31 Introduction: Plaster casting and manual rectification represent the benchmark prosthetic 32 socket design method . 3D technolog ies have increasing potential for prosthetic limb design 33 and fabrication, especially for enhancing access to these services in lower and middle income 34 countries (LMICs). However, the community has a responsibility to verify the efficacy of 35 these new digita l technologies. This study’s objective was to assess the repeatability of 36 plaster casting in vivo , specifically for clinically -relevant residuum shape and landmark 37 capture , and to compare this with three clinically -used 3D scanners . 38 Materials and Methods: A comparative re liability assessment of casting and 3D scanning was 39 conducted in eleven participants with established transtibial amputation . For each participant, 40 two positive moulds were cast by a prosthetist and digitised using a white light 3D surface 41 scanner. Between casts, each participant’s residuum was scanned. The deviation between 42 scan volumes, cross -sections and shapes was calculated. 43 Results: 95% of the clinically -relevant socket shape surface area had a deviation between 44 manual casts <2.87mm ( S.D. 0. 44mm). The average deviation by surface area was 0. 18mm 45 (S.D. 1.72mm). The repeatability coefficient of casting was 46.1ml (3.47%) for volume, and 46 9.6mm (3.53%) for perimeters . For all clinically -meaningful measures, greater reliability was 47 observed for the Omega scanner, and worse for the Sense and iSense scanners, although it 48 was observed that the Sense scanner perform ance was comparab le to casting (95th percentile 49 shape consistency ). 50 Conclusions: This study provides a platform to appraise new cli nical shape capture 51 technologies in the context of best practice in manual plaster casting , and starts the 52 conversation of which 3D scanning devices are most appropriate for different types of 53 clinical use. The methods and benchmark results may support pro sthetists in acquiring and 54 applying their clinical experience, as part of their continuing professional development. 55 KEYWORDS: 56 amputee, CAD/CAM, consistency, prosthetic socket, plaster casting, rectification, shape 57 error, transtibial, volume error 58 Introdu ction 59 A prosthetic limb user’s functional outcome depends fundamentally upon a 60 comfortable and robust human -prosthesis interface1, which most commonly features a 61 personalised socket. This is especially important after transtibial amputation where 62 individuals may attempt to be more active than those with higher -level amputations, and 63 where the socket -limb load transfer is particularly influenced by the underlying bony 64 anatomy. A variety of transtibial socket design strategies exist, most notably patella -tendon 65 bearing (PTB) and total surface bearing (TSB) approaches . According to P TB principles the 66 residual limb is loaded proportionally to the load tolerance of the underlying soft tissue and 67 bony areas. Despite studies on different aspects of transtibial sockets and residual limbs, there 68 is a lack of knowledge to enable consistent m anufacturing of a comfortable socket and 69 optimal alignment without the need for iterative socket fittings2. 70 Plaster casting and manual rectification is considered the benchmark shape capture 71 and socket design method. It remains the technique whereby the majority of sockets are 72 designe d prior to conventional manufacturing routes3, creating a standard against which new 73 technologies should be measured. A Plaster o f Paris (POP) wrap cast is manually applied 74 over the residuum with the aim to capture a modified shape of the soft tissues. Prosthetists 75 shape the POP during casting for the PTB socket using their hands, to create areas of load 76 bearing around the tibial pl ateau. This shape is used to produce a positive mould, which is 77 subsequently rectified according to similar design principles as listed above . These 78 procedures can be highly individual and are based on the experience, skill, and preference of 79 the individua l prosthetist and their patient4. 