Leg edema quantification for heart failure patients via 3D imaging

Methods of ex vivo analysis of tissue status in vascularized composite allografts

Vascularized composite allotransplantation can improve quality of life and restore functionality. However, the complex tissue composition of vascularized composite allografts (VCAs) presents unique clinical challenges that increase the likelihood of transplant rejection. Under prolonged static cold storage, highly damage-susceptible tissues such as muscle and nerve undergo irreversible degradation that may render allografts non-functional. Skin-containing VCA elicits an immunogenic response that increases the risk of recipient allograft rejection. The development of quantitative metrics to evaluate VCAs prior to and following transplantation are key to mitigating allograft rejection. Correspondingly, a broad range of bioanalytical methods have emerged to assess the progression of VCA rejection and characterize transplantation outcomes. To consolidate the current range of relevant technologies and expand on potential for development, methods to evaluate ex vivo VCA status are herein reviewed and comparatively assessed. The use of implantable physiological status monitoring biochips, non-invasive bioimpedance monitoring to assess edema, and deep learning algorithms to fuse disparate inputs to stratify VCAs are identified.

Volumetric assessment of lower limb oedema using 3D laser scanning technique: a systematic review

Clinically, oedema is described as an abnormal build-up of interstitial fluid in the body that is enough to produce palpable swelling. Its assessment offers valuable information to clinicians as this can inform management interventions; and help monitor adherence to home therapy programmes and activity levels. The aim of this systematic review is to establish the utility of 3D scanning technologies in the assessment of lower limb oedema. A computer-based search was completed in October 2020. Four studies were identified which utilised a 3D scanner to measure lower limb oedema. A review of the studies found very little evidence to support the efficacy of 3D laser scanning technology, although they show that the use of the technology is feasible. Current methods of lower leg oedema measurement have issues with reliability, practicability and time taken. There is a need for future studies to validate new methods of oedema assessment using technologies such as 3D laser scanning.

Evaluation of the Accuracy of a Video and AI Solution to Measure Lower Leg and Foot Volume

BACKGROUND AND OBJECTIVES

Peripheral edema, change in foot volume, is a marker of congestion which is regularly assessed in routine clinical care. A novel video and Artificial Intelligence (AI)-based solution used to measure anatomical parameters, including volume and foot length, Heartfelt HF-1, is compared to the laboratory gold standard (water displacement) and a medical disposable measuring tape.

DESIGN SETTING PARTICIPANTS AND MEASUREMENTS

58 healthy volunteers were measured with the Heartfelt device; 22 were also measured with the water displacement method and 19 with the medical tape. Bland-Altman analysis was performed for both volumes and foot lengths. Left/right foot differences provided covariance-corrected standard error of measurement (ccSEM) and minimum detectable difference (MDD) for each measurement method.

RESULTS

Heartfelt device measured volumes displayed excellent correlation to the gold standard (water displacement), with Bland-Altman bias of +32mL ±81mL (1 std.dev). Clinically important change in foot volume is approximately 13%. Water displacement yielded ccSEM of ± 32.1mL and MDD of 90mL (6.7% of average foot volume), while the Heartfelt device measurements yielded ccSEM of ±12.6mL and MDD of 35.3mL (2.6% of average foot volume). The majority of differences were attributable to manual positioning of the patient foot in the waterbath.

CONCLUSION

This study finds that in clinical and non-clinical settings, the Heartfelt device measures foot volume and length more precisely than either the water displacement technique or manual foot length measurements using a medical disposable tape, while having an excellent agreement with these methods.

Prioritizing symptom management in the treatment of chronic heart failure

Chronic heart failure (CHF) is a chronic, progressive disease that has detrimental consequences on a patient's quality of life (QoL). In part due to requirements for market access and licensing, the assessment of current and future treatments focuses on reducing mortality and hospitalizations. Few drugs are available principally for their symptomatic effect despite the fact that most patients' symptoms persist or worsen over time and an acceptance that the survival gains of modern therapies are mitigated by poorly controlled symptoms. Additional contributors to the failure to focus on symptoms could be the result of under‐reporting of symptoms by patients and carers and a reliance on insensitive symptomatic categories in which patients frequently remain despite additional therapies. Hence, formal symptom assessment tools, such as questionnaires, can be useful prompts to encourage more fidelity and reproducibility in the assessment of symptoms. This scoping review explores for the first time the assessment options and management of common symptoms in CHF with a focus on patient‐reported outcome tools. The integration of patient‐reported outcomes for symptom assessment into the routine of a CHF clinic could improve the monitoring of disease progression and QoL, especially following changes in treatment or intervention with a targeted symptom approach expected to improve QoL and patient outcomes.

SmartSock: a wearable platform for context-aware assessment of ankle edema

Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition to being burdensome and expensive, are sometimes not reliable and neglect important contextual factors such as patient's physical activity level and body posture. A novel wearable sensor, namely SmartSock, equipped with accelerometer and flexible stretch sensor embedded in clothing is presented. SmartSock is powered by advanced machine learning, signal processing, and correlation techniques to provide real-time, reliable, and context-rich information in remote settings. Our experiments on human subjects indicate high confidence in activity and posture recognition (with an accuracy of > 96%) as well as reliable edema quantification with intra-class correlation and Pearson correlation of 0.97.