Surrogating tumour cell density in head and neck cancer: [F]FDG PET- versus ADC (MRI)-based approaches.

Objective: In this study we examined the correlation between standardized uptake value (SUV) of [F]fluorodeoxyglucose (FDG) and apparent diffusion coefficient (ADC) within the gross tumor volume (GTV) of patients with head and neck squamous cell carcinoma (HNSCC). In addition, we assessed the comparability of cell density (ρ) estimates obtained from FDG PET and MRI data.

Methods: Twenty-one HNSCC patients from a prospective FMISO imaging trial underwent pre-treatment PET/CT and MRI.

Clinical Validation of Deep Learning for Image Restoration of Ultra-Low-Count [F]FDG PET for Dementia Diagnostics.

Deep learning (DL) represents a promising technique for image restoration. We explored its ability to restore ultra-low-count [F]FDG PET studies of the brain in subjects with dementia and in healthy subjects to allow for reduced scan durations or administered activities without compromising diagnostic performance. Various DL models using the content aware image restoration approach of CSBDeep toolbox (3D U-nets) were trained with subvolumes of 1,000 random subjects.

Divergent effects of age on imaging-based ATN biomarkers and cognition in Alzheimer's disease.

Introduction: We investigated whether age of patients with Alzheimer's disease (AD) at first visit to a memory clinic predicts biomarker findings along the amyloid beta deposition, pathologic tau, and neurodegeneration (ATN) scheme and moderates the association between ATN biomarkers and cognition.

Methods: We evaluated [C]Pittsburgh compound B positron emission tomography (PET), florzolotau (F) PET, [F]fluorodeoxyglucose PET, T1-weighted magnetic resonance imaging, and cognitive assessments ( = 190/63/252/687/2198) of a total of 2355 AD patients. We assessed direct and moderating effects of age.

The use of simulations to study the effect of acquisition schemes and quantification methods using positron emission tomography: an 18 F-Fallypride study.

Introduction: This computational study evaluates the accuracy of kinetic models and acquisition schemes in dynamic PET imaging using simulations of 18 F-fallypride PET in the human brain on the real-world data.

Methods: We employed a 2-tissue 4-k model to generate ideal tissue curves for three regions (putamen, thalamus, and temporal cortex) and a reference region (cerebellum), incorporating a simulated metabolite-corrected input function. Realistic measurements were simulated over a 240-min PET scan by defining acquisition protocols (frame timings and durations), modeling tracer decay, and adding noise.

Use of a Simulated Tumor Board to Teach Oncology and Multidisciplinary Collaboration to Pre-clinical Medical Students.

There is a need to teach interdisciplinary education in undergraduate medical education to encourage the fundamentals of teamwork and communication for enhanced patient outcomes. This report describes a novel interdisciplinary education session in the form of a simulated multidisciplinary oncology tumor board (TB) for pre-clinical medical students. Goals included the following: review of select pre-clinical lung cancer learning points, demonstration of diagnostic techniques relevant to the workup of lung cancer, and exposition of multidisciplinary and interprofessional teamwork.

Safety and quality of life of PSMA-PET- and MRI-based focal dose escalated radiotherapy for intermediate- and high-risk prostate cancer: Primary endpoint analysis of the bi-centric phase II HypoFocal trial (ARO2020-01).

Background And Purpose: To present the primary endpoint results, toxicities and quality of life (QoL) after two-year follow-up (FU) of the HypoFocal Phase II trial.

Material And Methods: Intermediate- and high-risk prostate cancer (PCa) patients were treated with moderately hypofractionated radiotherapy (MHRT) of 60 Gy in 20 fractions and a focal-boost of up to 75 Gy in Arm A, or high-dose-rate-brachytherapy (HDR-BT) of 15 Gy to the whole-gland with a boost of up to 19 Gy, followed by external beam RT (EBRT) of 44 Gy in 20 fractions in Arm B. Boost was based on combined information by multiparametric-magentic-resonance-tomography (mpMRI) and positron-emission-tomography targeting prostate-specific-membrane-antigen (PSMA-PET).

Open-source phantom with dedicated in-house software for image quality assurance in hybrid PET systems.

Background: Patients' diagnosis, treatment and follow-up increasingly rely on multimodality imaging. One of the main limitations for the optimal implementation of hybrid systems in clinical practice is the time and expertise required for applying standardized protocols for equipment quality assurance (QA). Experimental phantoms are commonly used for this purpose, but they are often limited to a single modality and single quality parameter, lacking automated analysis capabilities.

Can PSMA PET detect intratumour heterogeneity in histological PSMA expression of primary prostate cancer? Analysis of [Ga]Ga-PSMA-11 and [F]PSMA-1007.

Purpose: Prostate-specific membrane-antigen positron emission tomography (PSMA PET) is a promising candidate for non-invasive characterization of prostate cancer (PCa). This study evaluated whether PET with tracers [Ga]Ga-PSMA-11 or [F]PSMA-1007 is capable to depict intratumour heterogeneity of histological PSMA expression.

Methods: Thirty-five patients with biopsy-proven primary PCa without evidence of metastatic disease nor prior interventions were prospectively enrolled.