80 CAD/CAM technologies (Computer Aided Design / Manufacturing) are established in 81 some communities for residuum shape capture, prosthetic socket design and fabrication, with 82 claimed advantages including higher consistency and a perpetual digital design record. 83 Perceived disadvantages include a clinician learning curve and high capital equipment costs, 84 although the development of lower cost 3D scanning devices ha s been pro posed in an a ttempt 85 to overcome this barrier5,6. Other low -cost devices have been proposed for socket 86 reproduction, including smartphone -based photogrammetry7. However there is relatively little 87 evidence in the scientific literature for the accurac y or reliability of these lower cost devices, 88 either in absolute terms or in comparison to clinically meaningful benchmarks. Benchmark 89 measures might be taken from research on manual plaster methods , the traditional and most 90 frequently used approach . The consistency of plaster cast rectification has been investigated 91 in terms of the location an d depth of focal rectifications4, and the influence of prior activity 92 on the residuum’s volume and shape8. Others have compared hands -off vs. hands -on casting 93 methods in terms of the cast shape radius in a manikin model9, and the cast shape volume and 94 length10. However, more understanding is needed regarding the benchmark metric s relating to 95 the reliability of both clinically -relevant shape metrics and volumetric parameters, against 96 which to compare 3D scanning technologies. 97 This study’s objective was to conduct an in vivo assessment of the r epeatability of 98 plaster casting specif ically for residuum shape capture (i.e. pre -rectification) , employing high 99 accuracy and resolution CAD/CAM scanning and digitised shape analysis techniques5,11,12 100 The motivation was to investigate a comprehensive set of clinically -relevant shape metrics, 101 and provide benchmarking data to assess digital shape capture technologies. The work was 102 approached from a global challenges research perspective , where people may seek lower cost 103 technologies to improve P&O access in lower and middle income countries (LMICs), at the 104 potential expense of a ccuracy and reliability. Therefore, the study was conducted with 105 prosthetists in an ISPO -certified Cambodian P&O school and clinic . 106 MATERIALS AND METHODS 107 An assessment of the reliability of transtibial residual limb casting was conducted , for 108 comparison t o the reliability of 3D scanning with three different devices . Approval was 109 granted by institutional (ERGO 25100) and national ethics boards (Cambodian National 110 Ethics Committee for Health Research 073NECHR). Participants were recruited by 111 convenience samp ling from a single prosthetics centre . All participants’ residual limbs were 112 cast twice during one session, by one of two ISPO -certified prosthetists (authors AT and KB). 113 Negative plaster casts were produced according to the prosthetists’ normal practice w hen 114 producing a patella tendon bearing, supracondylar suspended socket ( Figure 1 A-F). The 115 prosthetists then converted their negative casts into positive moulds and performed light 116 surface abrasion using wire mesh (Figure 1 G). The positive mould shapes were digitised 117 using a structured white light surface scanner (Go!SCAN (Creaform Inc., Lévis, Canada), 118 which was previously shown to have a surface height accuracy of 0.2 mm ± 0.07 mm (mean 119 ± standard deviation error) on a similar object5. Between casts, each participant’s residual 120 limb was scanned by two observer s (ASD and PRW ), to p roduce 3D .stl surface mesh files 121 (Figure 1 H). The study used three scanners in a randomised order : the Creaform Go!SCAN 122 device (equivalent to structured white light Omega scanner, Ohio WillowWood Company, 123 USA), t he 2nd generation Sense scanner and the i Sense / Structure Sensor (3DSystems, USA). 124 125 Figure 1: Participants were cast seated, with a cellophane wrap on their residual limb (A, B). 