Image quality of lung perfusion with photon-counting-detector CT: comparison with dual-source, dual-energy CT.

PURPOSE: To evaluate the quality of lung perfusion imaging obtained with photon-counting-detector CT (PCD-CT) in comparison with dual-source, dual-energy CT (DECT). METHODS: Seventy-one consecutive patients scanned with PCD-CT were compared to a paired population scanned with dual-energy on a 3rd-generation DS-CT scanner using (a) for DS-CT (Group 1): collimation: 64 × 0.6 × 2 mm; pitch: 0.55; (b) for PCD-CT (Group 2): collimation: 144 × 0.4 mm; pitch: 1.5; single-source acquisition. The injection protocol was similar in both groups with the reconstruction of perfusion images by subtraction of high- and low-energy virtual monoenergetic images. RESULTS: Compared to Group 1, Group 2 examinations showed: (a) a shorter duration of data acquisition (0.93 ± 0.1 s vs 3.98 ± 0.35 s; p < 0.0001); (b) a significantly lower dose-length-product (172.6 ± 55.14 vs 339.4 ± 75.64 mGy·cm; p < 0.0001); and (c) a higher level of objective noise (p < 0.0001) on mediastinal images. On perfusion images: (a) the mean level of attenuation did not differ (p = 0.05) with less subjective image noise in Group 2 (p = 0.049); (b) the distribution of scores of fissure visualization differed between the 2 groups (p < 0.0001) with a higher proportion of fissures sharply delineated in Group 2 (n = 60; 84.5% vs n = 26; 26.6%); (c) the rating of cardiac motion artifacts differed between the 2 groups (p < 0.0001) with a predominance of examinations rated with mild artifacts in Group 2 (n = 69; 97.2%) while the most Group 1 examinations showed moderate artifacts (n = 52; 73.2%). CONCLUSION: PCD-CT acquisitions provided similar morphologic image quality and superior perfusion imaging at lower radiation doses. CLINICAL RELEVANCE STATEMENT: The improvement in the overall quality of perfusion images at lower radiation doses opens the door for wider applications of lung perfusion imaging in clinical practice. KEY POINTS: The speed of data acquisition with PCD-CT accounts for mild motion artifacts. Sharply delineated fissures are depicted on PCD-CT perfusion images. High-quality perfusion imaging was obtained with a 52% dose reduction.

Recent symptomatic omicron infection reduced COVID-19 pneumonia risk during reinfection: A computed tomography-based cohort study.

OBJECTIVES: SARS-CoV-2 infection could cause persistent lung injury or indicate potential genetic susceptibilities. While infection-elicited hybrid immunity could protect against severe COVID-19, it remains unknown whether recent infection could reduce pneumonia risk during reinfection due to insufficient viral and chest CT screening. METHODS: 15,598 patients, 96% fully vaccinated and 52% boosted, from Xiangyang, China who had symptomatic COVID-19 and chest CT scans during the first omicron BF.7 wave in December 2022 to January 2023 were followed through the second omicron XBB.1.5 wave between May and August 2023. 17,968 second-wave COVID-19 patients with chest CT scans but without prior symptomatic COVID-19 history were enrolled as first-time infection controls. RESULTS: 19.6% (3,061/15,598) first-wave patients were diagnosed with pneumonia. Among second-wave reinfected patients, only 0.2% (4/2,202) developed pneumonia, which was lower than the 1.7% (311/17,968) pneumonia prevalence among second-wave first-time patients, with adjusted relative risk (RR) of 0.11 (95% CI: 0.04-0.29). 1.3% (40/3,039) first wave pneumonia survivors showed residual abnormal patterns in follow-up CT scans within 8 months after pneumonia diagnosis. CONCLUSIONS: In a highly vaccinated population, prior symptomatic omicron infection within 8 months reduced pneumonia risk during reinfection. Uninfected individuals might need up-to-date vaccination to reduce pneumonia risk.

An advanced multisystem histiocytic sarcoma in a pregnant woman: A case report.

