SMART Lab (Skeleton Movement Analysis and Advanced Rehabilitation Technologies)-Bioengineering & Biomedicine Company Srl, Pescara, Italy.
Department of Neuroscience, Imaging and Clinical Sciences University G. D'Annunzio, Chieti-Pescara, Italy.
PLoS One. 2021 Mar 4;16(3):e0247915. doi: 10.1371/journal.pone.0247915. eCollection 2021.
Elevated plantar pressures represent a significant risk factor for neuropathic diabetic foot (NDF) ulceration. Foot offloading, through custom-made insoles, is essential for prevention and healing of NDF ulcerations. Objective quantitative evaluation to design custom-made insoles is not a standard method. Aims: 1) to develop a novel quantitative-statistical framework (QSF) for the evaluation and design of the insoles' offloading performance through in-shoe pressure measurement; 2) to compare the pressure-relieving efficiency of traditional shape-based total contact customised insoles (TCCI) with a novel CAD-CAM approach by the QSF.
We recruited 30 neuropathic diabetic patients in cross-sectional study design. The risk-regions of interest (R-ROIs) and their areas with in-shoe peak pressure statistically ≥200kPa were identified for each patients' foot as determined on the average of peak pressure maps ascertained per each stance phase. Repeated measures Friedman test compared R-ROIs' areas in three different walking condition: flat insole (FI); TCCI and CAD-CAM insoles.
As compared with FI (20.6±12.9 cm2), both the TCCI (7±8.7 cm2) and the CAD-CAM (5.5±7.3 cm2) approaches provided a reduction of R-ROIs mean areas (p<0.0001). The CAD-CAM approach performed better than the TCCI with a mean pressure reduction of 37.3 kPa (15.6%) vs FI.
The CAD-CAM strategy achieves better offloading performance than the traditional shape-only based approach. The introduced QSF provides a more rigorous method to the direct 200kPa cut-off approach outlined in the literature. It provides a statistically sound methodology to evaluate the offloading insoles design and subsequent monitoring steps. QSF allows the analysis of the whole foot's plantar surface, independently from a predetermined anatomical identification/masking. QSF can provide a detailed description about how and where custom-made insole redistributes the underfoot pressure respect to the FI. Thus, its usefulness extends to the design step, helping to guide the modifications necessary to achieve optimal offloading insole performances.
足底压力升高是导致神经性糖尿病足溃疡(NDF)的一个重要危险因素。通过定制鞋垫进行足部减压对于预防和治疗 NDF 溃疡至关重要。目前,针对定制鞋垫的减压效果,还没有标准的定量评估方法。目的:1)开发一种新的定量统计框架(QSF),通过鞋内压力测量来评估和设计鞋垫的减压性能;2)通过 QSF 比较传统的基于形状的全面接触定制鞋垫(TCCI)与新型 CAD-CAM 方法的减压效率。
我们采用横断面研究设计,招募了 30 名神经性糖尿病患者。根据每位患者在每个站立阶段获得的峰值压力图谱的平均值,确定每个患者足部的感兴趣的风险区域(R-ROI)及其鞋内峰值压力统计学上≥200kPa 的区域。重复测量 Friedman 检验比较了三种不同行走条件下 R-ROI 区域:平底鞋垫(FI)、TCCI 和 CAD-CAM 鞋垫。
与 FI(20.6±12.9cm2)相比,TCCI(7±8.7cm2)和 CAD-CAM(5.5±7.3cm2)方法均能减少 R-ROI 的平均面积(p<0.0001)。CAD-CAM 方法比 TCCI 更有效,其平均压力降低了 37.3kPa(15.6%),与 FI 相比。
CAD-CAM 策略比传统的仅基于形状的方法具有更好的减压效果。引入的 QSF 为文献中概述的直接 200kPa 截止方法提供了一种更严格的方法。它为评估减压鞋垫设计和后续监测步骤提供了一种统计学上合理的方法。QSF 允许对整个足底表面进行分析,而无需预先确定解剖识别/掩蔽。QSF 可以详细描述定制鞋垫如何以及在何处重新分配足底压力,相对于 FI。因此,它的用途扩展到设计阶段,有助于指导实现最佳减压鞋垫性能所需的修改。