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Hesami M, Blake M, Anderson MA, Asmundo L, Kilcoyne A, Najmi Z, Caravan PD, Catana C, Czawlytko C, Abdar Esfahani S, Kambadakone AR, Samir A, McDermott S, Domachevsky L, Ursprung S, Catalano OA. Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses. J Comput Assist Tomogr 2024:00004728-990000000-00316. [PMID: 38657156 DOI: 10.1097/rct.0000000000001615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
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.
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Affiliation(s)
- Mina Hesami
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Michael Blake
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Mark A Anderson
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | | | - Aoife Kilcoyne
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Zahra Najmi
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Peter D Caravan
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Ciprian Catana
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Cynthia Czawlytko
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Shadi Abdar Esfahani
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Avinash R Kambadakone
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Anthony Samir
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Shaunagh McDermott
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Liran Domachevsky
- Department of Nuclear Medicine, The Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Stephan Ursprung
- Department of Radiology, University Hospital Tuebingen, Tuebingen, Germany
| | - Onofrio A Catalano
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Santoro-Fernandes V, Huff DT, Rivetti L, Deatsch A, Schott B, Perlman SB, Jeraj R. An automated methodology for whole-body, multimodality tracking of individual cancer lesions. Phys Med Biol 2024; 69:085012. [PMID: 38457838 DOI: 10.1088/1361-6560/ad31c6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 03/08/2024] [Indexed: 03/10/2024]
Abstract
Objective. 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.Approach. This study introduces a lesion tracking methodology and benchmarked it using 2368Ga-DOTATATE PET/CT and PET/MR images of eight neuroendocrine tumor patients. The methodology consists of six steps: (1) alignment of multiple scans via image registration, (2) body-part labeling, (3) automatic lesion-wise dilation, (4) clustering of lesions based on local lesion shape metrics, (5) assignment of lesion tracks, and (6) output of a lesion graph. Registration performance was evaluated via landmark distance, lesion matching accuracy was evaluated between each image pair, and lesion tracking accuracy was evaluated via identical track ratio. Sensitivity studies were performed to evaluate the impact of lesion dilation (fixed versus automatic dilation), anatomic location, image modalities (inter- versus intra-modality), registration mode (direct versus indirect registration), and track size (number of time-points and lesions) on lesion matching and tracking performance.Main results. Manual contouring yielded 956 lesions, 1570 lesion-matching decisions, and 493 lesion tracks. The median residual registration error was 2.5 mm. The automatic lesion dilation led to 0.90 overall lesion matching accuracy, and an 88% identical track ratio. The methodology is robust regarding anatomic locations, image modalities, and registration modes. The number of scans had a moderate negative impact on the identical track ratio (94% for 2 scans, 91% for 3 scans, and 81% for 4 scans). The number of lesions substantially impacted the identical track ratio (93% for 2 nodes versus 54% for ≥5 nodes).Significance. The developed methodology resulted in high lesion-matching accuracy and enables automated lesion tracking in PET/CT and PET/MR.
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Affiliation(s)
- Victor Santoro-Fernandes
- School of Medicine and Public Health, Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
| | - Daniel T Huff
- School of Medicine and Public Health, Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
| | - Luciano Rivetti
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Alison Deatsch
- School of Medicine and Public Health, Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
| | - Brayden Schott
- School of Medicine and Public Health, Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
| | - Scott B Perlman
- School of Medicine and Public Health, Department of Radiology, Section of Nuclear Medicine, University of Wisconsin, Madison, WI, United States of America
| | - Robert Jeraj
- School of Medicine and Public Health, Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
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Rectal neuroendocrine neoplasms: what the radiologists should know. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:4016-4031. [PMID: 35288791 DOI: 10.1007/s00261-022-03474-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/18/2022] [Accepted: 02/21/2022] [Indexed: 02/06/2023]
Abstract
Neuroendocrine neoplasms of the rectum (R-NENs) are rare; however, their incidence has increased almost threefold in the last few decades. Imaging of R-NENs includes two primary categories: anatomic/morphologic imaging comprised of endoscopic ultrasound (EUS), computed tomography (CT), magnetic resonance imaging (MRI), and functional/molecular imaging comprising of planar scintigraphy, single-photon emission computed tomography (SPECT), and positron emission tomography (PET). The management depends on stage, dimension, atypical features, histological grade, and lymphovascular invasion (LVI). Low-risk local R-NENs can be resected endoscopically, and high-risk or locally advanced neoplasms can be treated with radical surgery and lymphadenectomy and/or chemoradiation. The review article focuses on imaging illustrations and discusses applications of different imaging modalities in diagnosing and managing R-NENs.
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