Apical fibrobullous lung disease in spondyloarthritis patients with biologic DMARDs indication.

OBJECTIVE: The rate of pleuroparenchymal involvement in patients with SpA varies widely, from 0% to 85%. The most common form is apical fibrobullous disease (AFLD). The aim of this study was to determine the incidence of AFLD and associated factors in SpA patients under and/or planned to start biologic DMARDs (bDMARDs) therapy. METHODS: The records of 3021 SPA patients registered with HUR-BIO who had indication of bDMARDs between 2010 and 2021 were scanned. The study included 2489 patients with at least one chest radiograph (X-ray). Patient demographics, comorbidities, laboratory data, bDMARDs used, baseline DASs, and purified protein derivative and/or QuantiFERON test results before initiation of bDMARDs were recorded. RESULTS: Of the 2489 patients, 36 (1.4%) were found to have AFLD by X-ray and/or CT. The mean disease duration was 11.7 (7.1) years. Patients with AFLD were more likely to be male [28 (77.8%) vs 1321 (53.9%), P = 0.004], older [56.3 (10.5) years vs 44.8 (11.4) years, P < 0.001], heavy smokers [27 (79.4%) vs 1468 (60.9%), P = 0.028] and have had longer disease duration [17. 7 (9.7) years vs 11.6 (7) years, P = 0.001]. QuantiFERON positivity was higher in the AFLD group [9 (36%) vs 309 (16.1%), P = 0.013]. While treatment with adalimumab was less preferred in those with AFLD, treatment with etanercept was more frequently preferred. CONCLUSION: As the radiological findings of AFLD can be confused with those of tuberculosis, special attention should be paid to differentiating between tuberculosis and the disease in males and in patients who have had long disease duration.

A screening study for COVID-19-associated pulmonary aspergillosis in critically ill patients during the third wave of the pandemic.

BACKGROUND: COVID-19-associated pulmonary aspergillosis (CAPA) has been reported as an important cause of mortality in critically ill patients with an incidence rate ranging from 5% to 35% during the first and second pandemic waves. OBJECTIVES: We aimed to evaluate the incidence, risk factors for CAPA by a screening protocol and outcome in the critically ill patients during the third wave of the pandemic. PATIENTS/METHODS: This prospective cohort study was conducted in two intensive care units (ICU) designated for patients with COVID-19 in a tertiary care university hospital between 18 November 2020 and 24 April 2021. SARS-CoV-2 PCR-positive adult patients admitted to the ICU with respiratory failure were included in the study. Serum and respiratory samples were collected periodically from ICU admission up to CAPA diagnosis, patient discharge or death. ECMM/ISHAM consensus criteria were used to diagnose and classify CAPA cases. RESULTS: A total of 302 patients were admitted to the two ICUs during the study period, and 213 were included in the study. CAPA was diagnosed in 43 (20.1%) patients (12.2% probable, 7.9% possible). In regression analysis, male sex, higher SOFA scores at ICU admission, invasive mechanical ventilation and longer ICU stay were significantly associated with CAPA development. Overall ICU mortality rate was higher significantly in CAPA group compared to those with no CAPA (67.4% vs 29.4%, p < .001). CONCLUSIONS: One fifth of critically ill patients in COVID-19 ICUs developed CAPA, and this was associated with a high mortality.

A COVID-19 first evaluation clinic at a university hospital in Turkey.

