A deep learning system for quantitative assessment of microvascular abnormalities in nailfold capillary images.

OBJECTIVES: Nailfold capillaroscopy is key to timely diagnosis of SSc, but is often not used in rheumatology clinics because the images are difficult to interpret. We aimed to develop and validate a fully automated image analysis system to fill this gap. METHODS: We mimicked the image interpretation strategies of SSc experts, using deep learning networks to detect each capillary in the distal row of vessels and make morphological measurements. We combined measurements from multiple fingers to give a subject-level probability of SSc.We trained the system using high-resolution images from 111 subjects (group A) and tested on images from subjects not in the training set: 132 imaged at high-resolution (group B); 66 imaged with a low-cost digital microscope (group C). Roughly half of each group had confirmed SSc, and half were healthy controls or had primary RP ('normal'). We also estimated the performance of SSc experts. RESULTS: We compared automated SSc probabilities with the known clinical status of patients (SSc versus 'normal'), generating receiver operating characteristic curves (ROCs). For group B, the area under the ROC (AUC) was 97% (94-99%) [median (90% CI)], with equal sensitivity/specificity 91% (86-95%). For group C, the AUC was 95% (88-99%), with equal sensitivity/specificity 89% (82-95%). SSc expert consensus achieved sensitivity 82% and specificity 73%. CONCLUSION: Fully automated analysis using deep learning can achieve diagnostic performance at least as good as SSc experts, and is sufficiently robust to work with low-cost digital microscope images.

Nailfold capillaroscopy: a survey of current UK practice and 'next steps' to increase uptake among rheumatologists.

OBJECTIVES: To identify barriers to the use of nailfold capillaroscopy as a diagnostic tool for patients presenting with Raynaud's phenomenon in UK rheumatology centres and to obtain rheumatologists' views on a proposed internet-based standardized system for clinical reporting of nailfold capillaroscopy images. METHODS: An online survey was developed using expert opinion from clinicians, scientists and health service researchers. The survey was piloted and sent to UK-based rheumatologists using established electronic mailing lists between October 2020 and March 2021. Survey data were analysed using descriptive statistics. RESULTS: A total of 104 rheumatologists representing rheumatology centres across the UK responded to the survey. Wide variations in terms of workloads and practices were described. Thirty-four (33%) respondents reported using nailfold capillaroscopy only at their own centre, 33 (32%) referred to other centres, 9 (9%) did both and 28 (27%) did not use capillaroscopy at all. Of the 43 respondents using capillaroscopy on site, 25 (58%) used either a dermatoscope or universal serial bus microscope and 9 (21%) used videocapillaroscopy. Among the 61 respondents not undertaking capillaroscopy on site, barriers included lack of equipment (85%), lack of experience in acquiring images (69%) and lack of expertise in interpreting images (67%). Sixty-six respondents (63%) expressed interest in an internet-based, standardized automated system for reporting images. CONCLUSION: Most UK rheumatologists currently do not perform nailfold capillaroscopy on site. An internet-based nailfold capillaroscopy system for use with low-cost microscopes as well as with videocapillaroscopy could help increase uptake of capillaroscopy and thereby facilitate early diagnosis of SSc across the UK.