limit ed by concerns with reliability.7 In response to this need, the 43 Radiographic Union Scale for Tibial Fractures (RUST) score was developed as a structured semi - 44 quantitative method for assessing callus. RUST scoring has demonstrable reliability,8,9 has been 45 adapted for use in distal femur fractures,10 has been used to diagnose nonunion fractures (RUST > 46 10 for union),11–13 and has been adopted in the design of large randomized controlled trials.14 47 Despite this wide use , no data currently exists to assess whether RUST scores are a reliable 48 measure of structural bone healing in clinical, not preclinical, application . 49 Accordingly, the objective of this study was to assess bone healing in a sequential cohort 50 of tibial fracture patients using a comprehensive suite of radiographic and patient -reported 51 Page 5 of 19 outcomes measures and to critically evaluate these instruments with refe rence to a new objective 52 biomechanical gold standard: the torsional rigidity of the fracture d limb relative to the intact bone 53 derived using patient -specific image -based finite element models from low -dose CT scans . 54 Methods 55 Study Design 56 Adult (age 18+ years) tibial shaft fracture patients were prospectively recruited from April 57 1, 2016 to December 31, 2016 in Cork University Hospital, a Level I trauma centre serving 58 southwest Ireland. All fractures were treated by reamed intramedullary na iling. Patients were 59 followed -up at 6, 12, 18, and 24 weeks or until clinical union, which was defined as radiographic 60 union with pain free ambulation. All cases were also reviewed at least one year after surgery. 61 Outcome measures included EQ-5D and NRS pa in scores, RUST scores, and quantitative 62 CT-derived morphometric and structural measures of callus . To minimize bias, RUST scoring was 63 completed by the senior clinician using blinded radiographs that were randomly shuffled such that 64 films from each follow -up were not presented in chronological order or grouped by patient. RUST 65 scores were repeated on the blinded shuffled films by the same rater after a period of four months 66 to assess intra -rater agreement. None of the CT-derived measures were made available for 67 comparison to the RUST scores or clinical findings until after all evaluations were completed. 68 The study design was reviewed and approved by the local Institutional Review Board and 69 all patients provided written informed consent. 70 CT Scan Protocol 71 Patients underwent l ow-dose CT scan ning at 12 weeks after surgery. CT scans were 72 performed on a GE (General Electric Healthcare; Waukesha, Wisconsin , USA ) Discovery CT750 73 HD with X -ray tube voltage of 80kV, current -time product of 10mAs, gantry rotation speed of 0.4 74 Page 6 of 19 seconds, and a pitch of 0.51. A pure iterative reconstruction algorithm, M odel-Based Iterative 75 Reconstruction (MBIR) , was used for image reconst ruction with a resolution improvement filter 76 kernel, RP05.15,16 The resulting scan resolution had a slice thickness of 0.625 mm and median pixel 77 spacing of 0.373 mm . 78 CT Scan Processing and Injured Limb R econstruction 79 Image sets were processed using the Mimics Innovation Suite v20 (Materialise ; Leuven, 80 Belgium). A segmentation workflow was developed to create 3D surface models by applying 81 density -based threshold rules to identify different tissues . Callus included tissue within threshold 82 values of 400 -1400 Hounsfield units (HU) and cortical bone included tissue within 1400 -2700 HU. 83 Automated surface optimization sequences were applied to refine the segmented models and then 84 the surfaces were enclosed and volumetrically discretized to create a unified tetrahedral mesh for 85 finite element (FE) analysis. The mesh was refined and elementwise mechanical properties were 86 interpolated from voxel radiodensities using a previously published elastic modulus scalin g law 87 based on local Hounsfield units of the original CT scan: 𝐸 = 0.00704 ×𝐻𝑈 [GPa].17 Each scan 88 was also digitally reconstructed to recreate an intact bone model representative of the pre -injury 89 anatomy. The complete workflow for generating the injured and intact models is summarized in 90 Figure 1 and discussed in detail elsewhere .18 91 A virtual torsion test was chosen as the summary measure of mechanical integrity in each 92 model. Torsional stiffness relative to intact paired controls is often used as a summary indicator of 93 healing in preclinical models ,19–23 because it is direction independent.24 Torsion test ing yields 94 virtual torsional rigidity: 𝑉𝑇𝑅 =𝑀𝐿/𝜙 [N-m2/°], where M is the twisting moment, L is the length 95 of the test segment, and 𝜙 is the angle of twist. All structural simulations were carried out in 96 ANSYS 17.2 (ANSYS; Canonsburg, PA , USA ). 