126 Indentations were marked by palpation either side of the patellar tendon (C) and at the supracondylar 127 level (D). After doffing (E) the posterior shelf and flare for knee flexion was formed with additional 128 plaster (F). Positive moulds were produced and lightly abraded (G). Between casts, the limb was 129 scann ed directly (H). 130 131 According to established methods5,11,13, in the AmpSc an open -source software package14, 132 pairs of scan files were compared. The shapes were aligned in 3D space, using both manual 133 and automated approaches. Rigid r egistration was used to match the pairs of positive mould 134 scans over each other, to assess the pairwise deviation. The shapes were sliced serially from 135 the distal tip to the supracondylar ridge at 1% intervals, and the volume and cross -sectional 136 profile di mensions were calculated using the enclosed cross -section area of each slice, its 137 perimeter length, and the maximal widths in the coronal and sagittal planes . 138 Shape deviation was analysed further using a ‘height’ deviation, presenting the surface - 139 surface n ormal deviation data following the visualisation standard set by Sanders and 140 Severance15. Deviatio ns were mapped between each cast and a direct scan of the participant’s 141 residual limb, and between the pairs of repeat manual casts and scans . 142 Quantitative analysis was conducted in several ways , all using MATLAB (MathWorks, 143 USA) , including : 144 1. Surface shape repeatability was characterised by calculating average and 95th area- 145 percentile surface height deviation between aligned cast or scan pairs (i.e. 95% of the 146 surface area deviate d between s cans by this value or less). 147 2. An Intraclass Correlation Coefficient (ICC) was calculated for reliability16,17 for the 148 eleven volume pairs, and for eleven pairs of perimeter measures from the mid -length 149 of each shape. The ICC(1,1) equation was used for intra -rater repeatability of casting, 150 and the ICC(3,1) equation for inter -rater re producibility of scanning. 151 3. Bland Altman plots18 were used to assess mean and within -subject differences 152 between volume and perimeter measurements, indicating potential bias and changes 153 in variance with measurement size, producing study population mean and standard 154 deviation values for each. One volume measure for e ach participant was plotted, and 9 155 perimeters (at 10% intervals over the proximal 90%). 156 4. Where the Bland Altman plots showed no changes in bias or variance with 157 measurement size, a repeatability coeffic ient (CR) was calculated as √2 x 1.96 x the 158 standard de viation, to give the boundary within which a repeat measurement would lie 159 with 95% probability19. 160 5. Finall y, to provide context to clinically relevant calliper and tape measurements, the 161 pairwise mean absolute difference, root mean squared difference and Pearson 162 correlation coefficients were calculated from the width and perimeter profiles along 163 the shape leng ths. 164 RESULTS 165 Eleven people with established (>2yrs) , unilateral transtibial amputation were 166 recruited and provided informed, written consent. All were male and had their amputation 167 following traumatic injury resulting from landmine or road traffic accide nt; ten had unilateral 168 amputation, and one bilateral. 169 The cast shapes represented a modification of the limb shape in several key regions 170 (Figure 2A&B ), and were similar for all participants . These included focal indentation eithe r 171 side of the patella tendon (ref. Figure 1C), medial and lateral supracondylar indentation (ref. 172 Figure 1D), and relief posteriorly for the hamstring (ref. Figure 1F). Positive shape change 173 was observed distally at the scar site and anteriorly over the tibia (i.e. the cast was larger than 174 the limb in these areas ). 