BACKGROUND: We aimed to analyze the usefulness of such a reserved area for the admission of the patients' symptoms suggesting COVID-19 and compare the demographic and clinical characteristics of the patients with COVID-19 and without COVID-19 who were admitted to C1 during the first month of the COVID-19 outbreak in our hospital. METHODS: A new area was set up in Hacettepe University Adult Hospital to limit the contact of COVID-19 suspicious patients with other patients, which was named as COVID-19 First Evaluation Outpatient Clinic (C1). C1 had eight isolation rooms and two sampling rooms for SARS-CoV-2 polymerase-chain-reaction (PCR). All rooms were negative-pressurized. Patients who had symptoms that were compatible with COVID-19 were referred to C1 from pretriage areas. All staff received training for the appropriate use of personal protective equipment and were visited daily by the Infection Prevention and Control team. RESULTS: One hundred and ninety-eight (29.4%) of 673 patients who were admitted to C1were diagnosed with COVID-19 between March 20, 2020, and April 19, 2020. SARS-CoV-2 PCR was positive in 142 out of 673 patients. Chest computerized tomography (CT) was performed in 421 patients and COVID-19 was diagnosed in 56 of them based on CT findings despite negative PCR. Four hundred and ninety-three patients were tested for other viral and bacterial infections with multiplex real-time reverse-transcriptase PCR (RTPCR). Blood tests that included complete blood count, renal and liver functions, d-dimer levels, ferritin, C- reactive protein, and procalcitonin were performed in 593 patients. Only one out of 44 healthcare workers who worked at C1 was infected by SARS-CoV-2. DISCUSSION: Early diagnosis of infected patients and ensuring adequate isolation are very important to control the spread of COVID-19. The purpose of setting up the COVID-19 first evaluation outpatient clinic was to prevent the overcrowding of ER due to mild or moderate infections, ensure appropriate distancing and isolation, and enable emergency services to serve for real emergencies. A wellplanned outpatient care area and teamwork including internal medicine, microbiology, and radiology specialists under the supervision of infectious diseases specialists allowed adequate management of the mild-to-moderate patients with suspicion of COVID-19.

Lung and kidney perfusion deficits diagnosed by dual-energy computed tomography in patients with COVID-19-related systemic microangiopathy.

OBJECTIVES: There is increasing evidence that thrombotic events occur in patients with coronavirus disease (COVID-19). We evaluated lung and kidney perfusion abnormalities in patients with COVID-19 by dual-energy computed tomography (DECT) and investigated the role of perfusion abnormalities on disease severity as a sign of microvascular obstruction. METHODS: Thirty-one patients with COVID-19 who underwent pulmonary DECT angiography and were suspected of having pulmonary thromboembolism were included. Pulmonary and kidney images were reviewed. Patient characteristics and laboratory findings were compared between those with and without lung perfusion deficits (PDs). RESULTS: DECT images showed PDs in eight patients (25.8%), which were not overlapping with areas of ground-glass opacity or consolidation. Among these patients, two had pulmonary thromboembolism confirmed by CT angiography. Patients with PDs had a longer hospital stay (p = 0.14), higher intensive care unit admission rates (p = 0.02), and more severe disease (p = 0.01). In the PD group, serum ferritin, aspartate aminotransferase, fibrinogen, D-dimer, C-reactive protein, and troponin levels were significantly higher, whereas albumin level was lower (p < 0.05). D-dimer levels ≥ 0.485 µg/L predicted PD with 100% specificity and 87% sensitivity. Renal iodine maps showed heterogeneous enhancement consistent with perfusion abnormalities in 13 patients (50%) with lower sodium levels (p = 0.03). CONCLUSIONS: We found that a large proportion of patients with mild-to-moderate COVID-19 had PDs in their lungs and kidneys, which may be suggestive of the presence of systemic microangiopathy with micro-thrombosis. These findings help in understanding the physiology of hypoxemia and may have implications in the management of patients with COVID-19, such as early indications of thromboprophylaxis or anticoagulants and optimizing oxygenation strategies. KEY POINTS: • Pulmonary perfusion abnormalities in COVID-19 patients, associated with disease severity, can be detected by pulmonary DECT. • A cutoff value of 0.485 µg/L for D-dimer plasma levels predicted lung perfusion deficits with 100% specificity and 87% sensitivity (AUROC, 0.957). • Perfusion abnormalities in the kidney are suggestive of a subclinical systemic microvascular obstruction in these patients.

AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.

