Search

Purpose: To develop a comprehensive multi-classification model that combines radiomics and clinic-radiological features to accurately predict the invasiveness and differentiation of pulmonary adenocarcinoma nodules. Methods: A retrospective analysis was conducted on a cohort comprising 500 patients diagnosed with lung adenocarcinoma between January 2020 and December 2022. The dataset included preoperative CT images and histological reports of adenocarcinoma in situ (AIS, n = 97), minimally invasive adenocarcinoma (MIA, n = 139), and invasive adenocarcinoma (IAC, n = 264) with well-differentiated (WIAC, n = 99), moderately differentiated (MIAC, n = 84), and poorly differentiated IAC (PIAC, n = 81). The patients were classified into two groups (IAC and non-IAC) for binary classification and further divided into three and five groups for multi-classification. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) algorithm to identify the most informative radiomics and clinic-radiological features. Eight machine learning (ML) models were developed using these features, and their performance was evaluated using accuracy (ACC) and the area under the receiver-operating characteristic curve (AUC). Results: The combined model, utilizing the support vector machine (SVM) algorithm, demonstrated improved performance in the testing cohort, achieving an AUC of 0.942 and an ACC of 0.894 for the two-classification task. For the three- and five-classification tasks, the combined model employing the one versus one strategy of SVM (SVM-OVO) outperformed other models, with ACC values of 0.767 and 0.607, respectively. The AUC values for histological subtypes ranged from 0.787 to 0.929 in the testing cohort, while the Macro-AUC and Micro-AUC of the multi-classification models ranged from 0.858 to 0.896. Conclusions: A multi-classification radiomics model combined with clinic-radiological features, using the SVM-OVO algorithm, holds promise for accurately predicting the histological characteristics of pulmonary adenocarcinoma nodules, which contributes to personalized treatment strategies for patients with lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Background: Current guidelines support different management of cryptococcosis between severely immunodeficient and immunocompetent populations. However, few studies have focused on cryptococcosis patients with mild-to-moderate immunodeficiency. We performed this study to determine the clinical features of pulmonary (PC) and extrapulmonary cryptococcosis (EPC) and compared them among populations with different immune statuses to support appropriate clinical management of this public health threat.Methods: All cases were reported by 14 tertiary teaching hospitals in Jiangsu Province, China from January 2013 to December 2018. The trends in incidence, demographic data, medical history, clinical symptoms, laboratory test indicators, imaging characteristics and diagnostic method of these patients were then stratified by immune status, namely immunocompetent (IC, patients with no recognized underlying disease or those with an underlying disease that does not influence immunity, such as hypertension), mild-to-moderate immunodeficiency (MID, patients with diabetes mellitus, end-stage liver or kidney disease, autoimmune diseases treated with low-dose glucocorticoid therapy, and cancer treated with chemotherapy) and severe immunodeficiency (SID, patients with acquired immunodeficiency syndrome, haematologic malignancies, solid organ transplantation or haematologic stem cell transplantation, idiopathic CD4 lymphocytosis, agranulocytosis, aggressive glucocorticoid or immunosuppressive therapy and other conditions or treatments that result in severe immunosuppression).Results: The clinical data of 255 cryptococcosis patients were collected. In total, 66.3% of patients (169) were IC, 16.9% (43) had MID, and 16.9% (43) had SID. 10.1% of the patients (17) with IC were EPC, 18.6% of the patients (8) with MID were EPC, and 74.4% of patients (32) were EPC (IC/MID vs. SID, p < 0.001). Fever was more common in the SID group than in the IC and MID groups (69.8% vs. 14.8% vs. 37.2%, p < 0.001). Of chest CT scan, most lesions were distributed under the pleura (72.7%), presenting as nodules/lumps (90.3%) or consolidations (10.7%). Pleural effusion was more common in SID group compared to IC group (33.3% vs. 2.4%, p < 0.001). Positivity rate on the serum capsular polysaccharide antigen detection (CrAg) test was higher in the SID group than in the other two groups [100.0% vs. 84.4% (MID) vs. 78.2% (IC), p = 0.013]. Positivity rate on the serum CrAg test was also higher in cryptococcal meningitis patients than in PC patients (100.0% vs. 79.5%, p = 0.015).Conclusions: The clinical presentation of MID patients is intermediate between SID and IC patients and is similar to that of IC patients. The serum CrAg test is more sensitive for the identification of SID or EPC patients. [ABSTRACT FROM AUTHOR]