Software Medical Device Research Articles

Assessing the Heterogeneity of Response of [68Ga] Ga-PSMA-11 PET/CT Lesions in Patients With Biochemical Recurrence of Prostate Cancer

IntroductionTreatment of men with metastatic prostate cancer can be difficult due to the heterogeneity of response of lesions. [68Ga]Ga-PSMA-11 (PSMA) PET/CT assists with monitoring and directing clinical intervention; however, the impact of response heterogeneity has yet to be related to outcome measures. The aim of this study was to assess the impact of quantitative imaging information on the value of PSMA PET/CT to assess patient outcomes in response evaluation. Patients and MethodsBaseline and follow-up (6 months) PSMA PET/CT of 162 men with oligometastatic PC treated with standard clinical care were acquired between 2015 and 2016 for analysis. An augmentative software medical device was used to track lesions between scans and quantify lesion change to categorize them as either new, increasing, stable, decreasing, or disappeared. Quantitative imaging features describing the size, intensity, extent, change, and heterogeneity of change (based on percent change in SUVtotal) among lesions were extracted and evaluated for association with overall survival (OS) using Cox regression models. Model performance was evaluated using the c-index. ResultsForty-one (25%) of subjects demonstrated heterogeneous response at follow-up, defined as having at least 1 new or increasing lesion and at least 1 decreasing or disappeared lesion. Subjects with heterogeneous response demonstrated significantly shorter OS than subjects without (median OS = 76.6 months vs. median OS not reached, P < .05, c-index = 0.61). In univariate analyses, SUVtotal at follow-up was most strongly associated with OS (HR = 1.29 [1.19, 1.40], P < .001, c-index = 0.73). Multivariable models applied using heterogeneity of change features demonstrated higher performance (c-index = 0.79) than models without (c-index = 0.71-0.76, P < .05). ConclusionAugmentative software tools enhance the evaluation change on serial PSMA PET scans and can facilitate lesional evaluation between timepoints. This study demonstrates that a heterogeneous response at a lesional level may impact adversely on patient outcomes and supports further investigation to evaluate the role of imaging to guide individualized patient management to improve clinical outcomes.

Monitoring Patient Reported Outcomes in PNH: Interim Results of a Market Research with florio ® PNH

Background: Patients withparoxysmal nocturnal hemoglobinuria (PNH), an ultra-rare, acquired disorder, report various cardiovascular, gastrointestinal, neurological or hematological symptoms that can severely impact their physical functioning and health-related quality of life. Patients may require long term treatment with anti-complement therapies to alleviate PNH symptoms or complications. Whilst blood biomarkers can aid the monitoring of disease progression, patient reported outcomes (PRO) and related symptoms are also of value in assessing response to therapy, but they are not always continuously tracked by patients. Hence florio PNH, a software medical device (smartphone app), was designed to allow easy monitoring of PRO and tracking of medication by patients. It allows documentation of therapy and common symptoms as well as hemoglobin and LDH levels. florio PNH can send treatment reminders and compiles the entered data into a patient report. Patients were invited to participate in market research of florio PNH to better understand monitoring habits and expectations towards an app in this area. Methods: Twenty patients were invited to participate in market research sponsored by Florio GmbH. The participants came from the UK PNH service centre in Leeds and were selected by the coordinating clinical team at routine clinic visits. The research was submitted for ethics approval and written informed consent was provided. The market research consisted of a one hour entry interview assessing current behavior and expectations towards monitoring of outcomes, followed by an eight-week period of field-testing florio PNH app. The subsequent one hour exit interview explored the user experience with the app, and which app features were seen of value, of less value or were missing. A total of 20 patients are to be enrolled in the research, of which 17 had completed the initial interview at the time of this report. Results: The majority of participants were 50 years of age or older (59%) and described themselves as “not tech savvy”. Six participants rated the impact of PNH on their life as significant, 6 as somewhat and 5 as little to none. Fatigue was named by 10 patients unprompted as the prominent symptom affecting their social and work life. Before the research, three participants neither tracked symptoms nor reported medication, five tracked both, seven only tracked their anti-complement infusions and two only major events when they happened. Forty seven percent of participants (8 of 17) did not prepare information at all for clinical consultations in advance, as they either experienced few events or relied on their memory. All users managed to install the app, set up their account and log events without problem. The app was described as easy to use, straightforward and participants appreciated that all data was in one location and possible to summarize into a report. Sixteen (94%) patients said that they believe the app will help them track events and that they would be enthused to use it in the future. Conclusions: Monitoring applications are employed in several rare bleeding disorders and have been shown to be valuable assets for collecting patient reported outcomes, especially in the outpatient setting. Participants of this research had no experience with using disease specific apps for collecting outcomes, and usually rely on the calendar functions provided by their smartphones or paper diaries. 94% concluded that the app will help them organize their PNH data, share data with their treating clinical team, better plan their future activities and be reminded when the next treatments are due.