OBJECTIVE: To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence (AI)-based software in different clinical severity groups during the disease course. METHODS: From March 11 to April 15, 2020, 51 patients (age, 18-84 years; 28 men) diagnosed and hospitalized with COVID-19 pneumonia with a total of 116 CT scans were enrolled in the study. Patients were divided into mild (n = 12), moderate (n = 31), and severe (n = 8) groups based on clinical severity. An AI-based quantitative CT analysis, including lung volume, opacity score, opacity volume, percentage of opacity, and mean lung density, was performed in initial and follow-up CTs obtained at different time points. Receiver operating characteristic analysis was performed to find the diagnostic ability of quantitative CT parameters for discriminating severe from nonsevere pneumonia. RESULTS: In baseline assessment, the severe group had significantly higher opacity score, opacity volume, higher percentage of opacity, and higher mean lung density than the moderate group (all P ≤ 0.001). Through consecutive time points, the severe group had a significant decrease in lung volume (P = 0.006), a significant increase in total opacity score (P = 0.003), and percentage of opacity (P = 0.007). A significant increase in total opacity score was also observed for the mild group (P = 0.011). Residual opacities were observed in all groups. The involvement of more than 4 lobes (sensitivity, 100%; specificity, 65.26%), total opacity score greater than 4 (sensitivity, 100%; specificity, 64.21), total opacity volume greater than 337.4 mL (sensitivity, 80.95%; specificity, 84.21%), percentage of opacity greater than 11% (sensitivity, 80.95%; specificity, 88.42%), total high opacity volume greater than 10.5 mL (sensitivity, 95.24%; specificity, 66.32%), percentage of high opacity greater than 0.8% (sensitivity, 85.71%; specificity, 80.00%) and mean lung density HU greater than -705 HU (sensitivity, 57.14%; specificity, 90.53%) were related to severe pneumonia. CONCLUSIONS: An AI-based quantitative CT analysis is an objective tool in demonstrating disease severity and can also assist the clinician in follow-up by providing information about the disease course and prognosis according to different clinical severity groups.

Comparison of clinical and magnetic resonance imaging findings of triple-negative breast cancer with non-triple-negative tumours.

PURPOSE: Triple-negative breast cancer (TNBC) has some distinctive features. The aim of the study was to compare clinical and breast magnetic resonance imaging (MRI) findings of TNBC with non-triple-negative breast cancer (nTNBC) in molecular subtypes such as ADC (apparent diffusion coefficient) values, T2-weighted (T2W) image intensity, shape, margin, lymph node involvement, grade, multifocality, multicentricity, bilaterality, and enhancement pattern differences between tumour subtypes. MATERIAL AND METHODS: A total of 141 patients who underwent breast biopsy at our institution between January 2010 and June 2018 were included in this study. Patients were divided into molecular subtypes according to hormone receptor status, and Ki-67 index. Tumour grade, enhancement patterns, age, lymph node involvement, ADC values, breast imaging reporting and data system (BI-RADS) category, bilaterality, multifocality, multicentricity, margin, shape, and T2W image intensity were evaluated for these subtypes. RESULTS: ADC values were higher in triple-negative tumours than in luminal A and luminal B tumours (p = 0.010 and p = 0.002, respectively). Circumscribed margin, type 2 enhancement curve, and rim enhancement were significantly higher in triple-negative tumours (p < 0.001). No significant difference was found between the groups in terms of other MRI findings including bilaterality, multifocality, multicentricity, shape, and T2W image intensity (p > 0.05). CONCLUSIONS: ADC values, circumscribed margin, and rim enhancement can provide important information about the tumour's biological behaviour and the course of the disease.

Do Histopathological Features and Microcalcification Affect the Elasticity of Breast Cancer?

OBJECTIVES: The aim of this study was to evaluate any association between histological grade, molecular subtypes of breast cancer, and strain elastography, and to investigate whether microcalcification affects the stiffness of tumor in breast cancers with the same histological grade. METHODS: Between April 2015 and March 2016, 94 lesions of 94 patients with the diagnosis of invasive ductal carcinoma were included in the study. Strain elastography was performed on all patients before biopsy. Histological grades (Grades 1, 2, and 3), molecular subtypes (luminal A, luminal B, Her-2, and basal-like), and strain ratio (SR) were compared. In the same histological grades, patients were divided into two groups according to the presence of microcalcifications, and the groups were compared with each other. RESULTS: Compared with Grades 1 (20.5) and 2 (23.7), Grade 3 (11.7) showed lower SR values (Grade 3-2, P = .01; Grade 3-1, P = .2). The groups with microcalcification had slightly higher SR in all histological grades, but not of statistical significance. In molecular subtypes, luminal A and B demonstrated higher SR, whereas HER2 and basal-like had lower SR (P > .05 for all group comparisons). CONCLUSIONS: Grade 3 invasive ductal carcinomas are different from other grades with lower SR values. The presence of microcalcifications and molecular subtypes do not affect elasticity like a high histological grade does.

Assessment of the effect of cigarette smoking on regional brain volumes and lesion load in patients with clinically isolated syndrome.

