Hepatocellular carcinoma and intrahepatic cholangiocarcinoma are the two most common primary malignant tumors of the liver. The similarities and variations in imaging characteristics that may aid in distinguishing between these two primary tumors will be discussed and outlined in this review. Knowledge of imaging techniques that are currently available would assist in the differentiation between these primary malignancies.

Objective To investigate the outcomes of ventilation/ perfusion scintigraphy on the diagnosis of pulmonary embolism in coronavirus disease 2019 (COVID-19) patients, we performed a systematic review of the available literature. Materials and methodsPubMed and Scopus were systematically searched up to 4 June 2022, for relevant studies. We included studies on patients with COVID-19 who have performed ventilation/perfusion scintigraphy for diagnosis of pulmonary embolism to describe any diagnosis outcome. Irrelevant and non-English articles were excluded. ResultsOverall, 27 articles were included in our review. The database search yielded studies from PubMed, Scopus, and studies identified through reviewing the reference list of included studies. Extracted information from the included studies could be categorized into several aspects: Diagnosis of pulmonary embolism with Q single-photon emission computed tomography (SPECT) CT, Tracheobronchial uptake, Diagnostic value of V/Q rather than Q at diagnosis pulmonary embolism, Different characteristics (morphological alterations) of COVID-19 in ventilation orperfusion scan, the prevalence of pulmonary embolism with Q or V/Q criteria, and Design of radiotherapy planning in lung cancer patients with COVID-19. ConclusionDifferent perfusion patterns in COVID-19 are challenging but can be alleviated by adding SPECT/ computed tomography (CT) to lung perfusion scans. Although perfusion only SPECT/CT can rule out or rule in others in considerable number of patients, ventilation scan is still needed in certain patients. Nucl Med Commun

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Background: To study the additive value of radiomics features to the BCLC staging system in clustering HCC patients. Methods: A total of 266 patients with HCC were included in this retrospective study. All patients had undergone baseline MR imaging, and 95 radiomics features were extracted from 3D segmentations representative of lesions on the venous phase and apparent diffusion coefficient maps. A random forest algorithm was utilized to extract the most relevant features to transplant-free survival. The selected features were used alongside BCLC staging to construct Kaplan–Meier curves. Results: Out of 95 extracted features, the three most relevant features were incorporated into random forest classifiers. The Integrated Brier score of the prediction error curve was 0.135, 0.072, and 0.048 for the BCLC, radiomics, and combined models, respectively. The mean area under the receiver operating curve (ROC curve) over time for the three models was 81.1%, 77.3%, and 56.2% for the combined radiomics and BCLC models, respectively. Conclusions: Radiomics features outperformed the BCLC staging system in determining prognosis in HCC patients. The addition of a radiomics classifier increased the classification capability of the BCLC model. Texture analysis features could be considered as possible biomarkers in predicting transplant-free survival in HCC patients.