Histiocytic sarcoma is an extremely rare disease that's hard to diagnose and treat, often leading to a poor prognosis. Here, we present a case report detailing a rare occurrence of HS in a 37-year-old pregnant woman who first presented with left shoulder pain, palpitations, and a productive cough at 20 weeks of gestation. Her diagnostic evaluations were performed, including different imaging modalities such as chest X-rays, CT scans, and MRI. Imaging revealed a large mediastinal mass with extensive involvement of the adrenal glands, lungs, and lymph nodes. The definitive diagnosis of HS is based on pathological and morphological features, and the immunohistochemistry report plays a key role. In our case, the diagnosis of HS was confirmed through pathological evaluation and immunohistochemistry, with a positive CD68 result obtained from a supraclavicular lymph node biopsy. A hospital committee comprising medical specialists like hematologists-oncologists, pathologists, pulmonologists, and obstetricians was brought together to assess the case collectively. The patient received chemotherapy, which alleviated her symptoms and maintained her condition. Based on the committee's recommendations, despite a healthy fetus and normal obstetric sonograms, the decision was made to terminate the pregnancy with the consent of the patient and her family. Despite initial improvement postchemotherapy, the patient's condition worsened, necessitating intubation. Tragically, two months after the initial admission, the patient passed away due to severe complications. In this case report, we provide a literature review and review of the patient's imaging reports. Since the patient is pregnant and HS is uncommon, it's important to highlight that this case is unique and worth sharing.

Utility of block-matching and 3D filter for reproducibility of lung density and denoising in low-dose chest CT: A pilot study.

PURPOSE: This study aimed to acquire an image quality consistent with that of full-dose chest computed tomography (CT) when obtaining low-dose chest CT images and to analyze the effects of block-matching and 3D (BM3D) filters on lung density measurements and noise reduction in lung parenchyma. METHODS: Using full-dose chest CT images, we evaluated lung density measurements and noise reduction in lung parenchyma images for low-dose chest CT. Three filters (median, Wiener, and the proposed BM3D) were applied to low-dose chest CT images for comparison and analysis with images from full-dose chest CT. To evaluate lung density measurements, we measured CT attenuation at the 15th percentile of the lung CT histogram. The coefficient of variation (COV) and contrast-to-noise ratio (CNR) were used to evaluate the noise level. RESULTS: The 15th percentile of the lung CT histogram showed the smallest difference between full- and low-dose CT when applying the BM3D filter, and the highest difference between full- and low-dose CT without filters (full-dose =  - 926.28 ± 0.32, BM3D =  - 926.65 ± 0.32, and low-dose =  - 959.43 ± 0.95) (p < 0.05). The COV was smallest when applying the BM3D filter, whereas the CNR was the highest (p < 0.05). CONCLUSIONS: The results of the study prove that the BM3D filter can reduce image noise while increasing the reproducibility of the lung density, even for low-dose chest CT.

A Case of Postoperative Noncardiogenic Edema: Negative Pressure Pulmonary Edema.

A case of complete recovery of negative pressure pulmonary edema after a Cottle surgery in a 24-year-old male. Teaching point: Negative pressure pulmonary edema is an important cause of postoperative noncardiogenic edema, with the spontaneous disappearance of all complaints within a relatively short period.

Is Type and Grade of Emphysema Important for Bone Mineral Density and Aortic Calcifications?

