Objectives: To develop and validate an MR radiomics-based nomogram to predict the presence of MVI in patients with solitary HCC and further evaluate the performance of predictors for MVI in subgroups (HCC ≤ 3 cm and > 3 cm).Materials and Methods: Between May 2015 and October 2020, 201 patients with solitary HCC were analysed. Radiomic features were extracted from precontrast T₁WI, arterial phase, portal venous phase, delayed phase and hepatobiliary phase images in regions of the intratumoral, peritumoral and their combining areas. The mRMR and LASSO algorithms were used to select radiomic features related to MVI. Clinicoradiological factors were selected by using backward stepwise regression with AIC. A nomogram was developed by incorporating the clinicoradiological factors and radiomics signature. In addition, the radiomic features and clinicoradiological factors related to MVI were separately evaluated in the subgroups (HCC ≤ 3 cm and > 3 cm).Results: Histopathological examinations confirmed MVI in 111 of the 201 patients (55.22%). The radiomics signature showed a favourable discriminatory ability for MVI in the training set (AUC, 0.896) and validation set (AUC, 0.788). The nomogram incorporating peritumoral enhancement, tumour growth type and radiomics signature showed good discrimination in the training (AUC, 0.932) and validation sets (AUC, 0.917) and achieved well-fitted calibration curves. Subgroup analysis showed that tumour growth type was a predictor for MVI in the HCC ≤ 3 cm cohort and peritumoral enhancement in the HCC > 3 cm cohort; radiomic features related to MVI varied between the HCC ≤ 3 cm and HCC > 3 cm cohort. The performance of the radiomics signature improved noticeably in both the HCC ≤ 3 cm (AUC, 0.953) and HCC > 3 cm cohorts (AUC, 0.993) compared to the original training set.Conclusions: The preoperative nomogram integrating clinicoradiological risk factors and the MR radiomics signature showed favourable predictive efficiency for predicting MVI in patients with solitary HCC. The clinicoradiological factors and radiomic features related to MVI varied between subgroups (HCC ≤ 3 cm and > 3 cm). The performance of radiomics signature for MVI prediction was improved in both the subgroups.

Background: Talaromyces marneffei (T. marneffei) is an opportunistic fungal pathogen commonly found in human immunodeficiency virus (HIV) patients that often infects lymph nodes. Knowledge about the computed tomography (CT) characteristics of T. marneffei lymphadenopathy in HIV patients is limited. The aim of this study was to investigate the clinical and CT characteristics of T. marneffei lymphadenopathy to improve its diagnosis and promote recognition of this type of infection in radiology.Methods: Between February 2019 and June 2021, we retrospectively reviewed the clinical features and CT characteristics of T. marneffei lymphadenopathy in 21 HIV patients.Results: The clinical symptoms of T. marneffei infection are non-specific. Anemia (100%), fever (85.7%) and cough and sputum production (76.2%) were the most frequent symptoms. Multiple lymphadenopathies, mainly in the mediastinum (76.2%) and mesentery (82.4%), can be fused (14.3%) and necrotic (52.4%), with slight (41.7%) and moderate enhancement (58.3%) that is heterogeneous. In addition to involving the lymph nodes, the lesions involved the lungs (81.0%), liver and spleen (42.9%), and small intestine (14.3%).Conclusions: T. marneffei is prone to affecting lymph nodes and extranodal organs in HIV patients. Although the clinical manifestations of T. marneffei infection are not specific, the possibility of T. marneffei infection should be considered if CT findings indicate multiple lesion sites.