A5044495249- Radiomics and Machine Learning in Medical Imaging
- Advanced Radiotherapy Techniques
- Head and Neck Cancer Studies
- Lung Cancer Diagnosis and Treatment
- Glioma Diagnosis and Treatment
- Endometrial and Cervical Cancer Treatments
- Prostate Cancer Diagnosis and Treatment
- Pituitary Gland Disorders and Treatments
- Advances in Oncology and Radiotherapy
- Medical Imaging Techniques and Applications
- Colorectal and Anal Carcinomas
- Neurofibromatosis and Schwannoma Cases
- Prostate Cancer Treatment and Research
- Meningioma and schwannoma management
- Neuroblastoma Research and Treatments
- Colorectal Cancer Surgical Treatments
- Head and Neck Surgical Oncology
- Ovarian cancer diagnosis and treatment
- Esophageal Cancer Research and Treatment
- Radiation Therapy and Dosimetry
- MRI in cancer diagnosis
- Management of metastatic bone disease
- Genetic factors in colorectal cancer
- Global Cancer Incidence and Screening
- Digital Radiography and Breast Imaging
The University of Texas MD Anderson Cancer Center
2018-2025
Anderson University - South Carolina
2020
Huntsman Cancer Institute
2019
University of Utah
2019
University of Pennsylvania
2014-2017
University of Cambridge
2016-2017
Addenbrooke's Hospital
2016-2017
Cancer Research UK
2016
Oropharyngeal cancer (OPC) primary gross tumor volume (GTVp) segmentation is crucial for radiotherapy. Multiparametric MRI (mpMRI) increasingly used OPC adaptive radiotherapy but relies on manual segmentation. Therefore, we constructed mpMRI deep learning (DL) GTVp auto-segmentation models and determined the impact of input channels performance.
Abstract Background Metastatic head and neck cancers (HNCs) predominantly affect the lungs have a two‐year overall survival (OS) of 15% to 50%, if amenable for pulmonary metastasectomy. Methods Retrospective review local control (LC), local‐regional (LRC) within same lobe, OS, toxicity rates in consecutive patients with metastatic HNC who underwent stereotactic ablative radiotherapy (SABR) January 2007 May 2018. Results Evaluated 82 107 lung lesions, most commonly squamous cell carcinoma...
Abstract Background Pathologic extranodal extension (pENE) is a crucial prognostic factor in oropharyngeal cancer (OPC), but determining pENE from imaging has high inter‐observer variability. The role of clinician specialty the accuracy imaging‐detected (iENE) remains unclear. purpose this study to assess influence on preoperative iENE detection human papillomavirus (HPV)‐positive OPC using computed tomography (CT) imaging. Methods This prospective observational evaluated pretherapy CT...
For locally advanced cervical cancer (LACC), anatomy correspondence with and without BT applicator needs to be quantified merge the delivered doses of external beam radiation therapy (EBRT) brachytherapy (BT). This study proposed evaluated different deformable image registration (DIR) methods for this application. Twenty patients who underwent EBRT LACC were retrospectively analyzed. Each patient had a pre-BT CT at boost (without applicator) MRI (with applicator). The DIR diffeomorphic...
The VoxTox research programme has applied expertise from the physical sciences to problem of radiotherapy toxicity, bringing together engineering, mathematics, high energy physics (including Large Hadron Collider), medical and radiation oncology. In our initial cohort 109 men treated with curative for prostate cancer, daily image guidance computed tomography (CT) scans have been used calculate delivered dose rectum, as distinct planned dose, using an automated approach. Clinical toxicity...
Background Financial toxicity (FT) reflects multi-dimensional personal economic hardships borne by cancer patients. It is unknown whether measures of FT—to date derived largely from English-speakers—adequately capture experiences and financial medically underserved low English proficiency US Hispanic We piloted a Spanish language FT instrument in this population. Methods version the Economic Strain Resilience Cancer (ENRICh) measure using qualitative cognitive interviews surveys...
A 54-year-old male presented with visual loss owing to a giant, infiltrative pituitary adenoma. Following decompressive trans-sphenoidal surgery, the patient was referred for adjuvant radiotherapy. We describe potential utility of 11carbon methionine positron emission tomography imaging in confirming true extent tumour infiltration, which included cavernous sinuses and bones skull base. The co-registration planning MR CT provided assurance complete radiotherapy coverage target volume...
OBJECTIVE Patients with metastatic thyroid cancer have prolonged survival compared to those other primary tumors. The spine is the most common site of osseous involvement in cases cancer. As a result, obtaining durable local control (LC) crucial. This study aimed evaluate efficacy stereotactic radiosurgery (SSRS) patients METHODS Information on treated SSRS for spinal metastases was retrospectively evaluated. delivered simultaneous integrated boost technique using single- or...
Abstract Purpose Segmentation of involved lymph nodes on head and neck computed tomography (HN-CT) scans is necessary for the radiotherapy treatment planning human papilloma virus (HPV) associated oropharynx cancers (OPC). We aimed to train a deep learning convolutional neural network (DL-CNN) identify segment contrast-enhanced HN-CT scans. Methods 90 patients who underwent levels II-IV dissection newly diagnosed, clinically node-positive, HPV-OPC were identified. Ground-truth segmentation...
Extranodal extension (pENE) is a critical prognostic factor in oropharyngeal cancer (OPC) that drives therapeutic disposition. Determination of pENE from radiological imaging has been associated with high inter-observer variability. However, the impact clinician specialty on human observer performance imaging-detected extranodal (iENE) remains poorly understood.
Abstract Background and Purpose Oropharyngeal cancer (OPC) primary gross tumor volume (GTVp) segmentation is crucial for radiotherapy. Multiparametric MRI (mpMRI) increasingly used OPC adaptive radiotherapy but relies on manual segmentation. Therefore, we constructed mpMRI deep learning (DL) GTVp auto-segmentation models determined the impact of input channels performance. Materials Methods ground truth segmentations were manually generated 30 patients from a clinical trial. We evaluated...