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Longitudinal assessment of diffusion-weighted imaging during magnetic resonance-guided radiotherapy in head and neck cancer.
Radiat Oncol
January 2025
German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
Background: For radiotherapy of head and neck cancer (HNC) magnetic resonance imaging (MRI) plays a pivotal role due to its high soft tissue contrast. Moreover, it offers the potential to acquire functional information through diffusion weighted imaging (DWI) with the potential to personalize treatment. The aim of this study was to acquire repetitive DWI during the course of online adaptive radiotherapy on an 1.
View Article and Find Full Text PDFDeep learning reconstruction of zero-echo time sequences to improve visualization of osseous structures and associated pathologies in MRI of cervical spine.
Insights Imaging
January 2025
Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Zurich, Switzerland.
Objectives: To determine whether deep learning-based reconstructions of zero-echo-time (ZTE-DL) sequences enhance image quality and bone visualization in cervical spine MRI compared to traditional zero-echo-time (ZTE) techniques, and to assess the added value of ZTE-DL sequences alongside standard cervical spine MRI for comprehensive pathology evaluation.
Methods: In this retrospective study, 52 patients underwent cervical spine MRI using ZTE, ZTE-DL, and T2-weighted 3D sequences on a 1.5-Tesla scanner.
A Comparison of Different Machine Learning Classifiers in Predicting Xerostomia and Sticky Saliva due to Head and Neck Radiotherapy using a Multi-objective, Multimodal Radiomics Model.
Biomed Phys Eng Express
January 2025
Radiation Oncology, Emory University, Emory Midtown Hospital, Atlanta, Georgia, 30322, UNITED STATES.
Although radiotherapy techniques are the primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity, and side effect. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on features extracted from pre-treatment imaging data. This study aims to compare different models in predicting radiation-induced xerostomia and sticky saliva in both early and late stage of HNC patients using CT and MRI image features along with demographics and dosimetric information.
View Article and Find Full Text PDFArtificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.
Int J Gynecol Cancer
January 2025
Institute of Image-Guided Surgery, IHU Strasbourg, France; University of Strasbourg, ICube, Laboratory of Engineering, Computer Science and Imaging, Department of Robotics, Imaging, Teledetection and Healthcare Technologies, CNRS, UMR, Strasbourg, France.
Objective: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optimal treatment planning and prognosis assessment. This study proposes a deep learning pipeline for tumor and uterus segmentation from magnetic resonance imaging (MRI) images to predict deep myometrial invasion and cervical stroma invasion and thus assist clinicians in pre-operative workups.
Methods: Two experts consensually reviewed the MRIs and assessed myometrial invasion and cervical stromal invasion as per the International Federation of Gynecology and Obstetrics staging classification, to compare the diagnostic performance of the model with the radiologic consensus.
A Rare Case of Bilateral Foot Drop Following Cervical Decompression in Tandem Spinal Stenosis.
Cureus
December 2024
Orthopaedic Surgery, Ng Teng Fong General Hospital, Singapore, SGP.
This case report describes a 70-year-old male presenting with limb weakness, urinary retention and tandem cervical and lumbar spinal stenosis with complicating white cord syndrome, a rare reperfusion injury post decompression surgery. Initially admitted following an unwitnessed fall, the patient's neurological examination indicated that progressive weakness of the limbs and sensory loss etiology is cervical and lumbar spondylosis with severe spinal canal stenosis, confirmed by imaging. Due to rapid deterioration, he underwent C5 corpectomy, cervical decompression and fusion.
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