Publications by authors named "Jonathan R Dillman"

Quantitative abdominal magnetic resonance imaging (MRI) offers non-invasive, objective assessment of diseases in the liver, pancreas, and other organs and is increasingly being used in the pediatric population. Certain quantitative MRI techniques, such as liver proton density fat fraction (PDFF), R2* mapping, and MR elastography, are already in wide clinical use. Other techniques, such as liver T1 mapping and pancreas quantitative imaging methods, are emerging and show promise for enhancing diagnostic sensitivity and treatment monitoring.

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To develop and validate a modality-invariant Swin U-Net Transformer (UNETR) deep learning model for liver and spleen segmentation on abdominal T1-weighted (T1w) or T2-weighted (T2w) MR images from multiple institutions for pediatric and adult patients with known or suspected chronic liver diseases. In this IRB-approved retrospective study, clinical abdominal axial T1w and T2w MR images from pediatric and adult patients were retrieved from four study sites, including Cincinnati Children's Hospital Medical Center (CCHMC), New York University (NYU), University of Wisconsin (UW) and University of Michigan / Michigan Medicine (UM). The whole liver and spleen were manually delineated as the ground truth masks.

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Background: Understanding distribution of published pediatric imaging research in radiology journals is relevant to understanding the state of research in the field.

Objective: To understand the current state of published original pediatric imaging research in major clinical radiology journals other than Pediatric Radiology.

Materials And Methods: We reviewed clinical imaging journals from among the top 20 radiology journals according to the Google Scholar h5-index as of June 2024.

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Objectives: To inform clinical monitoring of children and young adults with metabolic dysfunction-associated steatotic liver disease (MASLD) by characterizing the real-world natural history of MASLD and identifying baseline predictors of liver disease progression.

Materials And Methods: This retrospective study included consecutive patients ages < 23 years with MASLD who underwent serial MR elastography (MRE) and/or MR fat fraction (FF) examinations between 09/2009 and 11/2022. Outcomes of MASLD were defined based on maximum ratio values.

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Article Synopsis
  • * In a retrospective analysis of 73 pediatric patients (ages 4-20), both CAD systems, FlyerScan and MONAI, were assessed for detecting lung nodules of varying sizes; results showed a decline in sensitivity for low-dose scans.
  • * Specifically, FlyerScan had sensitivities of 76.9% for standard-dose and 66.8% for low-dose, while MONAI had 67.6% and 62.3% respectively, indicating a notable decrease in performance on low-dose scans
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The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising outcomes in discerning phenotypic characteristics and enhancing disease diagnosis. The development of such a technique hinges on the efficient fusion of heterogeneous multimodal features, which initially reside within distinct representation spaces. Naively fusing the multimodal features does not adequately capture the complementary information and could even produce redundancy.

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Background: Radiologic ulcers are increasingly recognized as an imaging finding of bowel wall active inflammation in Crohn disease (CD).

Objective: To determine the frequency of ulcers at MR enterography (MRE) in children with newly diagnosed ileal CD, assess agreement between radiologists, and evaluate if their presence correlates with other imaging and clinical features of intestinal active inflammation.

Materials And Methods: This retrospective study included 108 consecutive pediatric patients (ages 6-18 years) with newly diagnosed ileal CD that underwent clinical MRE prior to treatment initiation between January 2021 and December 2022.

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  • The study aimed to examine how various stress maneuvers affect liver stiffness measurements (LSMs) in patients with Fontan circulation compared to healthy individuals.
  • Ten post-Fontan patients and ten healthy controls underwent ultrasound measurements at baseline and after performing various maneuvers like exercise and fluid administration.
  • Results showed that post-Fontan patients had higher LSMs at baseline and during all maneuvers compared to controls, but diuresis significantly reduced liver stiffness in both groups, with a stronger effect noted in Fontan patients.
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Article Synopsis
  • - ComBat harmonization is a technique used to eliminate non-biological variations in multi-center research, particularly important when applying artificial intelligence to medical imaging data from different sources.
  • - A study analyzed radiomic and deep learning features from T2-weighted abdominal MRI scans of patients with suspected chronic liver disease, collected from three different manufacturers and field strengths.
  • - Results showed that before ComBat, there were significant differences in features based on manufacturer and field strength, but post-harmonization, these differences were eliminated, indicating that ComBat is effective in standardizing multi-center MRI data.
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Background: Quantitative parametric mapping is an increasingly important tool for noninvasive assessment of chronic liver disease. Conventional parametric mapping techniques require multiple breath-held acquisitions and provide limited anatomic coverage.

Purpose: To investigate a multi-inversion spin and gradient echo (MI-SAGE) technique for simultaneous estimation of T, T, and T* of the liver.

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Objective: This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (DL)-based reconstruction techniques on MRI radiomic features compared to conventional image reconstruction techniques.

