Human pancreatic cancer single cell atlas reveals association of CXCL10+ fibroblasts and basal subtype tumor cells.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) patients with tumors enriched for the basal-like molecular subtype exhibit enhanced resistance to standard of care treatments and have significantly worse overall survival (OS) compared to patients with classical subtype enriched tumors. It is important to develop genomic resources, enabling identification of novel putative targets in a statistically rigorous manner.

Experimental Design: We compiled a single cell RNA sequencing (scRNAseq) atlas of the human pancreas with 229 patient samples, aggregated from publicly available raw data.

Analysis pipeline to quantify uterine gland structural variations.

Background: Technical advances in whole tissue imaging and clearing have allowed 3D reconstruction of exocrine uterine glands deep-seated in the endometrium. However, there are limited gland structure analysis platforms to analyze these imaging data sets. Here, we present a pipeline for segmenting and analyzing uterine gland shape.

Near-pair patch generative adversarial network for data augmentation of focal pathology object detection models.

Purpose: The limited volume of medical training data remains one of the leading challenges for machine learning for diagnostic applications. Object detectors that identify and localize pathologies require training with a large volume of labeled images, which are often expensive and time-consuming to curate. To reduce this challenge, we present a method to support distant supervision of object detectors through generation of synthetic pathology-present labeled images.

High sensitivity methods for automated rib fracture detection in pediatric radiographs.

Rib fractures are highly predictive of non-accidental trauma in children under 3 years old. Rib fracture detection in pediatric radiographs is challenging because fractures can be obliquely oriented to the imaging detector, obfuscated by other structures, incomplete, and non-displaced. Prior studies have shown up to two-thirds of rib fractures may be missed during initial interpretation.

Machine-Learned Algorithms to Predict the Risk of Pneumothorax Requiring Chest Tube Placement after Lung Biopsy.

Purpose: To develop a machine-learned algorithm to predict the risk of postlung biopsy pneumothorax requiring chest tube placement (CTP) to facilitate preprocedural decision making, optimize patient care, and improve resource allocation.

Materials And Methods: This retrospective study collected clinical and imaging features of biopsy samples obtained from patients with lung nodule biopsy and included information from 59 procedures resulting in pneumothorax requiring CTP and randomly selected 67 procedures without CTP (convenience sample). The data were divided into 70 and 30 as training and testing sets, respectively.

Deep learning-enabled quantification of simultaneous PET/MRI for cell transplantation monitoring.

Current methods of imaging islet cell transplants for diabetes using magnetic resonance imaging (MRI) are limited by their low sensitivity. Simultaneous positron emission tomography (PET)/MRI has greater sensitivity and ability to visualize cell metabolism. However, this dual-modality tool currently faces two major challenges for monitoring cells.

Incorporating Tantalum Oxide Nanoparticles into Implantable Polymeric Biomedical Devices for Radiological Monitoring.

Longitudinal radiological monitoring of biomedical devices is increasingly important, driven by the risk of device failure following implantation. Polymeric devices are poorly visualized with clinical imaging, hampering efforts to use diagnostic imaging to predict failure and enable intervention. Introducing nanoparticle contrast agents into polymers is a potential method for creating radiopaque materials that can be monitored via computed tomography.

Incorporating Radiopacity into Implantable Polymeric Biomedical Devices for Clinical Radiological Monitoring.

Longitudinal radiological monitoring of biomedical devices is increasingly important, driven by risk of device failure following implantation. Polymeric devices are poorly visualized with clinical imaging, hampering efforts to use diagnostic imaging to predict failure and enable intervention. Introducing nanoparticle contrast agents into polymers is a potential method for creating radiopaque materials that can be monitored via computed tomography.

Phantom and methodology for comparison of small lesion detectability in PET.

Purpose: The main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.

Methods: We previously developed a small-lesion detection phantom and described initial results using a head-size phantom.

3D Magnetic Particle Imaging of Human Stem Cell-Derived Islet Organoid Transplantation Using a Machine Learning Algorithm.

Stem cell-derived islet organoids constitute a promising treatment of type 1 diabetes. A major hurdle in the field is the lack of appropriate method to determine graft outcome. Here, we investigate the feasibility of tracking of transplanted stem cell-derived islet organoids using magnetic particle imaging (MPI) in a mouse model.

Multi-Objective Evolutionary Algorithm for PET Image Reconstruction: Concept.

In many diagnostic imaging settings, including positron emission tomography (PET), images are typically used for multiple tasks such as detecting disease and quantifying disease. Unlike conventional image reconstruction that optimizes a single objective, this work proposes a multi-objective optimization algorithm for PET image reconstruction to identify a set of images that are optimal for more than one task. This work is reliant on a genetic algorithm to evolve a set of solutions that satisfies two distinct objectives.

Patient factors and outcomes associated with discordance between quantitative and qualitative cardiac PET ischemia information.

Background: Cardiac PET can provide quantitative myocardial blood flow (MBF) estimates. The frequency and clinical significance of discordant ischemia information between quantitative and qualitative parameters is unclear.

Methods: This retrospective, cohort study analyzed 256 Rb-82 stress-rest PET/CT studies.

SNMMI Procedure Standard/EANM Practice Guideline on Pediatric F-FDG PET/CT for Oncology 1.0.

PREAMBLEThe Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional nonprofit medical association founded in 1985 to facilitate communication worldwide among individuals pursuing clinical and academic excellence in nuclear medicine. SNMMI and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine.