Background: Chronic obstructive pulmonary disease has extrapulmonary manifestations, such as cardiovascular diseases and osteoporosis. The purpose of this research was to determine the relationship between the type and extent of emphysema with thoracic aorta calcification (TAC) and bone mineral density (BMD) at Th4, Th8, and L1 vertebrae. Methods: Emphysema was described by computed tomography parameters (both Fleischner classification and low attenuation value percentage, LAV%) and the clinical FEV1/FVC ratio (Tiffeneau-Pinelli index, TI, TI < 0.7; TI > 0.7). Results: Of 200 included patients (median age 64, 33% women), signs of clinical obstruction (TI) were observed in 104 patients, which had significantly lower BMD and more heavy TAC. BMD correlated negatively with LAV%, Rho = -0.16 to -0.23, while a positive correlation of aortic calcification with LAV% was observed, Rho = 0.30 to 0.33. Multiple linear regression showed that age and TI < 0.7 were independent predictors of BMD, ß = -0.20 to -0.40, and ß = -0.21 to -0.25; age and hypercholesterolemia were independent predictors of TCA, ß = 0.61 and ß = 0.19. Conclusions: Clinical TI and morphological LAV% parameters correlated with BMD and TAC, in contrast to Fleischer-graded emphysema, which showed no correlation. However, only TI was an independent predictor of BMD, while the morphologically described type and extent of emphysema could not independently predict any extrapulmonary manifestation.

Potential Predictive of Thoracic CT Value and Bone Mineral Density T-Value in COPD Complicated with Osteoporosis.

Background: COPD, combined with Osteoporosis, has a high incidence and potential for great harm. Choosing an optimal diagnostic method to achieve bone mineral density (BMD) screening is crucial for COPD patients. Studies on COPD patients with BMD reduction are lacking. Purpose: To identify the risk factors of BMD reduction and osteoporosis in COPD patients. Patients and Methods: We included a total of 81 patients with AECOPD, who were admitted to the hospital from July 1, 2019, to January 31, 2020. Patients were grouped into BMD normal group, BMD reduced group and OP group. The areas under ROC curve were used to explore the value of CT values in the diagnosis of bone abnormality, and clinical indicators were collected. Results: The CT value of the vertebral cancellous bone is highly correlated with the T value of BMD (R > 5.5, P < 0.0001). Using multivariate Logistic regression analysis, we showed that COPD duration, BMI, 25-hydroxyvitamin D3, and long-term inhaled glucocorticoid were independent factors affecting different BMD levels in COPD patients. No significant difference in bone formation indexes between groups. ß-crossL was negatively correlated with serum IL-6 (r=-0.254, P=0.022), and ALP was positively correlated with serum TNF-α (r=0.284, P=0.023). Conclusion: Thoracolumbar vertebral cancellous bone CT has potential value in the diagnosis of bone abnormality. COPD duration, BMI, 25-hydroxyvitamin D3, and long-term inhaled glucocorticoid may contribute to the BMD reduction in COPD patients, and serum IL-6 and TNF-α regulate bone metabolism in COPD patients.

ACR Appropriateness Criteria® Pulmonary Arteriovenous Malformation (PAVM): 2023 Update.

Pulmonary arteriovenous malformations (PAVMs) occur in 30% to 50% of patients with hereditary hemorrhagic telangiectasia. Clinical presentations vary from asymptomatic disease to complications resulting from the right to left shunting of blood through the PAVM such as paradoxical stroke, brain abscesses, hypoxemia, and cardiac failure. Radiology plays an important role both in the diagnosis and treatment of PAVM. Based on different clinical scenarios, the appropriate imaging study has been reviewed and is presented in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

A new computed tomography score-based staging for melioidosis pneumonia to predict progression.

Background: Melioidosis pneumonia, caused by the bacterium Burkholderia pseudomallei, is a serious infectious disease prevalent in tropical regions. Chest computed tomography (CT) has emerged as a valuable tool for assessing the severity and progression of lung involvement in melioidosis pneumonia. However, there persists a need for the quantitative assessment of CT characteristics and staging methodologies to precisely anticipate disease progression. This study aimed to quantitatively extract CT features and evaluate a CT score-based staging system in predicting the progression of melioidosis pneumonia. Methods: This study included 97 patients with culture-confirmed melioidosis pneumonia who presented between January 2002 and December 2021. Lung segmentation and annotation of lesions (consolidation, nodules, and cavity) were used for feature extraction. The features, including the involved area, amount, and intensity, were extracted. The CT scores of the lesion features were defined by the feature importance weight and qualitative stage of melioidosis pneumonia. Gaussian process regression (GPR) was used to predict patients with severe or critical melioidosis pneumonia according to CT scores. Results: The melioidosis pneumonia stages included acute stage (0-7 days), subacute stage (8-28 days), and chronic stage (>28 days). In the acute stage, the CT scores of all patients ranged from 2.5 to 6.5. In the subacute stage, the CT scores for the severe and mild patients were 3.0-7.0 and 2.0-5.0, respectively. In the chronic stage, the CT score of the mild patients fluctuated approximately between 2.5 and 3.5 in a linear distribution. Consolidation was the most common type of lung lesion in those with melioidosis pneumonia. Between stages I and II, the percentage of severe scans with nodules dropped from 72.22% to 47.62% (P<0.05), and the percentage of severe scans with cavities significantly increased from 16.67% to 57.14% (P<0.05). The GPR optimization function yielded area under the receiver operating characteristic curves of 0.71 for stage I, 0.92 for stage II, and 0.87 for all stages. Conclusions: In patients with melioidosis pneumonia, it is reasonable to divide the period (the whole progression of melioidosis pneumonia) into three stages to determine the prognosis.

A Literature Review on the Relative Diagnostic Accuracy of Chest CT Scans versus RT-PCR Testing for COVID-19 Diagnosis.

BACKGROUND: Reverse transcription polymerase chain reaction (RT-PCR) is the main technique used to identify COVID-19 from respiratory samples. It has been suggested in several articles that chest CTs could offer a possible alternate diagnostic tool for COVID-19; however, no professional medical body recommends using chest CTs as an early COVID-19 detection modality. This literature review examines the use of CT scans as a diagnostic tool for COVID-19. METHOD: A comprehensive search of research works published in peer-reviewed journals was carried out utilizing precisely stated criteria. The search was limited to English-language publications, and studies of COVID-19-positive patients diagnosed using both chest CT scans and RT-PCR tests were sought. For this review, four databases were consulted: these were the Cochrane and ScienceDirect catalogs, and the CINAHL and Medline databases made available by EBSCOhost. FINDINGS: In total, 285 possibly pertinent studies were found during an initial search. After applying inclusion and exclusion criteria, six studies remained for analysis. According to the included studies, chest CT scans were shown to have a 44 to 98% sensitivity and 25 to 96% specificity in terms of COVID-19 diagnosis. However, methodological limitations were identified in all studies included in this review. CONCLUSION: RT-PCR is still the suggested first-line diagnostic technique for COVID-19; while chest CT is adequate for use in symptomatic patients, it is not a sufficiently robust diagnostic tool for the primary screening of COVID-19.

Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning.

OBJECTIVES: To assess the accuracy of a deep learning-based algorithm for fully automated detection of thoracic aortic calcifications in chest computed tomography (CT) with a focus on the aortic clamping zone. METHODS: We retrospectively included 100 chest CT scans from 91 patients who were examined on second- or third-generation dual-source scanners. Subsamples comprised 47 scans with an electrocardiogram-gated aortic angiography and 53 unenhanced scans. A deep learning model performed aortic landmark detection and aorta segmentation to derive 8 vessel segments. Associated calcifications were detected and their volumes measured using a mean-based density thresholding. Algorithm parameters (calcium cluster size threshold, aortic mask dilatation) were varied to determine optimal performance for the upper ascending aorta that encompasses the aortic clamping zone. A binary visual rating served as a reference. Standard estimates of diagnostic accuracy and inter-rater agreement using Cohen's Kappa were calculated. RESULTS: Thoracic aortic calcifications were observed in 74% of patients with a prevalence of 27-70% by aorta segment. Using different parameter combinations, the algorithm provided binary ratings for all scans and segments. The best performing parameter combination for the presence of calcifications in the aortic clamping zone yielded a sensitivity of 93% and a specificity of 82%, with an area under the receiver operating characteristic curve of 0.874. Using these parameters, the inter-rater agreement ranged from κ 0.66 to 0.92 per segment. CONCLUSIONS: Fully automated segmental detection of thoracic aortic calcifications in chest CT performs with high accuracy. This includes the critical preoperative assessment of the aortic clamping zone.