97 Page 7 of 19 Statistical Analysis 98 Descriptive statistics were generated using Microsoft Excel (2016) and MATLAB 99 (R2016a, The MathWorks ; Natick, Massachusetts , USA ). All other statistical analyse s were 100 carried out in IBM SPSS Statistics 24 (IBM Corp ; Armonk, NY, USA). Repeated measures testing 101 for differences over time was carried out using Friedman non-parametric tests as is appropriate for 102 ordinal and non -normally distributed interval data. O ne-way repeated measures ANOVA was also 103 used for testing differences in normally -distributed interval variable s. Relationships between 104 outcomes measures were assessed using Pearson’s correlations. Normality was a ssessed by 105 Shapiro -Wilk and Kolmogorov -Smirnov testing. 106 Sources of Funding 107 Funding to support study management was provided by a grant from OrthoXel, DAC. 108 Results 109 Patient and Injury Characteristics 110 Twenty -four patients me t the inclusion criteria and 19 completed the follow -up protocol 111 including low -dose CT scan (see Figure 2) . Demographic and injury characteristics for these 112 patients are shown in Table 1. The m edian age was 39 years. Two patients (11%) were female and 113 three (16%) had open injuries. The predominant fracture morphology was OTA/AO type A (15 114 cases, 79%). Injury mechanisms included : sport s (5), simple fall (4), blow (3), fall from height (2), 115 crush (2), pedestrian struck by vehicle (2), and other (1). The median time to clinical union was 116 18.7 weeks . There was one delayed union, indicated by progressive autodynamization and eventual 117 union at 36 weeks . There were no nonunions or reoperations to induce union . 118 119 120 Page 8 of 19 Patient Reported Outcome Measures (PROMs) 121 Complete descriptive statistics for all EQ -5D component scores and the NRS pain scores 122 are shown in Table 2 and selected statistically or clinically meaningful temporal trends are 123 illustrated in Figure 3. Patients tended to report significant ly improved mobility, capacity for self - 124 care, engagement in usual activities, and general health over time. Post -hoc testing showed that 125 this trend was generally only statistically significant between the first and the last time points. One 126 exception was the usual activities score, where patients indicated the greatest difficulty at the six - 127 week follow -up, which was significantly different from the scores reported at all later time points. 128 Pain scores were very low for most patients and were steady over time, both in the EQ -5D pain 129 component score and on the NRS pain sca le. 130 RUST Scores 131 RUST scores at the four follow -ups are also shown in Figure 3, together with time to union. 132 The intra -class correlation coefficient, ICC(3,1) for test -retest reliability of RUST scoring with 133 consistency effects (two -way random single measu res procedure in SPSS) was 0.727 (95% CI 134 0.597 – 0.820). RUST scores significantly increased over time ( p = 0.001), and a fter six weeks, 135 became non-normally distributed with a notable ceiling effect, with at least 75% of patients 136 achieving RUST ≥ 10 from 18 weeks onward. 137 CT-Derived Morphometry and Virtual Mechanical Testing 138 Complete morphometric data for each patient -specific model is provided in Table 3, with 139 selected values illustrated in Figure 4. For each patient -specific model , the fractured limb VTR 140 was normalized by that patient’s own reconstructed intact tibia to produce a dimensionless 141 indicator of healing relative to the pre -injury state : normalized VTR . Across all patients , median 142 normalized VTR was 99% (IQR 86% – 113%) at 12 weeks . 