Clinical Meaningfulness of an Algorithm-Based Service for Analyzing Treatment Response in Patients with Metastatic Cancer Using FDG PET/CT.

: Determining how a patient with metastatic cancer is responding to therapy can be difficult for medical oncologists, especially with text-only radiology reports. In this investigation, we assess the clinical usefulness of a new algorithm-based analysis that provides spatial location and quantification for each detected lesion region of interest (ROI) and compare it to information included in radiology reports in the United States. : Treatment response radiology reports for FDG PET/CT scans were retrospectively gathered from 228 patients with metastatic cancers.

Uncertainty quantification via localized gradients for deep learning-based medical image assessments.

Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indicate the reliability of these models are less established. Increasingly, uncertainty quantification (UQ) methods are being introduced to inform users on the reliability of model outputs.

Models using comprehensive, lesion-level, longitudinal [Ga]Ga-DOTA-TATE PET-derived features lead to superior outcome prediction in neuroendocrine tumor patients treated with [Lu]Lu-DOTA-TATE.

Purpose: Somatostatin receptor (SSTR) imaging features are predictive of treatment outcome for neuroendocrine tumor (NET) patients receiving peptide receptor radionuclide therapy (PRRT). However, comprehensive (all metastatic lesions), longitudinal (temporal variation), and lesion-level measured features have never been explored. Such features allow for capturing the heterogeneity in disease response to treatment.

Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network.

Purpose: Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is often subtle and difficult to detect. Our goal was to develop a longitudinally-aware segmentation network (LAS-Net) that can quantify serial PET/CT images for pediatric Hodgkin lymphoma patients.

Materials And Methods: This retrospective study included baseline (PET1) and interim (PET2) PET/CT images from 297 patients enrolled in two Children's Oncology Group clinical trials (AHOD1331 and AHOD0831).

An automated methodology for whole-body, multimodality tracking of individual cancer lesions.

. Manual analysis of individual cancer lesions to assess disease response is clinically impractical and requires automated lesion tracking methodologies. However, no methodology has been developed for whole-body individual lesion tracking, across an arbitrary number of scans, and acquired with various imaging modalities.

Evaluation of Data-Driven Rigid Motion Correction in Clinical Brain PET Imaging.

Head motion during brain PET imaging can significantly degrade the quality of the reconstructed image, leading to reduced diagnostic value and inaccurate quantitation. A fully data-driven motion correction approach was recently demonstrated to produce highly accurate motion estimates (<1 mm) with high temporal resolution (≥1 Hz), which can then be used for a motion-corrected reconstruction. This can be applied retrospectively with no impact on the clinical image acquisition protocol.

Image intensity histograms as imaging biomarkers: application to immune-related colitis.

To investigate image intensity histograms as a potential source of useful imaging biomarkers in both a clinical example of detecting immune-related colitis (irColitis) inF-FDG PET/CT images of immunotherapy patients and an idealized case of classifying digital reference objects (DRO).Retrospective analysis of bowelF-FDG uptake in N = 40 patients receiving immune checkpoint inhibitors was conducted. A CNN trained to segment the bowel was used to generate the histogram of bowelF-FDG uptake, and percentiles of the histogram were considered as potential metrics for detecting inflammation associated with irColitis.

Development and validation of a longitudinal soft-tissue metastatic lesion matching algorithm.

Metastatic cancer presents with many, sometimes hundreds of metastatic lesions through the body, which often respond heterogeneously to treatment. Therefore, lesion-level assessment is necessary for a complete understanding of disease response. Lesion-level assessment typically requires manual matching of corresponding lesions, which is a tedious, subjective, and error-prone task.

Initial Experience With Low-Dose 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging With Deep Learning Enhancement.

Objective: To demonstrate the utility of deep learning enhancement (DLE) to achieve diagnostic quality low-dose positron emission tomography (PET)/magnetic resonance (MR) imaging.

Methods: Twenty subjects with known Crohn disease underwent simultaneous PET/MR imaging after intravenous administration of approximately 185 MBq of 18F-fluorodeoxyglucose (FDG). Five image sets were generated: (1) standard-of-care (reference), (2) low-dose (ie, using 20% of PET counts), (3) DLE-enhanced low-dose using PET data as input, (4) DLE-enhanced low-dose using PET and MR data as input, and (5) DLE-enhanced using no PET data input.

Convolutional Neural Networks for Automated PET/CT Detection of Diseased Lymph Node Burden in Patients with Lymphoma.

Purpose: To automatically detect lymph nodes involved in lymphoma on fluorine 18 (F) fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs).

Materials And Methods: In this retrospective study, baseline disease of 90 patients with lymphoma was segmented on F-FDG PET/CT images (acquired between 2005 and 2011) by a nuclear medicine physician. An ensemble of three-dimensional patch-based, multiresolution pathway CNNs was trained using fivefold cross-validation.

Measuring Glucose Uptake in Primary Invasive Breast Cancer Using Simultaneous Time-of-Flight Breast PET/MRI: A Method Comparison Study with Prone PET/CT.

Purpose: To compare the measurement of glucose uptake in primary invasive breast cancer using simultaneous, time-of-flight breast PET/MRI with prone time-of-flight PET/CT.

Materials And Methods: In this prospective study, women with biopsy-proven invasive breast cancer undergoing preoperative breast MRI from 2016 to 2018 were eligible. Participants who had fasted underwent prone PET/CT of the breasts approximately 60 minutes after injection of 370 MBq (10 mCi) fluorine 18 fluorodeoxyglucose (F-FDG) followed by prone PET/MRI using standard clinical breast MRI sequences performed simultaneously with PET acquisition.