Methods: Under IRB approval and informed consent, we prospectively collected undersampled coronal T2-weighted MR images of the abdomen (1.5 T; Philips Healthcare) from 17 pediatric and adult subjects and reconstructed them using a conventional image reconstruction technique (compressed sensitivity encoding [C-SENSE]) and two DL-based reconstruction techniques (SmartSpeed [Philips Healthcare, US FDA cleared] and SmartSpeed with Super Resolution [SmartSpeed-SuperRes, not US FDA cleared to date]).

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Crohn's disease (CD) is a chronic inflammatory condition that affects the gastrointestinal tract, particularly the ileum and colon. This disease is characterized by recurrent bouts of intestinal inflammation with subsequent bowel wall damage, including scarring (i.e.

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Utilization of magnetic resonance imaging (MRI) in the pediatric emergency room or urgent care setting for abdominopelvic indications has been increasing. The creation and implementation of rapid urgent MRI programs can have various challenges. The purpose of this article is to describe a framework for the creation of a rapid urgent abdominopelvic MRI program in the pediatric emergency room setting.

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Article Synopsis
  • Body magnetic resonance imaging (MRI) helps doctors find and monitor diseases in kids without using harmful radiation.
  • MRI gives clearer pictures of soft tissues and can measure things accurately, which is super helpful for diagnosis.
  • In the future, MRI for kids will get even better with faster techniques, special focus exams, and the use of artificial intelligence to improve results.
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Purpose: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction.

Materials And Methods: This prospective, IRB-approved study enrolled 50 pediatric patients (mean age = 11.8 ± 3.

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Background: Artificial intelligence (AI) reconstruction techniques have the potential to improve image quality and decrease imaging time. However, these techniques must be assessed for safe and effective use in clinical practice.

Objective: To assess image quality and diagnostic confidence of AI reconstruction in the pediatric brain on fluid-attenuated inversion recovery (FLAIR) imaging.

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Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms.

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Background: Despite advances in medical therapy, many children and adults with ileal Crohn's disease (CD) progress to fibrostenosis requiring surgery. We aimed to identify MRI and circulating biomarkers associated with the need for surgical management.

Methods: This prospective, multicenter study included pediatric and adult CD cases undergoing ileal resection and CD controls receiving medical therapy.

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Background: MRI diffusion-weighted imaging (DWI) is commonly used in MR enterography protocols for assessment of intestinal inflammation in patients with Crohn's disease. The intravoxel incoherent motion (IVIM) approach to DWI has been proposed as a more objective approach, providing quantitative parameters that reflect water diffusivity (D), blood flow (D*), and perfusion fraction (f).

Purpose: We aimed to determine if DWI-IVIM metrics from the terminal ileum in patients with newly diagnosed Crohn's disease differ from healthy participants and change in response to biologic medical therapy.

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Article Synopsis
  • This article focuses on developing deep learning models for segmenting liver, spleen, and pancreas in pediatric CT scans, addressing the lack of research in this area compared to adult cases.
  • The study leveraged 1,731 CT examinations, utilizing both institutional data and public datasets, and applied three different deep learning architectures while comparing them with a publicly available model, TotalSegmentator.
  • Results showed strong segmentation performance across both internal and public datasets, with variations in accuracy depending on the organ and model used, highlighting the effectiveness of transfer learning in enhancing model performance.
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Purpose: (1) To determine the frequency of surgical management in children with Crohn's Disease (CD) and a new radiologic ileal stricture, and (2) to identify imaging and clinical features that predict the need for surgery.

Methods: This retrospective study included pediatric patients (< 21 years old) with CD and a new ileal stricture diagnosed by MRE, CTE, or CT between July 2018 and June 2023. Three board-certified radiologists recorded stricture length, maximum mural thickness, minimum lumen diameter, maximum upstream diameter, and simplified magnetic resonance index of activity (sMaRIA) score.

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Liver fibrosis is an important clinical endpoint of the progression of autoimmune liver disease (AILD); its monitoring would benefit from noninvasive imaging tools. The purpose of this study was to assess the relationship between MR elastography (MRE) liver stiffness measurements and histologic liver fibrosis, as well as to evaluate the performance of MRE and biochemical-based clinical markers for stratifying histologic liver fibrosis severity, in children and young adults with AILD. This retrospective study used an existing institutional registry of children and young adults diagnosed with AILD (primary sclerosing cholangitis [PSC], autoimmune sclerosing cholangitis [ASC], or autoimmune hepatitis [AIH]).

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Liver congestion is increasingly encountered in clinical practice and presents diagnostic pitfalls of which radiologists must be aware. The complex altered hemodynamics associated with liver congestion leads to diffuse parenchymal changes and the development of benign and malignant nodules. Distinguishing commonly encountered benign hypervascular lesions, such as focal nodular hyperplasia (FNH)-like nodules, from hepatocellular carcinoma (HCC) can be challenging due to overlapping imaging features.

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