Objectives: INOCA (Ischemia in non- obstructive coronary arteries) has been recognized as a global health problem and poses a diagnostic challenge to establish the diagnosis which involves first ruling out obstructive coronary artery disease by the use of CT coronary angiography (CTCA) or an invasive angiogram. Second step involves the use of intracoronary pressure and Doppler monitoring which is not only costly, time consuming and lacks easy availability. CTFFR has emerged as frontline tool in the non invasive evaluation of patients with stable chest pain. This retrospective study was designed to evaluate the spectrum of findings of ischemia on CTCA and CT FFR in patients with stable chest pain to determine if this protocol can be used to identify patients with INOCA before they are subjected to invasive protocol. Methods: This was a retrospective study of 500 consecutive patients of stable chest pain with more than >1mm ST depression on resting EKG and or positive stress test who underwent CTCA along with CTFFR evaluation using a prescribed CT angiographic protocol. Post processing was done to reconstruct multiplanar angiographic views followed by CT FFR evaluation. All patients with no obstruction or stenosis less than 50% and with CT FFR of <0.80 were labeled as having INOCA. Subcategorisation of all INOCA patients was done based on Vessel tapering index (VTI), Plaque volume Index (PVI) into four subtypes- TypeI (vasospastic), Type II (site specific atherosclerotic), Type III (distal macrovascular dysfunction- DMD), Type IV (mixed). Results: Study showed 122 (34%) patients of stable chest pain had INOCA. Types I, III formed the largest group of patients 38% and 31% followed by the other two subtypes and showed significant differences in the VTI and PVI along with reduced FFR of <.80 in all these patients. Conclusion: Use of CTCA and CTFFR can be used as a first line tool to not only rule out obstructive coronary disease with ischemia but also to non invasively detect INOCA in patients with stable chest pain before subjecting these patients for further invasive protocols and can influence accurate management of such patients.
Background Evaluation of suspected coronavirus disease-2019 (COVID-19) patient is a diagnostic dilemma as it commonly presents like influenza in early stages. Studies and guidelines have emerged both for and against the use of imaging as a frontline tool to investigate such patients. Reverse transcriptase-polymerase chain reaction (RT-PCR) is suggested as the backbone of diagnosis. We designed and tested a diagnostic algorithm using artificial intelligence (AI) to determine the role of imaging in the evaluation of patients with acute flu-like presentation. Materials and Methods Overall, 3,235 consecutive patients with flu-like presentation were evaluated over a period of 240 days. All patients underwent plain radiographs of chest with computer-aided detection for COVID-19 (CAD4COVID) AI analysis. Based on the threshold scores, they were divided into two groups: group A (score < 50) and group B (score > 50). Group A patients were discharged and put on routine symptomatic treatment and follow-up with RT-PCR, while group B patients underwent high-resolution computed tomography (HRCT) followed by COVID-19 AI analysis and RT-PCR test. These were then triaged into COVID-19 and non-COVID-19 subgroups based on COVID-19 similarity scores by AI, and lung severity scores were also determined. Results Group A had 2,209 (68.3%) patients with CAD4COVID score of <50 while 1,026 (31.7%) patients comprised group B. Also, 825 (25.5%) patients were COVID-19 positive with COVID-19 similarity threshold of >0.85 on AI. RT-PCR was positive in 415 and false-negative in 115 patients while 12 patients died before the test could be done. The sensitivity and specificity of CAD4COVID AI analysis on plain radiographs for detection of any lung abnormality combined with HRCT AI analysis was 97.9% and 99% using the above algorithm. Conclusion Combined use of chest radiographs and plain HRCT with AI-based analysis is useful and an accurate frontline tool to triage patients with acute flu-like symptoms in non-COVID-19 health care facilities.
Background: Asian Indians have the highest prevalence (11%) of coronary artery risk worldwide compared to all other races. So far no quantifiable risk factor has been shown to explain such a high prevalence. Fat attenuation index (FAI) using CT coronary angiography (CTCA) has been recently used to demonstrate coronary perivascular inflammation and to confirm that atherosclerosis is an inflammatory process. Hence this study was conducted to determine FAI using CTCA in 200 adult Indians as a retrospective study to determine if it can be the answer to establish the cause for high prevalence of CAD in Indians and whether there are differences in FAI in normal adults and those with significant CAD and to determine if it could be used as imaging biomarker for diagnosis and follow up of such patients. Material and Methods: Retrospective study of 200 patients who underwent CTCA was done. Patients were divided into two groups based on no coronary disease (NOCAD) and those with significant coronary artery disease (CAD). Patient demographics were recorded for both groups. FAI estimation was done along with Plaque volume index (PVI), pericardial volume estimation and the differences between the two groups were statistically analysed. Results: Mean patient age in both groups was 52 years with male predominance (75-80%). Mean FAI,s for left anterior descending and right coronary arteries was 45.4 and -44.7 HU and of -38.0 and -39.2 HU for NOCAD and CAD groups respectively (p<0.001). Sensitivity and specificity of FAI to differentiate NOCAD from CAD at a cut off value >-38HU was 73% and 80% respectively with LR of 3.6. Conclusion: Normal adult Indians with NOCAD showed a high FAI compared to all other races which could be reason for highest prevalence of CAD amongst Indians. FAI can be used as imaging biomarker to differentiate CAD from NOCAD with sensitivity and specificity of 73% and 80% respectively.
Objective. This study was done to evaluate the role of real-time Elastography (ES) in the diagnosis and staging the severity of acute appendicitis. Methods. Forty patients with acute pain in the right iliac fossa were evaluated using ES and sonography. All patients with a diagnosis of acute appendicitis on ES were also staged for the severity of appendicular inflammation and later underwent surgery, and the findings on imaging were confirmed and results compared. The sensitivity and specificity for ES and sonography were then calculated. Results. Elastography had sensitivity and specificity of 100% each, whereas sonography had sensitivity of 88% and specificity of 100%. Elastography also depicted the severity of inflammation, with 12 patients having mild, 8 having moderate, and 5 having severe appendicitis. Conclusions. Combining ES with sonography improves the sensitivity in detection of acute appendicitis and can also be used to triage the severity of inflammation in such patients.
World has just passed through the global pandemic of COVID-19 disease with recent reports of it resurfacing in China.Although being a disease predominantly affecting lungs the involvements of other organs like heart, brain and gut have also been seen in the acute phase.PASC (post acute SARS COVID-19) is a distinct phase of the disease seen amongst survivors from both mild and severe disease where the patients continue to suffer from symptoms of palpitations, dysnoea on exertion, chest pain and fatigue.Few studies have been done in such patients to assess ongoing cardiac involvement.Most of these patients show normal left and right ventricle Ejection fraction, normal troponin levels with non specific EKG findings of sinus tachycardia.Some of these patients are made to undergo cardiac MR to rule out COVID-19 myocarditis.Here also most of the imaging specialists and the cardiologists are focused on the left ventricle only and look for the Lake Loius criteria to establish or rule out diagnosis.
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