Repeat GammaTile Brachytherapy in the Long-Term Management of Recurrent High-Grade Glioma: A Case Report.

Over the past two decades, despite the emergence of various novel therapies for glioblastoma, patient survival outcomes remain poor, particularly in the recurrent stage of the disease. Cesium-131 (Cs-131) brachytherapy presents a promising treatment option for patients with newly diagnosed and recurrent brain neoplasms, enabling the initiation of radiation therapy at the time of tumor resection. This approach eliminates the typical delay in therapy following surgery and the need for multiple return visits for fractionated external beam radiotherapy.

Quality of life outcomes in patients participating in the CALGB 30610 trial (CALGB 70702): Alliance.

Background: CALGB 30610 trial demonstrated that once daily thoracic radiotherapy (TRT) was not superior compared to standard twice daily TRT, in patients with limited stage small cell lung cancer. Quality of life outcomes may help oncologists decide the best treatment approach.

Methods: A total of 417 patients on CALGB 30610 participated in the quality-of-life substudy (CALGB 70702), which included the FACT Trial Outcome Index-Lung Cancer (FACT-L TOI), FACT-Esophageal Cancer (FACT-E) Eating and Swallowing Indices, ECOG Acute Esophagitis Scale, Hospital Anxiety and Depression Scale (HADS), difficulty swallowing, EQ-5D, and treatment convenience assessment at baseline, 3, 5, 7, 12, 26, and 52 weeks after starting TRT.

Treatment of brain metastases from non-small cell lung cancer: preclinical, clinical, and translational research.

Lung cancer is the second most common type of cancer and is the leading cause of cancer-related deaths in the United States. Approximately 10-40% of patients with solid tumors develop brain metastases, with non-small cell lung cancer accounting for approximately 50% of all cases of patients with brain metastases. Many management options are available which can include surgery, radiation, and systemic therapy.

Prognostic Factors in Limited-Stage Small Cell Lung Cancer: A Secondary Analysis of CALGB 30610-RTOG 0538.

Importance: The impact of patient-specific, disease-related, and social factors on outcomes in limited-stage small cell lung cancer (LS-SCLC) is not well defined. A post hoc secondary analysis of such factors from the Cancer and Leukemia Group B (CALGB) 30610-Radiation Therapy Oncology Group (RTOG) 0538 trial may impact future trial design.

Objective: To assess the comprehensive demographic, disease-related, treatment-related, and social factors for potential associations with survival outcomes and understand whether specific subpopulations may benefit from radiotherapy (RT) dose escalation in LS-SCLC.

The impact of multicentric datasets for the automated tumor delineation in primary prostate cancer using convolutional neural networks on F-PSMA-1007 PET.

Purpose: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of radiation oncology, significantly advancing the precision of contouring practices. However, the adaptability of these algorithms across diverse scanners, institutions, and imaging protocols remains a considerable obstacle. This study aims to investigate the effects of incorporating institution-specific datasets into the training regimen of CNNs to assess their generalization ability in real-world clinical environments.

The significance of partial volume effect on the estimation of hypoxic tumour volume with [F]FMISO PET/CT.

Background: The purpose of this study was to evaluate how a retrospective correction of the partial volume effect (PVE) in [F]fluoromisonidazole (FMISO) PET imaging, affects the hypoxia discoverability within a gross tumour volume (GTV). This method is based on recovery coefficients (RC) and is tailored for low-contrast tracers such as FMISO. The first stage was the generation of the scanner's RC curves, using spheres with diameters from 10 to 37 mm, and the same homogeneous activity concentration, positioned in lower activity concentration background.

Development and evaluation of two open-source nnU-Net models for automatic segmentation of lung tumors on PET and CT images with and without respiratory motion compensation.

Objectives: In lung cancer, one of the main limitations for the optimal integration of the biological and anatomical information derived from Positron Emission Tomography (PET) and Computed Tomography (CT) is the time and expertise required for the evaluation of the different respiratory phases. In this study, we present two open-source models able to automatically segment lung tumors on PET and CT, with and without motion compensation.

Materials And Methods: This study involved time-bin gated (4D) and non-gated (3D) PET/CT images from two prospective lung cancer cohorts (Trials 108237 and 108472) and one retrospective.

Single-Time-Point Renal Dosimetry Using Nonlinear Mixed-Effects Modeling and Population-Based Model Selection in [Lu]Lu-PSMA-617 Therapy.

The aim of this study was to investigate the accuracy of single-time-point (STP) renal dosimetry imaging using SPECT/CT data, a nonlinear mixed-effects (NLME) model, and a population-based model selection (PBMS) in a large population for Lu-labeled prostate-specific membrane antigen therapy. Biokinetic data (mean ± SD) of [Lu]Lu-PSMA-617 in kidneys at time points 1 (1.8 ± 0.

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

Purpose: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa), accurate delineation of gross tumor volume (GTV) in prostate-specific membrane antigen PET (PSMA-PET) becomes crucial. Manual approaches are time-consuming and observer dependent. The purpose of this study was to create a deep learning model for the accurate delineation of the intraprostatic GTV in PSMA-PET.