Comparison of Socket Geometry and Clinical Outcomes Between Manually- and Digitally-designed Prosthetic Sockets for Lower-limb Amputees: a Feasibility Study
Comparison of Socket Geometry and Clinical Outcomes Between Manually- and Digitally-designed Prosthetic Sockets for Lower-limb Amputees: a Feasibility Study
The most important aspect of a lower-limb prosthesis is the socket as the interface between the human and the mechanical prosthetic system. Proper fit of the socket to the residual limb is a critical factor in determining comfort, suspension, energy expenditure and ultimately the functional efficiency of the remaining prosthesis. Patients may not wear their prosthesis if they find the socket uncomfortable.
Traditional manufacturing of prosthetic sockets is a high-skill process involving several stages. Capturing the shape of the residual limb and modifying the mould is performed with a manual, hands-on approach. This leads to inconsistencies between clinicians, and increases the likelihood of human error. There is opportunity to improve this process with advanced computer-aided design (CAD) and manufacturing (CAM). 3D printing can be leveraged for its ability to effortlessly manufacture one-off, complex and organic shapes, such as prosthetic sockets. However, the digital method removes the tactile feedback that the clinician generally benefits from when manually designing the socket, thus leading to some uncertainty in how they are modifying the socket. Moreover, the difference in the learning curve may cause inconsistencies in modifications made by different clinicians.
While clinicians may be hesitant in their knowledge-transfer from a manual to digital method, sockets designed using CAD still produce successful outcomes. To facilitate wider-spread adoption of 3D printing as a standard tool in the clinic, more research is needed to better understand how the digital design process affects the geometry of the socket, and how this affects clinical outcomes for amputees.
The investigators hypothesize that (1) digitally-designed sockets and manually-designed sockets will have geometric differences, (2) the digitally-designed socket will result in better clinical outcomes compared to manually-designed sockets, and (3) improved clinical outcomes will correlate to geometric differences centred on particular regions of the socket. However, a feasibility study is needed to inform an effective protocol. This feasibility study aims to explore socket geometries and prosthetic outcomes compared between manually-designed and digitally-designed devices for lower-limb amputees. Findings will help in improving the current 3D printing techniques and exploring outcomes for the users.
This crossover case-control feasibility study aims to explore socket geometries and prosthetic outcomes compared between manually-designed and digitally-designed devices for lower-limb amputees. Feasibility and outcome measures will be measured at three major stages of routine prosthetic care, namely the socket fabrication, socket fitting, and functional testing.
Socket Fabrication:
Participants will be measured for the prosthetic device through (1) manual casting using Plaster of Paris bandages and (2) scanning using a 3D scanner (Artec Eva, Artec 3D, Luxembourg). The patient's residual limb soft tissue density will also be measured using a standard gauge (Fowler depth gage, Fowler Co., Inc., Massachusetts, USA) on certain landmarks: medial flare, distal end, lateral, popliteal region, distal tibia. The clinician will manually modify the positive plaster cast (herein, the M-socket) and digitally modify the scanned impression (herein, the AD-socket) using OMEGA software (OMEGA software, WillowWood Global LLC, Ohio, USA). The M-socket positive cast will be digitized by scanning the cast and exporting it to OMEGA. This scanned M-socket file and the CAD-socket file will each be 3D printed (Stratasys F370, Stratasys Ltd., Minnesota, USA) in nylon-based thermoplastic. Conventionally, the socket is manufactured by draping thermoplastic over a mold, but for this study, both sockets will be 3D printed. The two 3D-printed sockets will then be reinforced and connected to its corresponding component adapters using fiberglass and resin materials, as is done during current standard of care. To eliminate confounding, the same suspension and components will be used. Subjects will be given a patient experience survey to score their experience with each shape capturing process. The survey will be administered by a research assistant using a face-to-face interview technique before they are fit with the sockets.
Socket Fitting:
Both sockets will be fitted to the subject and immediate Socket Comfort Score will be recorded through an analogue visual scale, and will be recorded for every day that the patient wears each device. The immediate socket fit will be recorded by the number of filler sock plys needed to be added in the socket. Also, changes made to the sockets by the clinician (e.g., spot relieving) will be recorded. Subjects will continue therapy using the socket that is more comfortable and fits better, based on both the subject's judgment and the judgment of their clinician. If the subject finds both sockets as equally comfortable, he/she will get to choose the preferred socket to continue with for therapy. A healthcare provider will assist in the selection, should the patient request it. The subjects will be given 2 days to acclimate to the selected socket and will be retested for Socket Comfort Score once a day during the subject's therapy sessions, and tested for function one day before discharge (defined below).
Functional Testing:
One day before discharge from West Park, upon the completion of therapy, the participants will be tested for function through the L-test and 2-minute walk test (2MWT). This timeline is to ensure that the participant is safe to walk outside the parallel bars. The L test of functional mobility will be administered with the device. For patient safety, chairs will be placed in close proximity to the testing area, and subjects are allowed to walk with a mobility aid of their choice. One practice run will be allowed, followed by 2 trials with a 1-minute rest between trials. The mean times from the 2 trials will be used for data analysis. As a second measure of function, a 2-minute walk test (2MWT) will be administered after the L-test. To control for learning and practice effects, the subjects will be familiar with the test, or given 1 or more practice tests at least 1 day before testing. Subjects are allowed to walk with a mobility aid of their choice and allowed to rest during the 2-minute time.
The functional tests will be performed in the order described. The functional data will be collected by a member of the team other than the clinician that fits the patient in order to prevent bias in the results. Tests will be administered by a physiotherapist who is not involved in the study to ensure patient safety. To blind the device, the investigators will not disclose to the patient about the method the socket was designed when they first trial it. After the completion of the study, the participant will take the device home.
Clinical outcome measure data will be reported descriptively (mean, SD, minimum and maximum), and a statistical analysis plan detailing intended analyses will be drafted before the completion of data collection to inform a future study. The effect size will be calculated to help support sample size calculations for a future study. Feasibility data will be collected, and success of the feasibility analysis will be determined based on the following a priori criteria: recruitment rate ≥70% of all eligible potential participants; of the participants recruited, ≥70% adhered to the described protocol allowing for effective collection of quantitative and qualitative data appropriate for use in a definitive study; <20% dropped out of the study; SCS, L-test and 2MWT were identified as acceptable and appropriate outcome measures for the protocol; quantitative and qualitative data implied that digitally-designed sockets have different geometries to manually-designed sockets. Recruitment, adherence and drop-out rates will be calculated using the average obtained between the start of the study (once active recruitment starts) and the end of the study (once the desired sample size is reached). This study will decide that a larger study is not feasible if at least one of the criteria is not met.
Inclusion Criteria:
Exclusion Criteria: