A5005999785- Advanced Radiotherapy Techniques
- Lung Cancer Diagnosis and Treatment
- Medical Imaging Techniques and Applications
- Prostate Cancer Diagnosis and Treatment
- Lung Cancer Treatments and Mutations
- Radiomics and Machine Learning in Medical Imaging
- Prostate Cancer Treatment and Research
- Breast Cancer Treatment Studies
- Radiation Therapy and Dosimetry
- Stellar, planetary, and galactic studies
- Lung Cancer Research Studies
- Astronomy and Astrophysical Research
- Brain Metastases and Treatment
- Hepatocellular Carcinoma Treatment and Prognosis
- Endometrial and Cervical Cancer Treatments
- Radiopharmaceutical Chemistry and Applications
- Astrophysics and Star Formation Studies
- Management of metastatic bone disease
- Pancreatic and Hepatic Oncology Research
- Cancer Genomics and Diagnostics
- Advanced X-ray and CT Imaging
- Radiation Dose and Imaging
- Gastric Cancer Management and Outcomes
- Colorectal and Anal Carcinomas
- Advances in Oncology and Radiotherapy
Università Campus Bio-Medico
2015-2025
Champalimaud Foundation
2013-2025
Campus Bio Medico University Hospital
2016-2025
Human Genome Sciences (United States)
2023
Azienda Ospedaliera Universitaria Integrata Verona
2020
Istituti di Ricovero e Cura a Carattere Scientifico
2005-2019
Integrated Oncology (United States)
2018-2019
Radiotherapie Groep
2019
Hospital Universitario La Paz
2017
Università Cattolica del Sacro Cuore
2007-2016
A new entity of patients with recurrent prostate cancer limited to a small number active metastatic lesions is having growing interest: the oligometastatic patients. Patients disease could eventually be managed by treating all local therapy, i.e. either surgery or ablative stereotactic body radiotherapy. This study aims assess impact [(18)F]Choline ([(18)F]FMCH) PET/CT and use radiotherapy (SBRT) in (pts) (PCa).Twenty-nine pts PCa (≤3 synchronous detected [(18)F]FMCHPET/CT) were treated...
•Improvement of therapeutic ratio by novel unconventional radiotherapy approaches.•Immunomodulation using high-dose spatially fractionated radiotherapy.•Boosting radiation anti-tumor effects adding an immune-mediated cell killing.
The primary goal of precision medicine is to minimize side effects and optimize efficacy treatments. Recent advances in medical imaging technology allow the use more advanced image analysis methods beyond simple measurements tumor size or radiotracer uptake metrics. extraction quantitative features from images characterize pathology heterogeneity an interesting process investigate, order provide information that may be useful guide therapies predict survival. This paper discusses rationale...
Tumor cure with conventional fractionated radiotherapy is 65%, dependent on tumor cell-autonomous gradual buildup of DNA double-strand break (DSB) misrepair. Here we report that single-dose (SDRT), a disruptive technique ablates more than 90% human cancers, operates distinct dual-target mechanism, linking acid sphingomyelinase-mediated (ASMase-mediated) microvascular perfusion defects to unrepair in cells confer cell lethality. ASMase-mediated microcirculatory vasoconstriction after SDRT...
Oncogenes are important regulators of cancer growth and progression their action may be modulated by proteins the factor family, such as angiogenic cytokines, known to strongly involved in neoplastic evolution. Reciprocal interactions between oncogenes modulators represent, haematological neoplasms, including multiple myeloma (MM), a possible mechanism drug resistance. The aim this work is investigate vitro vivo whether or not c-myc deregulation melphalan resistance elicited patients...
Purpose: The need for an accurate lesion segmentation tool in PET is a prerequisite the estimation of response to therapy, radionuclide dosimetry, and application radiotherapy planning. In this work, authors have developed iterative method based on mathematical fit deduced from Monte Carlo simulations estimate tumor thresholds. Methods: GATE software, GEANT4 tool, was used model GE Advance scanner geometry. Spheres ranging between 1 diameters were simulated high diameter cylinder. spheres...
Abstract The automated processing of Electronic Health Records (EHRs) poses a significant challenge due to their unstructured nature, rich in valuable, yet disorganized information. Natural Language Processing (NLP), particularly Named Entity Recognition (NER), has been instrumental extracting structured information from EHR data. However, existing literature primarly focuses on handcrafted clinical features through NLP and NER methods without delving into learned representations. In this...