Publications by authors named "P J ten Berge"
Background: Computed tomography (CT) is a critical tool for the diagnosis of pneumonia caused by SARS-CoV-2. The Delta and Omicron variants show distinct clinical features, but the radiological differences between pneumonia caused by these variants have not been extensively studied in patients with oxygen-dependent pneumonia.
Objective: To compare the radiological and clinical features of pneumonia in patients hospitalized with oxygen-dependent SARS-CoV-2 infection caused by the Delta and Omicron variants.
Purpose: Neoadjuvant chemotherapy is now a common first line therapy for breast cancer. International guidelines recommend placement of a clip before commencement of therapy to assist with localizing the tumor bed in the event of excellent response-this takes up time and resources. The microcalcifications associated usually persist after chemotherapy and could serve as an alternative marker.
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- This study aims to develop a deep learning method for detecting pulmonary embolism (PE) and calculating its severity using specific metrics on 3D computed tomography pulmonary angiography (CTPA) images with few annotations.
- The approach includes a series of steps: identifying blood clots, classifying PE presence, and estimating both the Qanadli score and right-to-left ventricle diameter (RV/LV) ratio, utilizing data from a large set of patient examinations.
- Results showed promising accuracy for PE classification with an area under the curve (AUC) of about 0.87, and solid regression outcomes for estimating severity scores, indicating potential use of AI tools in clinical settings, though further research is needed. *
Purpose: In 2022, the French Society of Radiology together with the French Society of Thoracic Imaging and CentraleSupelec organized their 13th data challenge. The aim was to aid in the diagnosis of pulmonary embolism, by identifying the presence of pulmonary embolism and by estimating the ratio between right and left ventricular (RV/LV) diameters, and an arterial obstruction index (Qanadli's score) using artificial intelligence.
Materials And Methods: The data challenge was composed of three tasks: the detection of pulmonary embolism, the RV/LV diameter ratio, and Qanadli's score.
Purpose: The objective was to develop a radiological score obtained from multi-detector computed tomography (MDCT) to differentiate between single band adhesion (SBA) and matted adhesions (MA) as the etiology of small bowel obstruction (SBO).
Methods: All consecutive patients who underwent surgery from January 2013 to June 2018 for adhesion-induced SBO were retrospectively included.
Results: Among the 193 patients having surgery for SBO, 119 (61.