175 Comparison of the repeat casts from the prosthetists revealed a high level of reliability 176 (Figure 2 left). Greatest surface height deviation between casts was observed in regions where 177 the most substantial shape modification s were introduced during casting. The largest 178 deviations were observed in t he posterior block corresponding with the hamstring cut -out, 179 introduced after the cast was removed from the residuum (ref. Figure 1F). The other notable 180 region of deviation between cast shapes was on the distal pos terior aspect associated with the 181 calf muscles and scar site. 182 QUANTITATIVE ANALYSIS 1: SURFACE HEIGHT DEVIATION BETWEEN CASTS AND 183 SCANS: 184 The cast pairs were compared quantitatively ( Table 1). There was no apparen t 185 systematic error or bias between first and second casts (across participants, mean surface 186 height error -0.18 mm, range from -0.70 to +0.5 5 mm). Consistency between cast pairs of 187 local shape capture and modification is represented by the standard deviati on in surface 188 height over the surface area (across participants, mean 1.72 mm, range 1. 07 to 2.16 mm). On 189 average across the participants, 95% of the shape surface area had an absolute deviation 190 between casts of <3.60 mm (S.D. 0. 81 mm). In addition, 95% of the surface area most 191 clinically relevant to socket -limb loading (patella tendon to distal tip, below the eventual 192 socket brim) had a deviation between casts of <2.87 mm (S.D. 0. 44 mm). 193 Pairwise Cast Deviations /mm Pairwise Go!SCAN / Omega Scan Deviation s /mm Pairwise Sense Scan Deviations /mm Pairwise iSense Scan Deviations /mm Participant Mean Cast Volume (l) Raw mean (s.d.) Absolute 95th percentile Raw mean (s.d.) Absolute 95th percentile Raw mean (s.d.) Absolute 95th percentile Raw mean (s.d.) Absol ute 95th percentile Full Surface Patella Tendon to Distal Tip 1 1.299 0.55 (2.16) 4.05 3.21 -0.02 (0.39) 0.71 -0.57 (1.04) 2.14 -0.01 (2.34) 4.40 2 1.477 0.34 (2.15) 4.60 3.24 0.10 (0.54) 1.05 1.02 (1.03) 2.87 - - 3 1.649 0.31 (1.52) 3.48 2.80 0.00 (0.69) 1.34 0.21 (1.21) 2.54 0.45 (2.02) 3.68 4 1.109 -0.18 (1.17) 2.75 2.34 0.07 (0.34) 0.74 -0.61 (1.11) 2.42 -1.76 (2.16) 5.22 5 1.296 -0.70 (1.94) 4.31 3.43 -0.20 (0.42) 0.94 -0.04 (0.84) 1.78 -0.30 (1.39) 2.86 6 1.010 -0.14 (1.95) 4.74 3.04 0.09 (0.49) 0.96 0.69 (1.44) 3.16 0.51 (1.53) 2.77 7 1.628 0.08 (1.54) 3.27 3.01 -0.16 (0.42) 0.86 -0.01 (1.51) 2.68 -0.74 (1.69) 3.56 8 1.299 -0.56 (1.95) 4.09 2.95 -0.15 (0.81) 1.42 -0.59 (1.07) 2.68 -0.52 (1.69) 3.93 9 0.807 -0.37 (1.66) 3.22 3.19 0.07 (0.52) 1.00 0.13 (1.26) 2.60 -0.17 (1.39) 2.95 10 1.383 -0.21 (1.07) 2.36 2.10 0.05 (0.42) 0.81 -0.98 (1.44) 3.14 0.11 (2.01) 3.86 11 1.154 0.01 (1.75) 2.70 2.28 -0.10 (1.51) 1.58 0.99 (1.13) 2.89 0.03 (1.01) 2.02 Mean (s.d.) 1.283 (0.25 5) -0.18 (1.72) 3.60 (0.81) 2.87 (0.44) -0.02 (0.60) 1.04 (0.29) 0.02 (1.19) 2.63 (0.41) -0.22 (1.57) 3.53 (0.92) Table 1: Reliability of residual limb cast and scan surface height measurement expressed as 194 mean (s.d.) raw deviation and 95th percentile absolute deviation between cast or scan pairs, by 195 area. 196 The scanned shapes represented a non -contact characterisation of the residual limb 197 shape, i.e. without any soft tissue manipulation or pre -rectification landmarking. Comparison 198 of the repeat scans revealed differing reliability between devices (Figure 2 right) , and l ess 199 spatial trend in surface height deviation was observed between scans than between casts . The 200 scan pairs were compared quant itatively ( Table 1). The Omega scanner was more reliable 201 than casting, the Sense scanner was similar and the iSense scanner less reliable. Systematic 202 error or bias between first and second scans for any device was small compared to the 203 scanner’s corresponding c onsistency (standard deviation in surface height deviation over the 204 surface area of 0.60 mm for Omega, 1.19 mm for Sense and 1.57 mm for iSense ). On average 205 across the participants, 95% of the surface area from patella tendon to distal tip (below the 206 eventual socket brim) had a deviation between casts of <1.04 mm (S.D. 0.29 mm) for Omega, 207 <2.63 mm (S.D. 0.41 mm) for Sense and <3.53 mm (S.D. 0.92 mm) for iSense . 