Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI.

RATIONALE AND OBJECTIVES: To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPAIR fat saturation achieving a 50 % reduction in breath-hold duration (hereafter, VIBE-SPAIRDL) in terms of image quality and diagnostic confidence. MATERIALS AND METHODS: This prospective study enrolled consecutive patients referred for upper abdominal MRI from November 2023 to December 2023 at a single tertiary center. Patients underwent upper abdominal MRI with acquisition of non-contrast and gadobutrol-enhanced conventional VIBE-SPAIR (fourfold acceleration, acquisition time 16 s) and VIBE-SPAIRDL (sixfold acceleration, acquisition time 8 s) on a 1.5 T scanner. Image analysis was performed by four readers, evaluating homogeneity of fat suppression, perceived signal-to-noise ratio (SNR), edge sharpness, artifact level, lesion detectability and diagnostic confidence. A statistical power analysis for patient sample size estimation was performed. Image quality parameters were compared by a repeated measures analysis of variance, and interreader agreement was assessed using Fleiss' κ. RESULTS: Among 450 consecutive patients, 45 patients were evaluated (mean age, 60 years ± 15 [SD]; 27 men, 18 women). VIBE-SPAIRDL acquisition demonstrated superior SNR (P < 0.001), edge sharpness (P < 0.001), and reduced artifacts (P < 0.001) with substantial to almost perfect interreader agreement for non-contrast (κ: 0.70-0.91) and gadobutrol-enhanced MRI (κ: 0.68-0.87). No evidence of a difference was found between conventional VIBE-SPAIR and VIBE-SPAIRDL regarding homogeneity of fat suppression, lesion detectability, or diagnostic confidence (all P > 0.05). CONCLUSION: Deep learning reconstruction of VIBE-SPAIR facilitated a reduction of breath-hold duration by half, while reducing artifacts and improving image quality. SUMMARY: Deep learning reconstruction of prospectively accelerated T1 volumetric interpolated breath-hold examination for upper abdominal MRI enabled a 50 % reduction in breath-hold time with superior image quality. KEY RESULTS: 1) In a prospective analysis of 45 patients referred for upper abdominal MRI, accelerated deep learning (DL)-reconstructed VIBE images with spectral fat saturation (SPAIR) showed better overall image quality, with better perceived signal-to-noise ratio and less artifacts (all P < 0.001), despite a 50 % reduction in acquisition time compared to conventional VIBE. 2) No evidence of a difference was found between conventional VIBE-SPAIR and accelerated VIBE-SPAIRDL regarding lesion detectability or diagnostic confidence.

Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression.

OBJECTIVE: Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerated MRI of the upper abdomen in the context of pancreatic pathologies are lacking. In a clinical setting, the purpose of this study is to investigate the performance of a novel DL-based reconstruction algorithm in T1-weighted volumetric interpolated breath-hold examinations with partial Fourier sampling and Dixon fat suppression (hereafter, VIBE-DixonDL). The objective is to analyze its impact on acquisition time, image sharpness and quality, diagnostic confidence, pancreatic lesion conspicuity, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). METHODS: This prospective single-center study included participants with various pancreatic pathologies who gave written consent from January 2023 to September 2023. During the same session, each participant underwent 2 MRI acquisitions using a 1.5 T scanner: conventional precontrast and postcontrast T1-weighted VIBE acquisitions with Dixon fat suppression (VIBE-Dixon, reference standard) using 4-fold parallel imaging acceleration and 6-fold accelerated VIBE-Dixon acquisitions with partial Fourier sampling utilizing a novel DL reconstruction tailored to the acquisition. A qualitative image analysis was performed by 4 readers. Acquisition time, image sharpness, overall image quality, image noise and artifacts, diagnostic confidence, as well as pancreatic lesion conspicuity and size were compared. Furthermore, a quantitative analysis of SNR and CNR was performed. RESULTS: Thirty-two participants were evaluated (mean age ± SD, 62 ± 19 years; 20 men). The VIBE-DixonDL method enabled up to 52% reduction in average breath-hold time (7 seconds for VIBE-DixonDL vs 15 seconds for VIBE-Dixon, P < 0.001). A significant improvement of image sharpness, overall image quality, diagnostic confidence, and pancreatic lesion conspicuity was observed in the images recorded using VIBE-DixonDL (P < 0.001). Furthermore, a significant reduction of image noise and motion artifacts was noted in the images recorded using the VIBE-DixonDL technique (P < 0.001). In addition, for all readers, there was no evidence of a difference in lesion size measurement between VIBE-Dixon and VIBE-DixonDL. Interreader agreement between VIBE-Dixon and VIBE-DixonDL regarding lesion size was excellent (intraclass correlation coefficient, >90). Finally, a statistically significant increase of pancreatic SNR in VIBE-DIXONDL was observed in both the precontrast (P = 0.025) and postcontrast images (P < 0.001). Also, an increase of splenic SNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.34 and P = 0.003, respectively). Similarly, an increase of pancreas CNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.557 and P = 0.026, respectively). CONCLUSIONS: The prospectively accelerated, DL-enhanced VIBE with Dixon fat suppression was clinically feasible. It enabled a 52% reduction in breath-hold time and provided superior image quality, diagnostic confidence, and pancreatic lesion conspicuity. This technique might be especially useful for patients with limited breath-hold capacity.

Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers.

Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management.

Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses.

ABSTRACT: Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.

Imaging of Neuroendocrine Neoplasms; Principles of Treatment Strategies. What Referring Clinicians Want to Know.

ABSTRACT: Neuroendocrine neoplasms (NENs) are a diverse group of tumors that express neuroendocrine markers and primarily affect the lungs and digestive system. The incidence of NENs has increased over time due to advancements in imaging and diagnostic techniques. Effective management of NENs requires a multidisciplinary approach, considering factors such as tumor location, grade, stage, symptoms, and imaging findings. Treatment strategies vary depending on the specific subtype of NEN. In this review, we will focus on treatment strategies and therapies including the information relevant to clinicians in order to undertake optimal management and treatment decisions, the implications of different therapies on imaging, and how to ascertain their possible complications and treatment effects.

Clinical Intricacies and Advances in Neuroendocrine Tumors: An Organ-Based Multidisciplinary Approach.

ABSTRACT: Neuroendocrine neoplasms (NENs) are rare neoplasms originating from neuroendocrine cells, with increasing incidence due to enhanced detection methods. These tumors display considerable heterogeneity, necessitating diverse management strategies based on factors like organ of origin and tumor size. This article provides a comprehensive overview of therapeutic approaches for NENs, emphasizing the role of imaging in treatment decisions. It categorizes tumors based on their locations: gastric, duodenal, pancreatic, small bowel, colonic, rectal, appendiceal, gallbladder, prostate, lung, gynecological, and others. The piece also elucidates the challenges in managing metastatic disease and controversies surrounding MEN1-neuroendocrine tumor management. The article underscores the significance of individualized treatment plans, underscoring the need for a multidisciplinary approach to ensure optimal patient outcomes.

An Illustrated Review of the Recent 2019 World Health Organization Classification of Neuroendocrine Neoplasms: A Radiologic and Pathologic Correlation.

ABSTRACT: Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.

State-of-the-Art Hybrid Imaging of Neuroendocrine Neoplasms.

ABSTRACT: Neuroendocrine neoplasms (NENs) may be challenging to diagnose due to their small size and diverse anatomical locations. Hybrid imaging techniques, specifically positron emission tomography/computed tomography (PET/CT) and positron emission tomography/magnetic resonance imaging (PET/MRI), represent the current state-of-the-art for evaluating NENs. The preferred radiopharmaceuticals for NEN PET imaging are gallium-68 (68Ga) DOTA-peptides, which target somatostatin receptors (SSTR) overexpressed on NEN cells. Clinical applications of [68Ga]Ga-DOTA-peptides PET/CT include diagnosis, staging, prognosis assessment, treatment selection, and response evaluation. Fluorodeoxyglucose-18 (18F-FDG) PET/CT aids in detecting low-SSTR-expressing lesions and helps in patient stratification and treatment planning, particularly in grade 3 neuroendocrine tumors (NETs). New radiopharmaceuticals such as fluorine-labeled SSTR agonists and SSTR antagonists are emerging as alternatives to 68Ga-labeled peptides, offering improved detection rates and favorable biodistribution. The maturing of PET/MRI brings advantages to NEN imaging, including simultaneous acquisition of PET and MRI images, superior soft tissue contrast resolution, and motion correction capabilities. The PET/MRI with [68Ga]Ga-DOTA-peptides has demonstrated higher lesion detection rates and more accurate lesion classification compared to PET/CT. Overall, hybrid imaging offers valuable insights in the diagnosis, staging, and treatment planning of NENs. Further research is needed to refine response assessment criteria and standardize reporting guidelines.