A novel recognition of artificial intelligence in regional anaesthesia

Mechanised analysis of algorithms for problem solving, object recognition and decision-making assistance defines the general concept underlining artificial intelligence (AI).[1] The former presents notable applications in perioperative medicine across diverse situations like depth of anaesthesia monitoring, closed-loop anaesthesia delivery, risk-predictive models, pain-management through objective analgo-scoring, operating-room planning logistics and, guidance of perioperative ultrasonography. The recent Food and Drug Administration (FDA) approval[2] of the Scan Nav™ Anatomy Peripheral Nerve Block (PNB) system (Intelligent Ultrasound Group, Cardiff, United Kingdom)[3] only emerges as a novel recognition of the potential of AI in regional anaesthesia. Worthwhile to mention, Hemmerling et al.[4] described an encouraging seminal use of the robotic ultrasound-guided nerve block system or the Magellan system, almost a decade ago. Employing the same system, Morse et al.[5] went on to compare the performance parameters (learning curve and success rates) and subjective performance variability of manual versus robot-assisted ultrasonographic nerve blocks in a phantom model. The authors found that assistance of nerve blocks, enabled significant faster needle guidance (1.8 [1.6] seconds vs. 0.3 [0.3] seconds; P = 0.007), than for manual blocks. Inter-subject performance variability was also found to be considerably attenuated. Specific to the context of the recently FDA approved software medical device, ScanNav™ Anatomy PNB system uses deep-learning AI technology. During performance of a peripheral nerve block the ScanNav™ system identifies and grades a live ultrasound image using this technology. A distinctive colour overlay of the key sono-anatomical structures during a live ultrasound scan is a characteristic valuable attribute of the system.[3] This enhances standardisation and accuracy of the ultrasound image interpretation. This device colour highlights anatomy of 10 vital regions relevant to ultrasound-guided regional anaesthesia namely Interscalene, Supraclavicular, Axillary and Superior Trunk Brachial plexus of the upper limb; Erector Spinae Plane, Rectus Sheath and Supra-inguinal Fascia Iliaca sheath of truncal structures; and Femoral Nerve, Adductor canal and Popliteal nerve sheath of the lower limb. Furthermore, a 3-dimension inbuilt reference material provides a review of the relevant anatomy, probe-positioning technique; and demonstrates a virtual scan of the selected anatomical region. The system enables adjustments in the intensity of coloured highlighting according to user preference and allows for viewing the unmodified and highlighted images side-by-side for better comprehension of the sono-anatomy. The use of ScanNav™ system thereby facilitates as a labelling device alongside real-time anatomy visualisation during regional anaesthesia. The system also has inbuilt virtual scans that assist the clinician functioning as a 3D reference material of the relevant PNB anatomy scanned. Notably so, the software is compatible with the general-purpose ultrasound systems in addition to being a stand-alone device. Talking of the literature relevant to the ScanNav™ Anatomy PNB system, Bowness et al.[6] compared 240 ultrasound scans performed across 15 expert versus non-expert regional anaesthesia providers on evaluating its' role in promoting the uptake and generalisability of ultrasound-guided regional anaesthesia. The authors outlined that non-experts were more likely to submit positive feedback and less likely to submit negative reviews than the experts (P = 0.001). Positive feedbacks were obtained on the role of the device in training (37/60, 61.7%) and utility for teaching (30/60, 50.0%). Meanwhile the non-experts appreciated the anatomic structure identification and learning, as the contextual benefits, some nonexperts and experts thought the device could decrease the scanning confidence. Additionally, expert providers reported a potentially increased, yet insignificant, risk in 12/254 (4.7%) vs. 8/254 (3.1%, P = 0.362) scans for needle trauma to “safety” structures. The discussion elaborates the tremendous opportunity AI has to offer in guiding regional anaesthesia, awaiting prospective validation outside the core 10 block areas. The utility of this device can be further extended to sympathetic blocks like the stellate-ganglion, celiac-plexus and other blocks for treatment of chronic pain syndromes like complex regional pain syndrome. The times might not be distant when perioperative physicians have routine access to ultrasound machines integrated with AI-assisted colour reframing for anatomical landmark “coding” side by side with the present B-mode, M-mode and colour/pulse Doppler profiling.