208 209 Figure 2: Scan surfa ce deviation plots for one example participant: casts 1 and 2 vs. limb scan (A&B), 210 and absolute deviation between cast 1 vs. cast 2 (C). Absolute deviations between scans are plotted 211 for the Omega (D), Sense (E) and iSense (F) scanners. 212 QUANTITATIVE ANALY SIS 2 -4: VOLUME AND SERIAL SECTION PERIMETER 213 DEVIATION BETWEEN CASTS 214 The intra -prosthetist residual limb casting repeatability ( Table 2) was calculated from 215 raw cast volume data, and perimeters at 10% increments al ong the cast length , represented on 216 Bland -Altman plots (Figure 3, Figure 4). Casting and all scanners had very high ICC(1,1) 217 scores, above 0.977. No volume or perimeter bias was observed between first and second 218 casts or scans with any device . The standard deviation of pairwise volume differences of 16.6 219 ml equates to a repeatability coefficient of 46.1 ml or 3.47% (Figure 3 top left). The 220 repeatability coefficient f or cast perimeters was 9.6 mm or 3.53% (Figure 4 top lef t). For both 221 measures, casting lay between the Omega and Sense scanners for repeatability, with the 222 iSense scanner less repeatable. 223 Absolute /ml Relative /% Reliability Test (Cast 1 vs. Cast 2 or Scan 1 vs. Scan 2) Pairwise Difference (mean ± SD) Repeatability Coefficient Pairwise Difference (mean ± SD) Repeatability Coefficient ICC t-test p-Value Volume Cast -1.1 ± 16.6 46.1 -0.17 ± 1.25 3.47 0.998 * <0.0 01 Go!SCAN / Omega -1.0 ± 8.8 24.3 -0.02 ± 0.65 1.81 0.999 <0.001 Sense 27.8 ± 28.5 78.8 2.02 ± 1.89 5.23 0.994 <0.001 iSense 21.0 ± 44.2 122.4 1.67 ± 3.23 8.94 0.980 <0.001 Perimeter Cast 0.46 ± 3.46 9.60 0.15 ± 1.27 3.53 0.99 7* <0.001 Go!SCAN / Omega 0.08 ± 1.77 4.91 0.00 ± 0.61 1.69 0.999 <0.001 Sense 4.04 ± 5.53 15.32 1.33 ± 1.81 5.03 0.994 <0.001 iSense -0.10 ± 7.24 20.07 0.09 ± 2.56 7.10 0.978 <0.001 Table 2: Intra -rater reliability statistics on volume and perime ter measures obtained from digital 224 measures from Omega scans of cast pairs (n=11), and direct limb scan pairs by Omega (n=11), Sense 225 (n=11) and iSense (n=10). * Cast -cast intra -rater reliability used equation ICC(1,1); scan -scan inter - 226 rater reliabilities u sed equation ICC(3,1). 227 228 Figure 3: Bland -Altman plots of pairwise difference in volume measures for casting and the three 229 scanners (one measure per limb). 230 231 Figure 4: Bland -Altman plots of pairwise differe nce in perimeter measures for casting and the three 232 scanners (9 measures per limb, at 10% intervals along length). 233 234 QUANTITATIVE ANALYSIS 5: WIDTH AND PERIMETER PROFILE DEVIATION 235 BETWEEN CASTS 236 Width and perimeter profiles along the residuum length were use d for further 237 inspection of the shape deviation between casts and scans ( Figure 5, Table 3). All cast 1 vs. 238 cast 2 measures were highly correlated (r = 0.993 -0.999 ), and all width measurements 239 deviated by less than 3.25 mm. Slightly greater difference between measures was observed 240 for the coronal (M-L) compared to sagittal width (A-P) measurements. This may be attributed 241 to the residuum having lower flexibility in the anterio r-posterior direction than the medial - 242 lateral direction, owing to the bony tibial crest . Conversely, no difference was observed 243 between coronal and sagittal width reliability for the non -contact scan -based measurements. 244 The Sense and iSense scanners had si milar median and interquartile range deviations, both 245 larger than casting, and the Omega scanner was again observed to be the most reliable tool. 246 Absolute Difference /mm Relative Difference /% Measure (Cast 1 vs. Cast 2) Root Mean Squared Mean Absolute Root Mean Squared Mean Absolute Pearson Corr elation Coefficient Sagittal Width (Anterior -Posterior) Cast 1.355 (1.098 - 1.722 ) 1.055 (0.863 - 1.448 ) 1.634 (1.158 - 2.051 ) 1.266 (0.927 - 1.660 ) 0.997 (0.996 - 0.999 ) Go!SCAN / Omega 0.553 (0.391 - 0.729 ) 0.427 (0.310 - 0.521 ) 0.634 (0.383 - 0.682 ) 0.383 (0.327 - 0.613 ) 1.000 (0.999 - 1.000 ) Sense 2.311 (1.347 - 3.663 ) 2.005 (1.101 - 3.228 ) 2.802 (1.451 - 4.171 ) 2.159 (1.136 - 3.949 ) 0.999 (0.998 - 1.000 ) iSense 2.519 (1.663 - 3.580 ) 2.238 (1.428 - 3.197 ) 2.930 (1.701 - 4.559 ) 2.659 (1.416 - 4.33 7) 0.999 (0.999 - 0.999 ) Coronal Width (Medial -Lateral) Cast 2.123 (1.312 - 2.420 ) 1.630 (1.069 - 1.992 ) 2.101 (1.465 - 2.420 ) 1.643 (1.236 - 2.005 ) 0.994 (0.993 - 0.995 ) Go!SCAN / Omega 0.735 (0.646 - 0.829 ) 0.507 (0.468 - 0.677 ) 0.714 (0.635 - 0.811 ) 0.550 (0.458 - 0.631 ) 0.999 (0.998 - 1.000 ) Sense 2.042 (1.446 - 2.516 ) 1.635 (1.186 - 2.179 ) 2.337 (1.476 - 2.700 ) 1.779 (1.205 - 2.352 ) 0.998 (0.996 - 0.999 ) iSense 2.516 (2.009 - 3.048 ) 2.213 (1.798 - 2.655 ) 2.651 (2.112 - 3.070 ) 2.267 (1.898 - 2.59 4) 0.997 (0.995 - 0.998 ) Perimeter Cast 3.121 (2.673 - 3.589 ) 2.324 (1.948 - 2.472 ) 1.003 (0.885 - 1.116 ) 0.823 (0.728 - 0.898 ) 0.998 (0.997 - 0.999 ) Go!SCAN / Omega 1.477 (1.310 - 1.870 ) 0.786 (0.465 - 1.047 ) 0.534 (0.450 - 0.638 ) 0.410 (0.356 - 0.498 ) 0.999 (0.999 - 1.000 ) Sense 5.088 (4.213 - 8.023 ) 4.616 (3.733 - 6.377 ) 1.841 (1.551 - 2.974 ) 1.511 (1.201 - 2.260 ) 0.997 (0.998 - 0.999 ) iSense 5.043 (4.329 - 8.000 ) 3.404 (2.382 - 5.474 ) 1.684 (1.447 - 2.849 ) 1.350 (1.153 - 2.327 ) 0.996 (0.995 - 0.997) Table 3: Intra -rater reliability statistics for clinically -relevant measures of width and cross - 247 section perimeter profiles. Data were non -parametric, so presented as median (interquartile range). 248 249 Figure 5: Intra -rater reliability of casting and scanning for clinically relevant m easures of sagittal and 250 coronal plane widths, and perimeters, expressed by box and whisker plots. 251 DISCUSSION 252 This study set out to conduct a new, high -resolution assessment of the repeatability of 253 plaster casting , using gross volume and detailed shape metrics, specifically in the context of 254 clinically relevant residuum shape capture. The intention was to provide stringent but 255 appro priate benchmarking data for reliability of other technologies including 3D scanners and 256 pressure casting. Exemplar measures were conducted for three 3D scanners in current clinical 257 and research use, selected to cover a range from established, high accurac y devices to low 258 cost consumer products. Participants with transtibial amputation were recruited to assess 259 manual plaster cast and CAD/CAM methods in prosthetic device design and fabrication. In 260 an effort to contribute most clearly to the clinical communit y the present study’s results are 261 presented in a consistent manner to the standards of data visualisation established by Sanders 262 and Severance15, and a consensus of the statistical methods presented by Seminati et al13 and 263 Kofman et al20. 264 Considering consistency in both detailed shape measures and gross volume and 265 perimeter measures, t he high specification Omega scanner was more reliable than casting, 266 and the Sense scanner was similar or less reliable. T he iSense scanner was the least reliable in 267 all tests . Considering clinically -comparable measures of residuum width and perimeter 268 profiles , the Sense and iSense scanners had similar deviations, both larger than casting, and 269 the Omega scanner was again observed to be the most reliable tool. 270 To provide c linical context , we can compare casting variability to clinically 271 manageable volume changes . Lilja and Öberg21 proposed that the volume change 272 corresponding to donning one (+5%) and two stockings (+10%) is clinically significant, as a 273 new socket is typically prescribed once two stockings are required. Sanders and colleagues 274 reported that a limb volume change of ~6% (simulated by a uniform ±1.8 mm socket surface 275 offset)22 may p roduce clinically detectable effects on gait, quality of fit, comfort and 276 satisfaction measures. In the present study the repeatability coefficients of casting volume 277 and perimeter were both ~3.5%, below these indicated limits for clinical significance. All 278 these measurements’ ICC scores also comfortably exceeded the 0.90 threshold for clinically - 279 relevant reliability23. These values were also below that reported for volume change upon 280 muscle activation during casting , with a mean deviation of +5.5% (range -4.2% to +14.2%)24. 