Characteristics of atypical Pulmonary Tuberculosis without typical clinical features diagnosed by pathology.

PURPOSE: Some patients with pulmonary tuberculosis (PTB) do not display typical clinical features, leading to delays in diagnosis and treatment. METHODS: We retrospectively analyzed PTB patients admitted to the Second Affiliated Hospital of Chongqing Medical University between 2017 and 2020. They are divided into pathological group (diagnosed through pathological biopsy) and control group (diagnosed via sputum or lavage fluid). Clinical data of both groups were compared. Based on radiographic features, the pathological group was further divided into the inflammation group, peripheral nodule group, and central occupancy group. We then statistically analyzed the computed tomography (CT) signs, bronchoscopic manifestations and results of pathological biopsy for each subgroup. RESULTS: The pathological group consisted of 75 patients, while the control group had 338 patients. Multivariate logistic regression analysis showed that the pathological group had more diabetes (OR = 3.266, 95% CI = 1.609-6.630, P = 0.001), lower ESR (OR = 0.984, 95% CI = 0.971-0.998, P = 0.022), and lower CRP (OR = 0.990, 95% CI = 0.980-0.999, P = 0.036). In the three subgroups, the exudative lesions in the inflammation group were mostly located in atypical areas of PTB. The lobulation sign and spiculation sign were frequently observed in the peripheral nodule group. All presented with significant hilar mediastinal lymphadenopathy in the central occupancy group. In the pathological group, bronchoscopic manifestations typically included mucosal edema and bronchial stenosis. CONCLUSION: Diabetes is an independent risk factor for atypical PTB. Expression of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) in atypical PTB is low. Radiologically, it is most easily misdiagnosed when presented as peripheral solid nodules or masses, so a biopsy is recommended.

Chest CT Imaging Provides More Information Than Chest Radiography Alone in Determining Extent of Physiologic Impairment in Pulmonary Sarcoidosis.

BACKGROUND: Sarcoidosis staging primarily has relied on the Scadding chest radiographic system, although chest CT imaging is finding increased clinical use. RESEARCH QUESTION: Whether standardized chest CT scan assessment provides additional understanding of lung function beyond Scadding stage and demographics is unknown and the focus of this study. STUDY DESIGN AND METHODS: We used the National Heart, Lung, and Blood Institute study Genomics Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis cases of sarcoidosis (n = 351) with Scadding stage and chest CT scans obtained in a standardized manner. One chest radiologist scored all CT scans with a visual scoring system, with a subset read by another chest radiologist. We compared demographic features, Scadding stage, and CT scan findings and the correlation between these measures. Associations between spirometry results and Dlco, CT scan findings, and Scadding stage were determined using regression analysis (n = 318). Agreement between readers was evaluated using Cohen's κ value. RESULTS: CT scan features were inconsistent with Scadding stage in approximately 40% of cases. Most CT scan features assessed on visual scoring were associated negatively with lung function. Associations persisted for FEV1 and Dlco when adjusting for Scadding stage, although some CT scan feature associations with FVC became insignificant. Scadding stage was associated primarily with FEV1, and inclusion of CT scan features reduced significance in association between Scadding stage and lung function. Multivariable regression modeling to identify radiologic measures explaining lung function included Scadding stage for FEV1 and FEV1 to FVC ratio (P < .05) and marginally for Dlco (P < .15). Combinations of CT scan measures accounted for Scadding stage for FVC. Correlations among Scadding stage and CT scan features were noted. Agreement between readers was poor to moderate for presence or absence of CT scan features and poor for degree and location of abnormality. INTERPRETATION: CT scan features explained additional variability in lung function beyond Scadding stage, with some CT scan features obviating the associations between lung function and Scadding stage. Whether CT scan features, phenotypes, or endotypes could be useful for managing patients with sarcoidosis needs more study.