143 Page 9 of 19 Correlations between Outcomes Measures 144 Relationships between PROMs , RUST scores, and CT -derived properties at 12 weeks 145 were assessed by Pearson’s correlations. RUST scores were not significantly correlated with CT - 146 derived VTR [N -m2/°] of the fractured or intact tibia (all p > 0.217) , but RUST s cores had a 147 moderate and significant positive correlat ion with normalized (fract ured/intact) VTR ( p = 0.01 0, 148 see Figure 5). Callus volume had no observable correlat ion with normalized VTR ( R2 = 0.012 , p 149 = 0.651). Callus density showed a weak and non -significant correlation with normalized VTR (R2 150 = 0.167, p = 0.0 82). None of the EQ -5D component scores or pain measures were correlated with 151 normalized VTR (all R2 < 0.051, all non -significant ). RUST scores at 12 weeks were not 152 significantly correlated with time to union, but normalized VTR from 12 -week CT was moderately 153 and significantly correlated with the final clinical outcome (see Figure 5). 154 Discussion 155 When evaluating a new clinical assessment method , we must consider whether the 156 technique produces data that is objective (free from bias), precise ( repeatable and reproducible ), 157 systematically accurate (in agreement with true values, when known) , and clinically useful .25 For 158 this discussion, we will focus on the virtual structural analysis technique and its resulting summary 159 parameter, normalized VTR , which indicates the extent of structural healing proportional to the 160 individual’s own intact bone . 161 In terms of objectivity, the workflow for processing CT scans and carrying out structural 162 mechanics simulations follows a pre -defined sequence of actions applied uniformly for all models , 163 with extremely limited opportunity for introduction of researcher bias . The process has been 164 documented in extensive detail elsewhere .18 The strict workflow control produces d ata that is 165 Page 10 of 19 highly repeatable and any two individuals following the proscribed process would produce nearly 166 identical summary measures. 167 The question of systematic accuracy with patient -specific virtual structural analysis is 168 harder to resolve because the torsional rigidity of partially healed human fractures fixed by IM 169 nailing cannot be directly measured . The closest set of available reference data a rises from 170 published values for the torsional rigidity of intact cadaver tibiae, which have an expected mean 171 torsional rigidity of 2.42 ± 0.80 N -m2/° in physical mechanical testing .26 For comparison, the mean 172 intact virtual torsional rigidity of the tibiae in our case series was 2. 32 ± 0.68 N-m2/°, indicating 173 that the modeling technique produces global structural parameters that are clearly within the 174 physiological r ange and very near the accepted reference value based on the limited data available. 175 Systematic model bias may be present , for example in the choice of a mathematical scaling law 176 for defining mechanical properties from radiodensity, but this source of error would be consistent 177 across all models and is likely to be small in light of the close agreement between our results and 178 published cadaver test data . 179 Finally, we consider ed whether virtual structural analysis is clinically useful via an a priori 180 power analysis based on all data collected at 12 weeks . For each outcome measure, we calculated 181 the required sample size to detect clinically meaningful 20% differences between group means, 182 assum ing 80% power and a significance level of 0.05. Based on this data , significant differences 183 between means would be detectable for the following measures with the group sample sizes 184 shown : NRS pain score (N = 273), EQ -5D Mobility Component score (N = 55), objective callus 185 volume from CT (N = 151), RUST score (N = 30), and normalized VTR (N = 30). Notably, unlike 186 in preclinical research, callus volume is not a useful measure of healing progress because the 187 variety of clinical fracture morphologies leads to large variability in the amount of callus . Both 188 Page 11 of 19 RUST score and normalized VTR had similar expected statistical power, but the utility of RUST 189 scoring should be considered carefully due to ceiling effects and known challenges with 190 interpretation and repeatability.9 Furthermore, in this analysis, virtual torsional rigidity at 12 weeks 191 successfully predicted time to union, w hereas RUST scor e did not. 192 Aside from questions of statistical power, t his study also illustrates some concerning 