281 A recent study identified similar variability in volume and perimeter measures for transtibial 282 sockets produced by casting and the Biosculptor CAD/CAM method, for a single 283 individual25, and t he absolute volume reliability measures were slightly better than ac hieved 284 using water displacement26. 285 Considering the more detailed shape measures, t he mean surface height deviation in 286 serial castings was larger in 6 of the 11 participants than the +0.25 mm socket manufacturing 287 bias (mean radial e rror) reported by Sanders et al27 as clinically noticeab le (Table 1). 288 However, the present data includes the more variable residuum tip, and deviation was less 289 than the thickness of a 1 -ply sock28 in all cases. The mean height error was smaller than the 290 +0.25 mm bias for all 11 participants with the Omega scanner, but larger for 7/11 participants 291 with the Sense and for 6/10 participants with the iSense. This study’s high resolution shape 292 deviation mapping extends prior casting reliability investigations which considered global 293 metrics including volume, length and cross section area9,10 to compare casting methods, and 294 analysis of rectifications subsequent to the shape capture itself 4. The most notable prior 295 application of these shape deviation mapping techniques to casting was conducted by Sanders 296 et al, addressing the specific question of the influence of the time delay between an activity 297 protocol and casting8. 298 Considering other clinical measurement tools, the width and perimeter measurement 299 reliability for casting was in the same range or slightly lower than the calliper, tape measure 300 and anthropometer data presen ted by Geil29. Shape and volume reliability data were 301 comparable to those obtained from existing CAD scanning technologies5,13,20,30 and the lower 302 cost scanners were comparable to smartphone photog rammetry for digitising sockets7. The 303 standard deviation and 95th percentile surface height difference between casts, indicative of 304 the greatest local variability in shape c apture, were similar to the focal rectification 305 consistency data reported by Convery et al4. 306 The present study’s main limitation is a relatively small convenience sample with 307 restricted inclusion criter ia, representing amputation due to trauma only (landmines and road 308 traffic accidents) , and as such may have limited generalisability . Indeed, i t should be noted 309 that the present ed data are relevant to transtibial residual limb casting only, and may not be 310 directly applied to other amputation levels or orthoses that have greater reliance upon bony 311 prominences. A recent review31 concluded that shape capture tools “require more consistent 312 ‘gold standards’” and highlighted a lack of CAD assessm ents on residual limbs, where most 313 prior work has used models. This study offers in vivo benchmarks, and the participant cohort 314 represent s a stringent benchmarking test for new technologies, as several of the more 315 established participants displayed slender , long residual limbs with clear bony prominences, 316 and would be expected to produce more consistent contact -based shape measurements than 317 individuals with more fleshy residua. 318 This study only included two prosthetists, although one was a recent graduate a nd the 319 other had 18 years’ clinical experience. Further, we did not address inter -prosthetist 320 variability , as it is likely that different prosthetists would each produce differently shaped 321 sockets that would achieve acceptable user comfort. The study also considers variability 322 arising from plaster casting for residuum shape capture and landmarking for subsequent 323 rectification, but not variability in the final rectification features. The presented data are 324 intended for use in appraisal of other shape capture methods; consistency of subsequent 325 rectifications may be compared to the results prese nted by Convery et al4. As a final key 326 limitation, it is acknowledged that the relationship between socket comfort and socket fit is 327 not understood31, and assessing user satisfaction with sockets produced by the different 328 approaches was outside this study’s remit. 