PURPOSE: Smoking has been associated with an increased risk of developing multiple sclerosis, disease progression and clinical disability. We detected the effects of smoking on regional brain volumes and lesion load in patients with clinically isolated syndrome using quantitative magnetic resonance imaging. MATERIALS AND METHODS: Smoker patients (n = 16), smoker healthy controls (n = 13), non-smoker patients (n = 17) and non-smoker healthy controls (n = 14) underwent magnetic resonance imaging and neocortical volumes were measured. Lesion load was calculated in terms of number and volume of white matter hyperintensities. RESULTS: Smoking was associated with increased gray matter volumes in several regions of the brain. A tendency towards greater lesion load in smoker patients was found. Smoking duration was significantly negatively correlated with intracranial volume and left hemisphere cortical gray matter volume. There was no relationship between regional brain volumes and clinical disability scores, lesion load duration of the disease and degree of smoking exposure. CONCLUSIONS: Clinically isolated syndrome related regional brain atrophy might vary in extent and severity with smoking. Despite increased lesion load, less cortical and deep gray matter damage with a possible neuroprotective effect occurs in smoking.

Does coronary calcium scoring with a SCORE better predict significant coronary artery stenosis than without? Correlation with computed tomography coronary angiography.

OBJECTIVE: To determine effectiveness of coronary artery calcium score (CACS) alone and combined with Systematic Coronary Risk Evaluation (SCORE) in adult patients for significant coronary artery stenosis by using computed tomography coronary angiography (CTCA) as reference standard. METHODS: Two thousand twenty-one patients with suspected coronary artery disease (CAD) underwent CACS test and CTCA. Patients were examined with dual-source CT and were grouped according to their age, gender, CACS, and estimated SCORE risk. Coronary plaque existence and degree of stenosis were assessed with CTCA. Sensitivity, specificity, and ROC curves were analyzed. RESULTS: CACS was the single independent variable in estimating relative risk of critical stenosis and had superior outcome when compared with SCORE risk in logistic regression and ROC curve. Area under the ROC curve was greatest in the interval between 50-59 years. When SCORE was combined with CACS in patients with zero CACS, percentage of significant stenosis increased from 1.4% to 7.0% in patients with high or very high SCORE risk, and decreased to 0.9 % in patients with low or moderate SCORE risk. CONCLUSIONS: CACS combination with SCORE risk predicts coronary artery stenosis. When CACS is zero, CTCA can be performed in patients with high or very high SCORE risk.

Spontaneous Isolated Celiac Artery and Superior Mesenteric Artery Dissections: A Rare Case.

BACKGROUND: Arterial dissection is defined as the cleavage of the arterial wall by an intramural hematoma. Reports of dissection of the celiac and/or superior mesenteric artery are rare; as far as we know, only 24 cases of spontaneous isolated celiac trunk dissection, and 71 cases of spontaneous isolated superior mesenteric artery dissection have been reported. CASE REPORT: The case presents a 48-year-old male with a sudden-onset epigastric pain. A Computed Tomography Angiography of the thoracoabdominal aorta was applied and dissections of both the celiac artery and SMA were determined. A conservative therapeutic approach was preferred and the patient was discharged with anticoagulant and antihypertensive therapy. CONCLUSIONS: Although rare, spontaneous isolated celiac artery and superior mesenteric artery dissections must be kept in mind in the differential diagnosis of the epigastric pain in the emergency room. Contrast-enhanced Computed Tomography Angiography examination is the method of choice in the diagnosis.

Pyelolymphatic backflow demonstrated by an abdominal CT: A case report.

BACKGROUND: Pyelolymphatic backflow phenomenon, which is a subtype of pyelorenal backflow, is a rare condition that occurs during the acute phase of urinary obstruction. Pyelorenal backflow has already been described in humans with retrograde pyelography. Our report presents a rare case of pyelolyphatic backflow demonstrated by a computed tomography. CASE REPORT: A 67-year-old man with a history of bladder carcinoma was admitted to the emergency department due to right-sided flank pain and hematuria. Hematuria resolved after insertion of a 3-way urinary catheter, but flank pain persisted. As a result, an abdominopelvic CT was performed. CT revealed numerous tiny, serpiginous tubular structures connected with each other and filled with urine. They began intrarenally and extended caudally surrounding the ureter in the retroperitoneum. Subsequently, the patient underwent an ultrasound-guided nephrostomy to decompress the collecting system of the right kidney. Antegrade pyelography revealed minimal hydroneprosis. However, no leakage from the ureter to the retroperitoneum was observed, proving that the changes demonstrated by a CT were due to pyelolymphatic reflux caused by increased pressure in the collecting tubules filling the lymphatics with opaque urine. CONCLUSIONS: This report presents a very rare case of pyelolymphatic reflux demonstrated by a CT. We present this case report as a reminder that although rare, pyelolymphatic reflux can occur as a result of obstruction without manifestations of hydronephrosis and it can be confused with leakage from the ureter.