Comparison of 11 automated PET segmentation methods in lymphoma.

Segmentation of lymphoma lesions in FDG PET/CT images is critical in both assessing individual lesions and quantifying patient disease burden. Simple thresholding methods remain common despite the large heterogeneity in lymphoma lesion location, size, and contrast. Here, we assess 11 automated PET segmentation methods for their use in two scenarios: individual lesion segmentation and patient-level disease quantification in lymphoma.

Impact of Anatomic Location of Bone Metastases on Prognosis in Metastatic Castration-Resistant Prostate Cancer.

Background: Whole-body assessments of F-NaF positron emission tomography (PET)/computed tomography (CT) provide promising quantitative imaging biomarkers of metastatic castration-resistant prostate cancer (mCRPC). This study investigated whether the distribution of metastases across anatomic regions is prognostic of progression-free survival.

Patients And Methods: Fifty-four mCRPC patients with osseous metastases received baseline NaF PET/CT.

[I]CLR1404 PET/CT in High-Grade Primary and Metastatic Brain Tumors.

Purpose: There is a continuous search for imaging techniques with high sensitivity and specificity for brain tumors. Positron emission tomography (PET) imaging has shown promise, though many PET agents either have a low tumor specificity or impractical physical half-lives. [I]CLR1404 is a small molecule alkylphosphocholine analogue that is thought to bind to plasma membrane lipid rafts and has shown high tumor-to-background ratios (TBR) in a previous pilot study in brain tumor patients.

FLT PET/CT imaging of metastatic prostate cancer patients treated with pTVG-HP DNA vaccine and pembrolizumab.

Background: Immunotherapy has demonstrated remarkable success in treating different cancers. Nonetheless, a large number of patients do not respond, many respond without immediate changes detectable with conventional imaging, and many have unusual immune-related adverse events that cannot be predicted in advance. In this exploratory study, we investigate how 3'-Deoxy-3'-F-fluorothymidine (FLT) positron emission tomography (PET) measurements of tumor and immune cell proliferation might be utilized as biomarkers in immunotherapy.

Response-to-repeatability of quantitative imaging features for longitudinal response assessment.

Quantitative imaging biomarkers (QIBs) are often selected and ranked based on their repeatability performance. In the context of treatment response assessment, however, one must also consider how sensitive a QIB is to measuring changes in the tumour. This work introduces response-to-repeatability ratio (R/R), which weighs the ability of a QIB to detect significant changes with respect to its measurement repeatability and applies it to the case of PET texture features.

Automated classification of benign and malignant lesions in F-NaF PET/CT images using machine learning.

Purpose: F-NaF PET/CT imaging of bone metastases is confounded by tracer uptake in benign diseases, such as osteoarthritis. The goal of this work was to develop an automated bone lesion classification algorithm to classify lesions in NaF PET/CT images.

Methods: A nuclear medicine physician manually identified and classified 1751 bone lesions in NaF PET/CT images from 37 subjects with metastatic castrate-resistant prostate cancer, 14 of which (598 lesions) were analyzed by three additional physicians.

A statistically optimized regional thresholding method (SORT) for bone lesion detection in F-NaF PET/CT imaging.

Identification of individual lesions on F-NaF PET bone scans is a time-consuming and often subjective process that makes accurate characterization of disease burden challenging. Current automated methods either underestimate disease or struggle with high false positive rates. We developed a statistically optimized regional thresholding (SORT) method that optimizes detection of bone lesions.

Quantification of bone flare on F-NaF PET/CT in metastatic castration-resistant prostate cancer.

Background: Bone flare has been observed on Tc-MDP bone scans of patients with metastatic castration-resistant prostate cancer (mCRPC). This exploratory study investigates bone flare in mCRPC patients receiving androgen receptor (AR) inhibitors using F-NaF PET/CT.

Methods: Twenty-nine mCRPC patients undergoing AR-inhibiting therapy (abiraterone, orteronel, enzalutamide) received NaF PET/CT scans at baseline, week 6, and week 12 of treatment.

Dynamic F-FLT PET imaging of spatiotemporal changes in tumor cell proliferation and vasculature reveals the mechanistic actions of anti-angiogenic therapy.

Anti-angiogenic therapies target tumor vasculature and tumor cells, thus a concurrent assessment of these targets would lead to a greater understanding of therapeutic resistance and facilitate development of improved therapeutic strategies. We utilize dynamic 3'-deoxy-3'-F-fluorothymidine positron emission tomography (F-FLT PET) scanning to concurrently assess changes in tumor cell proliferation and vasculature during anti-angiogenic therapy, providing insight into how these therapies may be used effectively with combination chemotherapy. Thirty-three patients with advanced solid malignancies underwent treatment with vascular endothelial growth factor receptor inhibitor (VEGFR-TKI) axitinib on an intermittent schedule (two-weeks-on/one-week-off).

Pharmacodynamic study using FLT PET/CT in advanced solid malignancies treated with a sequential combination of X-82 and docetaxel.

Background: A sequential approach, synchronizing cell-cycle specific chemotherapy during VEGFR-TKI treatment breaks, may improve the therapeutic index of this combination therapy. In this study we investigate the safety/tolerability and pharmacodynamic effects of docetaxel used in sequential combination with the novel VEGFR-TKI X-82.

Methods: Patients with advanced solid malignancies underwent 21-day treatment cycles with X-82 administered daily on days 1-14, a treatment break on days 15-20, and docetaxel administered on day 21.

Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values.

Unlabelled: The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions.