Publications by authors named "Josef A Buchner"
Background And Purpose: This study investigates the use of Vision Transformers (ViTs) to predict Freedom from Local Failure (FFLF) in patients with brain metastases using pre-operative MRI scans. The goal is to develop a model that enhances risk stratification and informs personalized treatment strategies.
Materials And Methods: Within the AURORA retrospective trial, patients (n = 352) who received surgical resection followed by post-operative stereotactic radiotherapy (SRT) were collected from seven hospitals.
Article Synopsis
- A subgroup of patients with oligometastatic cancer may benefit from local treatment of all cancer lesions to achieve longer disease-free survival, especially when brain metastases are involved.
- An analysis of 7,000 PET scans identified 106 patients with both extracranial oligometastases and brain metastases, finding that brain involvement significantly impacted disease classification and treatment outcomes.
- Patients with oligometastasic disease had a median survival of 28 months compared to 10 months for polymetastatic patients, suggesting that brain metastases should not automatically exclude individuals from clinical trials.
Article Synopsis
- - The article discusses the increasing role of artificial intelligence (AI) in radiation oncology, specifically its application in patient care and radiotherapy planning.
- - It reviews AI techniques for automating the segmentation of important areas like organs at risk (OARs) and tumor volumes, highlighting improved efficiency and consistency in treatment planning.
- - Despite challenges in applying these tools clinically, the potential for personalized treatment plans and advancements in tumor detection presents a promising future for faster and more precise radiotherapy.
Article Synopsis
- Surgical resection is the primary treatment for patients with large or symptomatic brain metastases, but there's still a risk of local failure, prompting the development of a prediction tool to identify those at high risk.
- Data from the AURORA study included 253 patients for training and 99 for external testing, utilizing radiomic features from MRI scans to enhance prediction accuracy.
- The elastic net regression model combining radiomic and clinical features showed a significant improvement in predicting local failure, with lower risk groups experiencing only 9% failure at 24 months compared to 74% in high-risk groups, suggesting potential for improved patient follow-up and treatment.
Article Synopsis
- The study focuses on improving treatment for glioblastoma, a challenging brain cancer, by validating a new computational tumor growth model for personalized therapy.
- Researchers analyzed data from 124 TCGA patients and 397 UCSF patients to find links between clinical outcomes and factors related to tumor growth and genetics.
- Results indicate that certain growth parameters are significantly linked to patient survival and that the model may enhance radiation treatment planning without increasing radiation exposure.
Identifying core MRI sequences for reliable automatic brain metastasis segmentation.
Radiother Oncol
November 2023
Background: Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation.
Methods: We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers.
Background: Stereotactic radiotherapy is a standard treatment option for patients with brain metastases. The planning target volume is based on gross tumor volume (GTV) segmentation. The aim of this work is to develop and validate a neural network for automatic GTV segmentation to accelerate clinical daily routine practice and minimize interobserver variability.
View Article and Find Full Text PDFPurpose: This study aims to evaluate the association of the maximum standardized uptake value (SUVmax) in positron-emission tomography targeting prostate-specific membrane antigen (PSMA-PET) prior to salvage radiotherapy (sRT) on biochemical recurrence free survival (BRFS) in a large multicenter cohort.
Methods: Patients who underwent Ga-PSMA11-PET prior to sRT were enrolled in four high-volume centers in this retrospective multicenter study. Only patients with PET-positive local recurrence (LR) and/or nodal recurrence (NR) within the pelvis were included.