329 In an LMIC clinical context, important discussion should consider the specific use of 330 3D scanning and other CAD/CAM technologies. There are risks associated with embedding 331 these digital technologies in established manual plaster -based socket design and fabrication 332 workflows, and with present CAD/CAM technologies the crucial sustainable mainten ance, 333 servicing and replaceability factors of Appropriate Technologies may not yet be met32. There 334 are different use cases for these 3D technologies short of adopting a full CAD/CAM 335 workflo w, such as i) replication of a well -fitting but damaged or lost manual socket7, ii) 336 detailed residual limb volume and shape surveying, and iii) remote assessment for individuals 337 who c annot easily attend P&O clinics. Regarding socket replication, the ‘well -fitting’ c aveat 338 is key, as the residuum’s volume and shap e are known to change over time as well as 339 fluctuate, and it is uncommon for sockets to wear out. Anecdotally, some clinicians perform 340 residuum s hape capture by plaster casting and then proceed to digitise the cast by 3D 341 scanning, prior to CAD rectification and CNC fabrication. Different levels of scanning 342 accuracy and reliability will be necessary for these different cases, with greatest accuracy 343 required for socket replication and cast digitisation. Lower spe cification devices may offer 344 benefits instead for enhancing LMIC P&O service access for people living in remote 345 communities , but not at the expense of providing an accurate, well -fitting socket . There is a 346 moral imperative to ensure that only appropriate t echnology is deployed, which has been 347 tested and validated for the particular P&O service in question, irrespective of geograph ical 348 or financial constraints . Furthermore, i t is essential that these digital methods and devices, 349 high or low cost, are not see n as a replacement for clinician training. As a fundamental 350 principle of ethical research and development, all new technologies must be proven before 351 clinical use, as we must prove the prosthetic devices themselves . 352 This study’s results support the establi shed body of evidence around plaster casting as 353 the benchmark of prosthetic socket design, whereby expert prosthetists apply their skill and 354 experience, and against which novel technologies should be measured. Three case -study 355 devices in current clinical u se were compared, and different use -cases proposed. A ppraisal of 356 new technologies should consider quantitative accuracy and reliability metrics alongsid e 357 qualitative usability factors20 and ultimately prosthesis user outcome measures10,33 and 358 acceptability scoring34. This study presents one element of the data to support such appraisal 359 and selection of appropriate technologies . The shape capture and measurement method may 360 also support prosthetists in measuring their plasterwork skills as part of their training and 361 continuing professional development. 362 ACKNO WLEDGEMENTS 363 The authors are grateful to funders the Engineering and Physical Sciences Research 364 Council (EPSRC) / National Institute for Health Research (NIHR) Global Challenges 365 Research Fund (grants EP/R014213/1 & EP/N02723X/1), and the Royal Academy of 366 Engineering (RAEng grant RF/130). 367 The authors thank Exceed Worldwide for facilitating, and Thearith Heang, Carson 368 Harte and Sam Simpson of the Exceed Research Network (ERN) for providing critical 369 review. We also thank the University of Southampton’s Institu te for Life Sciences / FortisNet 370 interdisciplinary musculoskeletal research network for supporting our preliminary work. 371 We have no conflicts of interest relevant to this study. 372 Data availability Supporting data are openly available from the University of 373 Southampton repository at https://doi.org/10.5258/SOTON /D0381 NOTE: TO BE 374 ACTIVATED UPON PUBLICATION. 375