Use of Dual-Energy CT for Quantification of Essential Trace Metals (Iron, Copper, and Zinc): Proof of Concept.

Altered concentrations of essential trace metals have been associated with the development of abdominal tumors. We developed a method to quantify trace metals (iron, copper, and zinc) using monochromatic data from commercially available dual-energy CT (DECT) implementations. Our data provide a foundation for the use of DECT for noninvasive quantification of essential trace metals.

Sharing and Selling Images: Ethical and Regulatory Considerations for Radiologists.

Opportunities to share or sell images are common in radiology. But because these images typically originate as protected health information, their use admits a host of ethical and regulatory considerations. This article discusses four scenarios that reflect data sharing or selling arrangements in radiology, especially as they might occur in "big data" systems or applications.

Correction to: Ovarian torsion: developing a machine-learned algorithm for diagnosis.

The original version of this paper included errors in Fig. 3. The corrected Fig.

Ovarian torsion: developing a machine-learned algorithm for diagnosis.

Background: Ovarian torsion is a common concern in girls presenting to emergency care with pelvic or abdominal pain. The diagnosis is challenging to make accurately and quickly, relying on a combination of physical exam, history and radiologic evaluation. Failure to establish the diagnosis in a timely fashion can result in irreversible ovarian ischemia with implications for future fertility.

Technical Note: A digital reference object representing Hoffman's 3D brain phantom for PET scanner simulations.

Purpose: Physical and digital phantoms play a key role in the development and testing of nuclear medicine instrumentation and processing algorithms for clinical and research applications, including neuroimaging using positron emission tomography (PET). We have developed and tested a digital reference object (DRO) version of the original segmented magnetic resonance imaging (MRI) data used for the three-dimensional (3D) PET brain phantom developed by Hoffman et al., which is used as the basis of a commercially available physical test phantom.

PET/CT-guided biopsy with respiratory motion correction.

Purpose: Given the ability of positron emission tomography (PET) imaging to localize malignancies in heterogeneous tumors and tumors that lack an X-ray computed tomography (CT) correlate, combined PET/CT-guided biopsy may improve the diagnostic yield of biopsies. However, PET and CT images are naturally susceptible to problems due to respiratory motion, leading to imprecise tumor localization and shape distortion. To facilitate PET/CT-guided needle biopsy, we developed and investigated the feasibility of a workflow that allows to bring PET image guidance into interventional CT suite while accounting for respiratory motion.

Accuracy of Myocardial Blood Flow Estimation From Dynamic Contrast-Enhanced Cardiac CT Compared With PET.

Background The accuracy of absolute myocardial blood flow (MBF) from dynamic contrast-enhanced cardiac computed tomography acquisitions has not been fully characterized. We evaluate computed tomography (CT) compared with rubidium-82 positron emission tomography (PET) MBF estimates in a high-risk population. Methods In a prospective trial, patients receiving clinically indicated rubidium-82 PET exams were recruited to receive a dynamic contrast-enhanced cardiac computed tomography exam.

Performance evaluation of the 5-Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2-2012 Standard.

Unlabelled: The GE Discovery MI PET/CT system has a modular digital detector design allowing three, four, or five detector block rings that extend the axial field-of-view (FOV) from 15 to 25 cm in 5 cm increments. This study investigated the performance of the 5-ring system and compared it to 3- and 4-ring systems; the GE Discovery IQ system that uses conventional photomultiplier tubes; and the GE Signa PET/MR system that has a reduced transaxial FOV.

Methods: PET performance was evaluated at three different institutions.

Comparison of Micro-Computed Tomography and Clinical Computed Tomography Protocols for Visualization of Nasal Cartilage Before Surgical Planning for Rhinoplasty.

Importance: There is no imaging standard to model nasal cartilage for the planning of rhinoplasty procedures. Preoperative visualization of cartilage may improve objective evaluation of nasal deformities, surgical planning, and surgical reconstruction.

Objectives: To evaluate the feasibility of visualizing nasal cartilage using high resolution micro-computed tomography (CT) compared with the criterion standard of pathologic findings in a cadaveric specimen and to evaluate its accuracy compared with various clinical CT protocols.

Patient body motion correction for dynamic cardiac PET-CT by attenuation-emission alignment according to projection consistency conditions.

Introduction: Patient body motion is known to cause large deviations in the determination of myocardial blood flow (MBF) with errors exceeding 300%. Accurate correction for patient whole-body motion is still a largely unsolved problem in cardiac positron emission tomography (PET) imaging.

Objective: This study evaluated the efficacy of using Natterer's formulation of the Helgason-Ludwig consistency conditions on the two-dimensional Radon transform to align computed tomography to PET projection data in multiple time frames of a dynamic sequence for the purpose of frame-by-frame correction of rigid whole-body motion.

Establishment of normative values for the fetal posterior fossa by magnetic resonance imaging.

Objective: Suspected Dandy-Walker continuum anomalies constitute a significant percentage of prenatal cases evaluated by magnetic resonance imaging (MRI). To unify the description of posterior fossa malformations, we sought to establish objective measurements for the posterior fossa in normal fetuses between 18 and 37 weeks gestation.

Methods: T2-weighted images of normal fetal brains in sagittal projection were obtained from fetal magnetic resonance (MR) studies of normal brains performed from 2009 to 2017.