Efficacy of Opportunistic Screening with Chest CT in Identifying Osteoporosis and Osteopenia in Patients with T2DM.

Purpose: To explore the validity of the thoracic spine Hounsfield Unit (HU) measured by chest computed tomography (CT) for opportunistic screening of diabetic osteoporosis. The current study attempted to establish a diagnostic threshold for thoracic spine HU in a type 2 diabetes mellitus (T2DM) population with osteoporosis. Patients and Methods: The current study retrospectively included 334 patients with T2DM. They underwent chest CT and Dual-energy X-ray (DXA) between August 2021 and January 2022 in our hospital. HU values were measured on the resulting chest CT images at thoracic spine 11 and 12 to construct regions of interest. All patients were grouped according to the lowest T-value of DXA examination: osteoporosis, osteopenia and normal bone density. HU values were compared with T-values in each group of patients, and receiver operating characteristics curves were plotted to calculate diagnostic thresholds as well as sensitivity and specificity. Results: There was a strong correlation between the HU values of chest CT and the T-values of DXA (p < 0.01). The sensitivity for osteoporosis was 88.7% for T11 attenuation≤ 98 HU and the specificity for osteoporosis was 87.5% for T12 attenuation ≤ 117HU; the specificity for normal BMD was 85.4% for T11 attenuation ≥ 147 HU and 82% for T12 attenuation ≥ 146 HU. Conclusion: Chest CT can be used to screen patients with T2DM for opportunistic osteoporosis and help determine if they need DXA screening. The current study suggests that when the HU threshold of T11 ≤ 98/T12 ≤ 117, patients may need further osteoporosis screening.

Comparing Visual and Software-Based Quantitative Assessment Scores of Lungs' Parenchymal Involvement Quantification in COVID-19 Patients.

(1) Background: Computed tomography (CT) plays a paramount role in the characterization and follow-up of COVID-19. Several score systems have been implemented to properly assess the lung parenchyma involved in patients suffering from SARS-CoV-2 infection, such as the visual quantitative assessment score (VQAS) and software-based quantitative assessment score (SBQAS) to help in managing patients with SARS-CoV-2 infection. This study aims to investigate and compare the diagnostic accuracy of the VQAS and SBQAS with two different types of software based on artificial intelligence (AI) in patients affected by SARS-CoV-2. (2) Methods: This is a retrospective study; a total of 90 patients were enrolled with the following criteria: patients' age more than 18 years old, positive test for COVID-19 and unenhanced chest CT scan obtained between March and June 2021. The VQAS was independently assessed, and the SBQAS was performed with two different artificial intelligence-driven software programs (Icolung and CT-COPD). The Intraclass Correlation Coefficient (ICC) statistical index and Bland-Altman Plot were employed. (3) Results: The agreement scores between radiologists (R1 and R2) for the VQAS of the lung parenchyma involved in the CT images were good (ICC = 0.871). The agreement score between the two software types for the SBQAS was moderate (ICC = 0.584). The accordance between Icolung and the median of the visual evaluations (Median R1-R2) was good (ICC = 0.885). The correspondence between CT-COPD and the median of the VQAS (Median R1-R2) was moderate (ICC = 0.622). (4) Conclusions: This study showed moderate and good agreement upon the VQAS and the SBQAS; enhancing this approach as a valuable tool to manage COVID-19 patients and the combination of AI tools with physician expertise can lead to the most accurate diagnosis and treatment plans for patients.

A Multichannel CT and Radiomics-Guided CNN-ViT (RadCT-CNNViT) Ensemble Network for Diagnosis of Pulmonary Sarcoidosis.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. The early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings poses challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we develop a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures the localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieves the highest performance with accuracy, sensitivity, specificity, precision, F1-score, and combined AUC of 0.93 ± 0.04, 0.94 ± 0.04, 0.93 ± 0.08, 0.95 ± 0.05, 0.94 ± 0.04, and 0.97, respectively, in a five-fold cross-validation study with pulmonary sarcoidosis (n = 126) and LCa (n = 93) cases. A detailed ablation study showing the impact of CNN + ViT compared to CNN or ViT alone, and CT + radiomics input, compared to CT or radiomics alone, is also presented in this work. Overall, the AI model developed in this work offers promising potential for triaging the pulmonary sarcoidosis patients for timely diagnosis and treatment from chest CT.

