Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard.Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed.Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P < 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P < 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P < 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P < 0.05).Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.

A robust benchmark for evaluating and improving mosaic variant calling strategies

The rapid advances in sequencing and analysis technologies have enabled the accurate detection of diverse forms of genomic variants, including germline, somatic, and mosaic mutations. However, unlike for the former two mutations, the best practices for mosaic variant calling still remain chaotic due to the technical and conceptual difficulties faced in evaluation. Here, we present our benchmark of nine feasible strategies for mosaic variant detection based on a systematically designed reference standard that mimics mosaic samples, with 390,153 control positive and 35,208,888 negative single-nucleotide variants and insertion–deletion mutations. We identified the condition-dependent strengths and weaknesses of the current strategies, instead of a single winner, regarding variant allele frequencies, variant sharing, and the usage of control samples. Moreover, feature-level investigation directs the way for immediate to prolonged improvements in mosaic variant calling. Our results will guide researchers in selecting suitable calling algorithms and suggest future strategies for developers.

Implementation and Evaluation of a Mobile Retinal Image Acquisition System for Screening Diabetic Retinopathy: Study Protocol

Screening diabetic retinopathy, a major cause of blindness, is time-consuming for ophthalmologists and has some constrains in achieving full coverage and attendance. The handheld fundus camera EyeFundusScope was recently developed to expand the scale of screening, drawing on images acquired in primary care and telescreening made by ophthalmologists or a computer-aided diagnosis (CADx) system. This study aims to assess the diagnostic accuracy of the interpretation of images captured using EyeFundusScope and perform its technical evaluation, including image quality, functionality, usability, and acceptance in a real-world clinical setting. Physicians and nurses without training in ophthalmology will use EyeFundusScope to take pictures of the retinas of patients with diabetes and the images will be classified for the presence or absence of diabetic retinopathy and image quality by a panel of ophthalmologists. A subgroup of patients will also be examined with the reference standard tabletop fundus camera. Screening results provided by the CADx system on images taken with EyeFundusScope will be compared against the ophthalmologists’ analysis of images taken with the tabletop fundus camera. Diagnostic accuracy measures with 95% confidence intervals (CIs) will be calculated for positive and negative test results. Proportion of each category of image quality will be presented. Usability and acceptance results will be presented qualitatively.

Static CT myocardial perfusion imaging: image quality, artifacts including distribution and diagnostic performance compared to 82Rb PET

Background Rubidium-82 positron emission tomography (82Rb PET) MPI is considered a noninvasive reference standard for the assessment of myocardial perfusion in coronary artery disease (CAD) patients. Our main goal was to compare the diagnostic performance of static rest/ vasodilator stress CT myocardial perfusion imaging (CT-MPI) to stress/ rest 82Rb PET-MPI for the identification of myocardial ischemia. Methods Forty-four patients with suspected or diagnosed CAD underwent both static CT-MPI and 82Rb PET-MPI at rest and during pharmacological stress. The extent and severity of perfusion defects on PET-MPI were assessed to obtain summed stress score, summed rest score, and summed difference score. The extent and severity of perfusion defects on CT-MPI was visually assessed using the same grading scale. CT-MPI was compared with PET-MPI as the gold standard on a per-territory and a per-patient basis. Results On a per-patient basis, there was moderate agreement between CT-MPI and PET-MPI with a weighted 0.49 for detection of stress induced perfusion abnormalities. Using PET-MPI as a reference, static CT-MPI had 89% sensitivity (SS), 58% specificity (SP), 71% accuracy (AC), 88% negative predictive value (NPV), and 59% positive predictive value (PPV) to diagnose stress-rest perfusion deficits on a per-patient basis. On a per-territory analysis, CT-MPI had 73% SS, 65% SP, 67% AC, 90.8% NPV, and 34% PPV to diagnose perfusion deficits. Conclusions CT-MPI has high sensitivity and good overall accuracy for the diagnosis of functionally significant CAD using 82Rb PET-MPI as the reference standard. CT-MPI may play an important role in assessing the functional significance of CAD especially in combination with CCTA.

Evaluation of two AI software for the diagnosis of TB infection : A study protocol (Preprint)

BACKGROUND Tuberculosis (TB) profile in Malaysia showed an average annual growth rate of 2.23%, with an estimated 92 cases per 100,000 people reported in 2018. CXR remains the best conventional method for the early detection of pulmonary TB infection. The intervention of AI in TB diagnosis could efficiently aid human interpreters and reduce health professionals' work burden. To date, no evaluation of AI studies has been carried out in Malaysia. OBJECTIVE This study aims to determine the diagnostic accuracy and evaluate the performance of Qure.ai and Putra Analytica AI software. METHODS We will conduct a retrospective case-control study in Respiratory Medicine Institute (IPR), Kuala Lumpur Health Clinic and Bandar Botanik Klang Health Clinic. Patients' medical reports on TB investigation will be retrieved by accessing electronic and hardcopy medical records and collecting demographic data. Prior to conducting the study, patients' PTB status will be obtained by identifying MTB culture (reference standard) results in order to create a case and a control group. A total of 2000 CXR images will be retrieved, of which 1000 images will be the case (abnormality). Normal and abnormal CXR will be categorized into film and digital CXR, which will be screened onto the said AI software (index tests). RESULTS Results obtained from the AI software will be compared with the reference standard, and significant statistical analysis will be computed CONCLUSIONS We hope that the findings of this evaluation study will provide sufficient information for stakeholders and to implement AI technology in the medical imaging field for better management of TB in hospital and clinic settings.

ICD-10 Diagnostic Coding for Identifying Hospitalizations Related to a Diabetic Foot Ulcer

Purpose: To estimate the positive predictive value (PPV) of Canadian ICD-10 diagnostic coding for the identification of hospitalization related to a diabetic foot ulcer (DFU). Methods: Hospitalizations related to a neuropathic and/or ischemic DFU were identified from the Discharge Abstract Database (DAD) records of a single Canadian tertiary care hospital between April 1, 2002 and March 31, 2019. The first coding approach required a most responsible diagnosis (MRDx) code for diabetes-specific foot ulceration or gangrene (DSFUG group). Three alternative coding approaches were also considered: MRDx code for lower-limb osteomyelitis (osteomyelitis group); lower-limb ulceration (LLU group); or lower-limb atherosclerotic gangrene (atherosclerosis group)—each in conjunction with a non-MRDx DSFUG code on the same DAD record. From all eligible DAD records, random samples were drawn for each coding group. DAD records were independently compared by a masked reviewer who manually abstracted data from the entire hospital record (reference standard). The PPV and 95% CI were generated. Results: Out of 1,460 hospitalizations, a total of 300, 50, 33 and seven records were included from the DSFUG, osteomyelitis, LLU and atherosclerosis samples, respectively. Compared to the reference standard, the PPV for all 390 records was 88.5% (95% CI 84.9 to 91.5). The DSFUG group had the highest PPV (90.0%, 95% CI 86.0 to 93.2), followed by the atherosclerosis (85.7%, 95% CI 42.1 to 99.6), LLU (84.9%, 95% CI 68.1 to 94.9) and osteomyelitis (82.0%, 95% CI 68.6 to 91.4) groups. Conclusion: Based on data from a Canadian tertiary care hospital, the specified coding algorithms can be used to identify and study the management and outcomes of people hospitalized with a DFU in Ontario.