Crucial computed tomography and magnetic resonance imaging findings of fallopian tubal tuberculosis for diagnosis: a retrospective study of 26 cases.

Background: Fallopian tubal tuberculosis (FTTB), which typically presents with non-specific clinical symptoms and mimics ovarian malignancies clinically and radiologically, often affects young reproductive females and can lead to infertility if not promptly managed. Early diagnosis by imaging modalities is crucial for initiating timely anti-tuberculosis (anti-TB) treatment. Currently, comprehensive radiological descriptions of this relatively rare disease are limited.

Deep learning on longitudinal CT scans: automated prediction of treatment outcomes in hospitalized tuberculosis patients.

Three deep learning (DL)-based prediction models (PMs) using longitudinal CT images were developed to predict tuberculosis (TB) treatment outcomes. The internal dataset consists of 493 bacteriologically confirmed TB patients who completed the anti-tuberculosis treatment with three-time CT scans, including a pretreatment CT scan and two follow-up CT scans. PM1 was trained using only pretreatment CT scans, and PM2 and PM3 were developed by adding follow-up scans.