NMOSDCopilot: Feasibility of Smartphone-Based Digital Biomarkers for the Self-Assessment of Vision, Motor and Cognitive Functions in Neuromyelitis Optica Spectrum Disorder (S50.002)

NMOSDCopilot: Feasibility of Smartphone-Based Digital Biomarkers for the Self-Assessment of Vision, Motor and Cognitive Functions in Neuromyelitis Optica Spectrum Disorder (S50.002)

Identifying Digital Biomarkers for the Self-Monitoring of Patients Living with Generalized Myasthenia gravis: a Proof of Concept (P7-8.007)

<h3>Objective:</h3> To identify clinically meaningful digital biomarkers (dBMKs) intended to track symptoms and signs among people living with generalized myasthenia gravis (gMG) and to prepare the development of a software medical device for the patients’ unsupervised digital self-assessment. <h3>Background:</h3> Generalized myasthenia gravis (gMG) is characterized by fluctuating manifestations and heterogeneity in fatigue and muscle group weakness. Literature pinpoints a lack of objective measurement tools for the self-assessment of gMG symptoms outside office visits, resulting in different perceptions between physicians and patients on the impact of the disease. <h3>Design/Methods:</h3> We used a Double Diamond methodology to identify dBMKs of interest for gMG patients and evaluate their relevance for clinicians through qualitative interviews. Unmet needs and dBMKs concepts were prioritized during a technical Proof-of-Concept (PoC) study. The acceptability of the digital device was assessed with prototype-supported interviews. <h3>Results:</h3> Interviews with 27 patients (France, USA) confirmed the feasibility of dBMKs to measure gMG-related neurological functions. All were interested in tracking symptoms. 9 international MG experts were interested in assessing gMG symptomology between office visits with clinically meaningful dBMKs. A PoC study on healthy subjects, performed under different conditions, confirmed the feasibility of analyzing raw data collected by the smartphone’s sensors. 5 digital active measures inspired by clinical gold standards and relying on the smartphone’s sensors were selected with their related dBMKs (ptosis, breathing, dysarthria, upper and lower extremities functions). Patient-reported outcome measures (daily activities, pain, sleep, depression, quality of life) will be incorporated as e-questionnaires. <h3>Conclusions:</h3> We perceived a need for an unsupervised patient self-assessment digital solution to monitor symptomatology outside office visits. In 2023, development of ME&amp;MG, a smartphone solution, will begin. It aims to inform and improve communication between patients and their care teams. International multicenter studies comparing ME&amp;MG to clinical gold standards including the Quantitative Myasthenia Gravis score, will be deployed. <b>Disclosure:</b> Pascal Laforet has nothing to disclose. David Orlikowski has nothing to disclose. Prof. NICOLAS has nothing to disclose. The institution of Prof. Prigent has received research support from VLM - Patients association for lysosomial diseases. The institution of Prof. Prigent has received research support from ADEP Assitance. Dr. Berling has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Adscientiam. Dr. Berling has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Roche. Ghislain N’Dah-Sekou has nothing to disclose. Dr. Gorin has received personal compensation for serving as an employee of Ad Scientiam. Dr. Moreira has received personal compensation for serving as an employee of Ad Scientiam. Mrs. Narcy has received personal compensation for serving as an employee of Ad Scientiam. Dr. Plaud has received personal compensation for serving as an employee of Ad Scientiam. Mrs. Touré Cuq has received personal compensation for serving as an employee of Ad Scientiam . Dr. Keller has received personal compensation for serving as an employee of Alexion. Dr. Keller has stock in Alexion, Roche, Novartis, Celgene, Abbvie, Merck, Ionis, Sanofie, Organon, MSD. Mr. Werneburg has received personal compensation for serving as an employee of Alexion. Dr. Aras has received personal compensation for serving as an employee of Alexion Pharmaceuticals Inc. Dr. Benatar has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Biogen. The institution of Dr. Benatar has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Arrowhead. Dr. Benatar has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Alexion. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Annexon. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving as a Consultant for UCB. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving as a Consultant for UniQure. Dr. Benatar has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Immunovant. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alector. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Sanofi. Dr. Benatar has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Benatar has received intellectual property interests from a discovery or technology relating to health care. Dr. Benatar has received intellectual property interests from a discovery or technology relating to health care.