193 limitations of some assessment instruments that are commonly used to assess fracture healing and 194 outcomes. First, our data indicated that PROMs such as EQ -5D may be likely to show a strong 195 regression to the mean effect, in which patients report feeling better over time, independent of their 196 structural healing progress . Published normative population data from the EuroQol Group for 197 individual s in the UK shows that the median self -reported health score across all age groups is 198 90,27 which is precisely equal to the median health score reported by our participants at 24 weeks 199 after surgery. The fact that none of the of the PROMs were significantly correlated with our 200 objective measure of healing —normalized virtual torsiona l rigidity —suggests that PROMs 201 provide insight into the psychological response to injury, but are not be a reliable indicator of the 202 physiological progress of fracture union for nailed tibial fractures . 203 This study also suggest s some potential difficulties with the widely used RUST score. Our 204 RUST scores intra-class correlation coefficient (ICC = 0.727) was comparable to the RUST 205 repeatability recently reported by many other investigators,9,10,22,23,28,29 but was not as good as the 206 original reports.8 Notably, none of the se reports show that RUST scoring meets the strict est 207 definition of ICC>0.9 for an assessment to be deemed “reasonable for clinical measurements ”,30 208 even in studies using simple transverse osteotomies in animal models.22,23 Furthermore, our data 209 indicates that RUST scores may not have prognostic validity for predicting longitudinal outcomes, 210 an issue that was raised early in the history of the RUST scoring,31 but has been neglected in favor 211 Page 12 of 19 of repeated examination of inter - and intra -rater reliability. Interpreted cautiously, our data 212 supports the gen eral conclusion that RUST is useful for differentiat ing between healed and 213 unhealed fractures, but may be lacking in sensitivity and specificity as a surrogate measure of 214 callus structural integrity, particularly in early healing ( non-united RUST < 10). 215 This study has a few noteworthy limitations. First , we have not included any objective 216 activity monitoring, which if available, would provide a valuable comparison to the EQ -5D 217 Mobility and Usual Activities component scores. We also did not collect data on pain or 218 radiographic progress at very early time points (< 6 weeks). By 6 weeks, patients were reporting 219 low levels of pain with limited need for analgesia , so it is possible that more meaningful early pain 220 data may have been missed. The balance between pa in and self-limited activity may also dictate 221 the level of mechanical stimulation that drives callus formation, but this was not quantified in our 222 investigation and may b e important for future study. Finally, although the virtual mechanical test 223 method we have employed shows promise, the sample size was small and stronger inferences about 224 diagnostic or prognostic validity , particularly for early nonunion detection, will require further 225 study. 226 In conclusion, we have shown that normalized virtual torsional r igidity ( VTR ) from CT - 227 derived patient -specific structural models is predictive of final time to union, offers greater 228 statistical power than PROMs, and avoids difficulties associated with RUST scoring such as 229 repeatability and ceiling effects. Patient -specific modeling does incur increased investigational 230 burden compared to using only patient -reported or standard radiographic measures, but in 231 exchange, it offers precision and accuracy that cannot be achieved by those routine assessments . 232 In the future , virtual mechanical testing may be appropriate or even preferable as a main outcome 233 measure in clinical trials designed to compare healing between groups when sensitivity and 234 Page 13 of 19 objectivity are of paramount importance, such as research focused on implant typ e or design , 235 surgical approach, injury characteristics, patient risk factors, or behavioral interventions . 236 Acknowledgements 237 The authors gratefully acknowledge supporting contributions from Karl James MB, FFR 238 (RCSI), Richard Kavanagh MB, FFR (RCSI), and Owen J. O’Connor MB, FFR (RCSI) . 239 Page 14 of 19