Immunoglobulin G4-related thoracic disease: clinical and radiological findings of a Turkish cohort.

BACKGROUND AND AIM: Thoracic involvement of Immunoglobulin G4-related disease (IgG4-RD) is relatively rare and may be disregarded at the time of initial diagnosis due to its asymptomatic nature. This study aimed to ascertain the prevalence and patterns of thoracic involvement in a retrospective cohort of Turkish patients with IgG4-RD. METHODS: A total of 90 patients (47 males and 43 females, with a mean age of 57.7±15.5 years) diagnosed with IgG4-RD were reviewed retrospectively. All computed tomography (CT) scans were re-evaluated by two thoracic radiologists and IgG4-related thoracic disease was assessed on four compartments: The mediastinum, pulmonary parenchyma, airways, and pleura. IgG4-related thoracic disease was categorized as: definite, highly probable, probable or possible. RESULTS: There were 64 patients who had undergone at least one thorax CT examination, and 18 (28%) were diagnosed with IgG4-related thoracic disease. The rate of IgG4-related thoracic disease increased by 20% and reached a ratio of 48.4% (n=31) after a thorough reevaluation of registry data specifically to thoracic findings. The mediastinum was the most frequently involved compartment, affecting 16 (51.6%) patients, followed by pulmonary parenchyma in 14 (45.2%) patients, and airways and pleura in 10 (32.3%) patients each. Other organ involvements were more prevalent and IgG4 levels were higher in patients with thoracic involvement. Eosinophils were significantly elevated in patients with thoracic involvement (p=0.023). CONCLUSIONS: IgG4-related thoracic disease is heterogeneous and likely to be more prevalent than currently recognized. The mediastinum is the most frequently involved compartment. It is important to assess IgG4-related thoracic disease at the time of initial diagnosis. Elevated levels of serum IgG4 and eosinophils, as well as a greater number of organ involvements may serve as indicators of thoracic involvement.

Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study.

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients: Intensive care unit admission. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (cor(Xu1, Zv1) = 0.596, p value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

Costovertebral and costotransverse joint involvement in spondyloarthritis.

OBJECTIVES: Costovertebral (CV), costotransverse (CTr), sternoclavicular (SC), and manubriosternal (MS) joints are impacted in spondyloarthritis (SpA) patients; however, clinical aspects of these involvements require additional evaluation. METHODS: A total of 281 SpA patients who had undergone chest computed tomography (CT) for any reason between 2010 and 2020 were included in the study. SpA patients were divided into three groups, ankylosing spondylitis (AS), non-radiographic axial SpA, and psoriatic arthritis. Thirty age- and sex-matched rheumatoid arthritis (RA) patients and 30 non-rheumatic disease individuals were selected for comparison. An experienced radiologist reviewed 24 CV, 20 CTr, 2 SC, and 1 MS joints from a thorax CT for each patient. All joints were classified as: normal (0); suspicious (1), mild (2), moderate (3), or severe (4). RESULTS: Total CV and CTr joint scores differed between diseases (p < .001). Male AS patients had higher CV and CTr scores than female AS patients (male CV score: 52 [range 0-96] and CTr score: 22 [range 0-80]; female CV score: 20 [range 0-96] and CTr score: 12 [range 0-79]). Strong negative correlations were detected in AS patients between chest expansion and CV (r = -0.703 p = .007) and CTr (r = -0.763 p = .002) joint involvement; positive correlations between CV and CTr joints, and modified Stoke Ankylosing Spondylitis Spinal Score (p < .05); and no significant association for MS and SC joints. CONCLUSIONS: CV and CTr joint involvement on thorax CT was more severe in AS and negatively affected chest expansion. The use of thorax CT scans performed for other indications in the examination of these joints may be advantageous for the early beginning of rehabilitation programs targeted at maintaining chest mobility.

Two in one: Overlapping CT findings of COVID-19 and underlying lung diseases.