Software medical device maintenance: DevOps based approach for problem and modification management

AbstractSoftware problem resolution and change control processes are crucial for the performance, safety, and regulatory clearance of a medical device. Software changes are frequent throughout the whole life cycle of a product; therefore, iterative analysis and risk assessment are necessary to determine the impact of changes on the whole system. IEC standard 62304 clarifies software medical device life cycle processes including problem and modification analysis and requirements. The aim of this work is to describe a cost‐effective and fully customizable solution for software medical devices problem and modification management implemented in our group. Key features of the problem and modification management related to the software life cycle have been identified and taken into account. A digital commercial platform for software development and maintenance has been identified and used to implement an architecture satisfying the standard. The architecture solution (SWMA, software maintenance architecture) has been successfully developed and a description of how it addresses IEC 62304 standard requirements both in terms of problem resolution and in terms of change control has been provided. The presented system can be useful for manufacturers/groups to establish software maintenance plans that include activities and tasks related to software problem resolution and change control processes. The approach can be adopted for analyzing and resolving problems arising before and after the release of a medical device.

BES TEST™ accuracy evaluation by means of 3D-printed phantoms

The BES TEST™ (Bone Elastic Structure Test), is a recently developed software medical device that detects pathological changes of bone trabecular architecture by measuring its elastic characteristics, known to be directly related to its resistance. The results are expressed by the Bone Structure Index (BSI) or by its T-score, that is the number of standard deviations from the healthy population average. Purpose: Evaluate the precision of BES TEST™ under reproducibility conditions, defined as repeated measurements on the same or similar objects which include different locations, operators, and measuring systems. Methods: A total of 51 replicate measurements were performed by four different operators on five different phantoms. Each phantom was 3D printed using Stereolithography (SLA) and Fused Deposition Modeling (FDM) and has a unique internal structure that mimics trabecular bone. ISO 5725 guidelines were followed for the interpretation of results. Results: The 3D-printed phantoms performed like real bones when analyzed with BES TEST™. The reproducibility 95% Confidence Interval expressed in BSI is [Formula: see text], which corresponds in T-score to [Formula: see text]. The Least Significant Change in BSI is [Formula: see text], which corresponds to [Formula: see text]. Conclusion: The reproducibility of BES TEST™ within the admissible range is not inferior to that of gold standard tests for osteoporosis. 3D printing proved a valuable tool to perform reliable replicate measurements without having patients undergo unnecessary tests.

POSA292 MSCopilot® as a Digital Tool to Collect Patients’ Insights in Health Economics Research in Multiple Sclerosis

MSCopilot® is a CE-marked software medical device used by multiple sclerosis (MS) patients for the remote monitoring of their disease in four dimensions: walking, upper-limb dexterity, cognition and low-contrast vision. This research explored the relevancy of the usage of MSCopilot® as a digital tool in PETALS study estimating the total societal impact of MS in France.

MSCopilot: New smartphone-based digital biomarkers correlate with Expanded Disability Status Scale scores in people with Multiple Sclerosis

BackgroundA previous clinical study showed the high specificity, sensitivity and reliability of MSCopilot, a software medical device designed by Ad Scientiam for the self-assessment of people with Multiple Sclerosis (PwMS), compared to the traditional Multiple Sclerosis Functional Composite (MSFC). We conducted further analyses to assess MSCopilot's performance with respect to the Expanded Disability Status Scale (EDSS). MethodsThe data of 116 PwMS were analysed. We studied the correlations between MSCopilot scores and the EDSS, and their ability to distinguish PwMS with high and low EDSS through a study of the distribution of the digital test scores as well as logistic regression models. The same analyses were performed using the MSFC tests. ResultsMSCopilot composite scores were as highly correlated to the EDSS (|r| = 0.65, p < 0.01) as their MSFC counterparts, confirming the known correlation of the MSFC with the EDSS. In a linear regression framework, the Walking digital tests have good explanatory power, especially for PwMS with EDSS > 3.5 (R²adj=0.47). The mean values of each MSCopilot subscore were significantly different between patients with an EDSS > 3.5 and others (p < 0.05), which could not be proved for the MSFC Cognition tests. MSCopilot4 was the best model to predict an EDSS score > 3.5 (AUC = 0.92). ConclusionThese analyses confirm the reliability of MSCopilot and show interesting correlations with the EDSS (similar results obtained with the MSFC). MSCopilot was able to highlight nuances in the different stages of MS the MSFC could not capture.