Pulmonary Function, Computed Tomography Lung Abnormalities, and Small Airway Disease after COVID-19: 3-, 6-, and 9-Month Follow-Up.

Background/Objectives: Coronavirus disease 2019 (COVID-19) course may differ among individuals-in particular, those with comorbidities may have severe pneumonia, requiring oxygen supplementation or mechanical ventilation. Post-COVID-19 long-term structural changes in imaging studies can contribute to persistent respiratory disturbance. This study aimed to investigate COVID-19 sequels affecting the possibility of persistent structural lung tissue abnormalities and their influence on the respiratory function of peripheral airways and gas transfer. Methods: Patients were divided into two groups according to severity grades described by the World Health Organization. Among the 176 hospitalized patients were 154 patients with mask oxygen supplementation and 22 patients with high-flow nasal cannula (HFNC) or mechanical ventilation. All tests were performed at 3, 6, and 9 months post-hospitalization. Results: Patients in the severe/critical group had lower lung volumes in FVC, FVC%, FEV1, FEV1%, LC, TLC%, and DLCO% at three months post-hospitalization. At 6 and 9 months, neither group had significant FVC and FEV1 value improvements. The MEF 25-75 values were not significantly higher in the mild/moderate group than in the severe/critical group at three months. There were weak significant correlations between FVC and FEV1, MEF50, MEF 75, plethysmography TLC, disturbances in DLCO, and total CT abnormalities in the severe/critical group at three months. In a mild/moderate group, there was a significant negative correlation between the spirometry, plethysmography parameters, and CT lesions in all periods. Conclusions: Persistent respiratory symptoms post-COVID-19 can result from fibrotic lung parenchyma and post-infectious stenotic small airway changes not visible in CT, probably due to persistent inflammation.

Phenotype and Clinicoradiological Differences in Multifocal and Focal Bronchiectasis.

Introduction: Bronchiectasis is a chronic progressive respiratory disease characterized by permanent dilatation of the bronchi. It is a complex condition with numerous different etiologies, co-morbidities, and a heterogeneous presentation. As we know, there is a lack of studies that describe the differences and compare the characteristics between focal and multifocal bronchiectasis. The aim of this study is to identify differences in clinical characteristics presentation, severity or distribution in focal and multifocal bronchiectasis, and prognostic implications. Methods: 126 patients with computed tomography (CT)-verified bronchiectasis were enrolled. Baseline characteristics that included age, sex, smoking history, and respiratory symptoms were recorded, with special attention paid to hemoptysis appearance, body mass index, and comorbidities. The type of bronchiectasis determined by CT scan and the modified Reiff scores indicating radiological severity were recorded. Patients were divided in two groups (I is focal and II is multifocal). Results: There were no statistically significant differences in age, smoking status, comorbidity, and BMI between the two groups. Multifocality was associated with a significantly higher proportion of females (p = 0.014), the rate of hemoptysis (p = 0.023), and the number of hospitalizations, but not of exacerbations and prevalence of immunodeficiency (p = 0.049). Significantly, a high number of subjects with multifocality had bronchiectasis of moderate severity, and post-infective and asthma-associated phenotypes were the dominant in this group. Unexpectedly, the cystic and varicose radiological phenotype (which need more time to develop) were more dominant in the focal group. The cylindrical phenotype was equally observed in the multifocal and focal groups. Conclusions: Our study suggests that multifocality is not related to age, number of exacerbations, or radiological phenotype, but it seems to be associated with the clinical post-infective phenotype, immunodeficiency, frequent hospitalizations, and severity. Thus, the presence of multifocal bronchiectasis may act as a biomarker of severity and poor outcomes in these patients.