Evaluation of early metabolic changes following vorasidenib using FET PET in patients with -mutant gliomas.

The phase-3 INDIGO trial demonstrated that the isocitrate dehydrogenase () inhibitor vorasidenib significantly prolonged progression-free survival and delayed intervention in patients with CNS WHO grade 2 gliomas. However, conventional MRI showed limited response, with only 11% of patients having objective responses. Studies suggest that serial PET imaging with radiolabeled amino acids, such as -(2-[ F]-fluoroethyl)-L-tyrosine (FET) PET, may provide earlier and more informative assessments of treatment response than MRI.

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements.

The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.

Multicentric Ga-PSMA PET radiomics for treatment response assessment of Lu-PSMA-617 radioligand therapy in patients with metastatic castration-resistant prostate cancer.

Objective: The treatment with Lutetium PSMA (Lu-PSMA) in patients with metastatic castration-resistant prostate cancer (mCRPC) has recently been approved by the FDA and EMA. Since treatment success is highly variable between patients, the prediction of treatment response and identification of short- and long-term survivors after treatment could help tailor mCRPC diagnosis and treatment accordingly. The aim of this study is to investigate the value of radiomic parameters extracted from pretreatment Ga-PSMA PET images for the prediction of treatment response.

Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

Objectives: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation.

Materials And Methods: The consensus was achieved by a multi-stage process.

MRI and F-FET PET for Multimodal Treatment Monitoring in Patients with Brain Metastases: A Cost-Effectiveness Analysis.

PET using the radiolabeled amino acid -(2-[F]fluoroethyl)-l-tyrosine (F-FET) has been shown to be of value for treatment monitoring in patients with brain metastases after multimodal therapy, especially in clinical situations with equivocal MRI findings. As medical procedures must be justified socioeconomically, we determined the effectiveness and cost-effectiveness of F-FET PET for treatment monitoring of multimodal therapy, including checkpoint inhibitors, targeted therapies, radiotherapy, and combinations thereof in patients with brain metastases secondary to melanoma or non-small cell lung cancer. We analyzed already-published clinical data and calculated the associated costs from the German statutory health insurance system perspective.

Impact of improved dead time correction on the quantification accuracy of a dedicated BrainPET scanner.

Objective: Quantitative values derived from PET brain images are of high interest for neuroscientific applications. Insufficient DT correction (DTC) can lead to a systematic bias of the output parameters obtained by a detailed analysis of the time activity curves (TACs). The DTC method currently used for the Siemens 3T MR BrainPET insert is global, i.

Treatment-associated imaging changes in newly diagnosed MGMT promoter-methylated glioblastoma undergoing chemoradiation with or without cilengitide.

Background: Radiological progression may originate from progressive disease (PD) or pseudoprogression/treatment-associated changes. We assessed radiological progression in O6-methylguanine-DNA methyltransferase (MGMT) promoter-methylated glioblastoma treated with standard-of-care chemoradiotherapy with or without the integrin inhibitor cilengitide according to the modified response assessment in neuro-oncology (RANO) criteria of 2017.

Methods: Patients with ≥ 3 follow-up MRIs were included.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients.

Background: In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks.

Methods: The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy.

Clinical Applications of Radiomics in Nuclear Medicine.

Radiomics is an emerging field of artificial intelligence that focuses on the extraction and analysis of quantitative features such as intensity, shape, texture and spatial relationships from medical images. These features, often imperceptible to the human eye, can reveal complex patterns and biological insights. They can also be combined with clinical data to create predictive models using machine learning to improve disease characterization in nuclear medicine.

Assessment of Brain Tumour Perfusion Using Early-Phase F-FET PET: Comparison with Perfusion-Weighted MRI.

Purpose: Morphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-F-fluoroethyl)-L-tyrosine (F-FET).

The Medical Informatics Initiative and the Network University Medicine - Perspectives for Nuclear Medicine.

Digitization in the healthcare sector and the support of clinical workflows with artificial intelligence (AI), including AI-supported image analysis, represent a great challenge and equally a promising perspective for preclinical and clinical nuclear medicine. In Germany, the Medical Informatics Initiative (MII) and the Network University Medicine (NUM) are of central importance for this transformation. This review article outlines these structures and highlights their future role in enabling privacy-preserving federated multi-center analyses with interoperable data structures harmonized between site-specific IT infrastructures.

Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET.

Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas.

Hybrid PET/MRI in Cerebral Glioma: Current Status and Perspectives.

Advanced MRI methods and PET using radiolabelled amino acids provide valuable information, in addition to conventional MR imaging, for brain tumour diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumour progression from treatment-related changes, and the early assessment of responses to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing, and has been addressed in numerous studies.

The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms.

Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer.

Background: The expression level of the programmed cell death ligand 1 (PD-L1) appears to be a predictor for response to immunotherapy using checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). As differences in terms of PD-L1 expression levels in the extracranial primary tumor and the brain metastases may occur, a reliable method for the non-invasive assessment of the intracranial PD-L1 expression is, therefore of clinical value. Here, we evaluated the potential of radiomics for a non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to NSCLC.

Advances in PET imaging for meningioma patients.

In patients with meningioma, diagnosis and treatment planning are predominantly based on anatomical imaging using MRI or CT. Constraints of these imaging modalities include precise meningioma delineation-especially at the skull base, in the case of -osseus growth, and in tumors with complex geometry-and the differentiation of post-therapeutic reactive changes from meningioma relapse. Advanced metabolic imaging using PET may help to characterize specific metabolic and cellular features providing additional information beyond the information derived from anatomical imaging alone.

Amino Acid PET in Neurooncology.

For decades, several amino acid PET tracers have been used to optimize diagnostics in patients with brain tumors. In clinical routine, the most important clinical indications for amino acid PET in brain tumor patients are differentiation of neoplasm from nonneoplastic etiologies, delineation of tumor extent for further diagnostic and treatment planning (i.e.