Interventional multicenter study to assess the feasibility of an e-health system (ZEMY) designed to manage symptoms and treatment-related toxicities in patients with breast cancer.

e14107 Background: There is increasing interest in using e-health systems for symptom monitoring and alert triggering. ZEMY, a new software medical device, was developed to improve symptom management and enhance patient and health care team interactions. Methods: This was a three-month open-label, interventional, single arm study conducted at five French sites. Adult women with breast cancer (BC) initiating oral and/or parenteral cancer treatment received a smartphone with ZEMY installed and verbal training. Patients started cancer treatment on Day 1 and were followed for three months. Patients entered data for ten prespecified symptoms. The ZEMY software made recommendations to patients on the self-management of symptoms and transmitted automatic messages to the health care team. Primary outcome was patient feasibility response at 3 months (completion of ≥3 symptom reports and a report completion rate of ≥60% per patient). Secondary objectives included ZEMY symptom management, usability and satisfaction, and device deficiencies (DDs). Results: Overall, 54 patients were enrolled (Jun 2018 to Jan 2019) and 52 (96.3%) completed the study. Thirty-one (57.4%) patients were responders; this was not significantly higher than the predefined cut-off and ZEMY feasibility was not demonstrated. Forty-seven (87.0%) patients had ≥3 completed symptom reports and 33 (66.0%) patients had a report completion rate of ≥60% (missing: n = 4). In subgroup analyses, 22/30 (73.3%) patients with locally advanced BC and 24/36 (66.7%) patients aged 40–60 years were responders. ZEMY patient recommendations and health care team automatic messages were considered relevant at least once in &gt; 74% of cases for five of the six symptoms that were reported at least once by more than 1/3 of patients (diarrhea, nausea, fatigue, cutaneous and mucosal toxicities, and anxiety/depression). Using a 0–10 visual analogue scale, mean ZEMY satisfaction score was higher for patients than investigators (6.3 ±2.9 vs 4.4 ±1.5). Overall, 95 DDs were reported in 37 (68.5%) patients. Main reasons for DDs were inappropriate recommendations (n = 51) and device malfunction (n = 36). Conclusions: The primary endpoint of the study was not reached; however, higher response rates were observed in subgroups versus the overall population, indicating that ZEMY may be useful in symptom management in these patients. Generally, patients had a favorable opinion of ZEMY. The DD rate observed indicates the need for better user support in the future. Clinical trial information: NCT03558490.

Clinical Evaluation of a Software Medical Device for the Self-Assessment of Patients Living with Multiple Sclerosis: Results of the MSCopilot Study (P3.2-012)

Clinical Evaluation of a Software Medical Device for the Self-Assessment of Patients Living with Multiple Sclerosis: Results of the MSCopilot Study (P3.2-012)

Development of ACRODAT\xae, a new software medical device to assess disease activity in patients with acromegaly

PurposeDespite availability of multimodal treatment options for acromegaly, achievement of long-term disease control is suboptimal in a significant number of patients. Furthermore, disease control as defined by biochemical normalization may not always show concordance with disease-related symptoms or patient’s perceived quality of life. We developed and validated a tool to measure disease activity in acromegaly to support decision-making in clinical practice.MethodsAn international expert panel (n = 10) convened to define the most critical indicators of disease activity. Patient scenarios were constructed based on these chosen parameters. Subsequently, a panel of 21 renowned endocrinologists at pituitary centers (Europe and Canada) categorized each scenario as stable, mild, or significant disease activity in an online validation study.ResultsFrom expert opinion, five parameters emerged as the best overall indicators to evaluate disease activity: insulin-like growth factor I (IGF-I) level, tumor status, presence of comorbidities (cardiovascular disease, diabetes, sleep apnea), symptoms, and health-related quality of life. In the validation study, IGF-I and tumor status became the predominant parameters selected for classification of patients with moderate or severe disease activity. If IGF-I level was ≤1.2x upper limit of normal and tumor size not significantly increased, the remaining three parameters contributed to the decision in a compensatory manner.ConclusionThe validation study underlined IGF-I and tumor status for routine clinical decision-making, whereas patient-oriented outcome measures received less medical attention. An Acromegaly Disease Activity Tool (ACRODAT) is in development that might assist clinicians towards a more holistic approach to patient management in acromegaly.

PRM12 - Individualised Growth Response Optimisation (IGRO): A Multi-Language Software Medical Device to Predict Growth Response in Children Treated With Growth Hormone (GH)

PRM12 - Individualised Growth Response Optimisation (IGRO): A Multi-Language Software Medical Device to Predict Growth Response in Children Treated With Growth Hormone (GH)