Coronavirus disease 2019 (COVID-19) is associated with pneumonia and has various pulmonary manifestations on computed tomography (CT). Although COVID-19 pneumonia is usually seen as bilateral predominantly peripheral ground-glass opacities with or without consolidation, it can present with atypical radiological findings and resemble the imaging findings of other lung diseases. Diagnosis of COVID-19 pneumonia is much more challenging for both clinicians and radiologists in the presence of pre-existing lung disease. The imaging features of COVID-19 and underlying lung disease can overlap and obscure the findings of each other. Knowledge of the radiological findings of both diseases and possible complications, correct diagnosis, and multidisciplinary consensus play key roles in the appropriate management of diseases. In this pictorial review, the chest CT findings are presented of patients with underlying lung diseases and overlapping COVID-19 pneumonia and the various reasons for radiological lung abnormalities in these patients are discussed.

Admission chest CT findings and risk assessment for stroke-associated pneumonia.

INTRODUCTION: Stroke-associated pneumonia (SAP) is a significant cause of morbidity and mortality after stroke. Various factors, including dysphagia and stroke severity, are closely related to SAP risk; however, the contribution of the baseline pulmonary parenchymal status to this interplay is an understudied field. Herein, we evaluated the prognostic performance of admission chest computed tomography (CT) findings in predicting SAP. METHODS: We evaluated admission chest CT images, acquired as part of a COVID-19-related institutional policy, in a consecutive series of acute ischemic stroke patients. The pulmonary opacity load at baseline was quantified using automated volumetry and visual scoring algorithms. The relationship between pulmonary opacities with risk of pneumonia within 7 days of symptom onset (i.e., SAP) was evaluated by bivariate and multivariate analyses. RESULTS: Twenty-three percent of patients in our cohort (n = 100) were diagnosed with SAP. Patients with SAP were more likely to have atrial fibrillation, COPD, severe neurological deficits, and dysphagia. The visual opacity score on chest CT was significantly higher among patients who developed SAP (p = 0.014), while no such relationship was observed in terms of absolute or relative opacity volume. In multivariate analyses, admission stroke severity, presence of dysphagia and a visual opacity score of ≥ 3 (OR 6.37, 95% CI 1.61-25.16; p = 0.008) remained significantly associated with SAP risk. CONCLUSIONS: Pulmonary opacity burden, as evaluated on admission chest CT, is significantly associated with development of pneumonia within initial days of stroke. This association is independent of other well-known predisposing factors for SAP, including age, stroke severity, and presence of dysphagia.

Multimodal Biomedical Data Fusion Using Sparse Canonical Correlation Analysis and Cooperative Learning: A Cohort Study on COVID-19.

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (corr(Xu1, Zv1) = 0.596, p-value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

Outcomes of high-risk breast lesions diagnosed using image-guided core needle biopsy: results from a multicenter retrospective study.

PURPOSE: The clinical management of high-risk lesions using image-guided biopsy is challenging. This study aimed to evaluate the rates at which such lesions were upgraded to malignancy and identify possible predictive factors for upgrading high-risk lesions. METHODS: This retrospective multicenter analysis included 1.343 patients diagnosed with high-risk lesions using an image-guided core needle or vacuum-assisted biopsy (VAB). Only patients managed using an excisional biopsy or with at least one year of documented radiological follow-up were included. For each, the Breast Imaging Reporting and Data System (BI-RADS) category, number of samples, needle thickness, and lesion size were correlated with malignancy upgrade rates in different histologic subtypes. Pearson's chi-squared test, the Fisher-Freeman-Halton test, and Fisher's exact test were used for the statistical analyses. RESULTS: The overall upgrade rate was 20.6%, with the highest rates in the subtypes of intraductal papilloma (IP) with atypia (44.7%; 55/123), followed by atypical ductal hyperplasia (ADH) (38.4%; 144/375), lobular neoplasia (LN) (12.7%; 7/55), papilloma without atypia (9.4%; 58/611), flat epithelial atypia (FEA) (8.7%; 10/114), and radial scars (RSs) (4.6%; 3/65). There was a significant relationship between the upgrade rate and BI-RADS category, number of samples, and lesion size Lesion size was the most predictive factor for an upgrade in all subtypes. CONCLUSION: ADH and atypical IP showed considerable upgrade rates to malignancy, requiring surgical excision. The LN, IP without atypia, pure FEA, and RS subtypes showed lower malignancy rates when the BI-RADS category was lower and in smaller lesions that had been adequately sampled using VAB. After being discussed in a multidisciplinary meeting, these cases could be managed with follow-up instead of excision.