Dietrich Stoevesandt, Jonas Steglich, Jörg M Bartelt, Lars Kurch, Kathleen M McCarten, Jamie E Flerlage, Thomas W Georgi, Christine Mauz-Körholz, Steve Y Cho, Dieter Körholz, Regine Kluge, Kara M Kelly, Tanja Pelz, Dirk Vordermark, Bradford S Hoppe, Karin Dieckmann, Stephan D Voss
Staging of pediatric Hodgkin lymphoma is currently based on the Ann Arbor classification, incorporating the Cotswold modifications and the Lugano classification. The Cotswold modifications provide guidelines for the use of CT and MRI. The Lugano classification emphasizes the importance of CT and PET/CT in evaluating both Hodgkin lymphoma and non-Hodgkin lymphoma but focuses on adult patients. This article presents consensus guidelines that extend the traditional classifications used for adult Hodgkin lymphoma staging and provide rigorous definitions of lymph node groups based on MRI, CT, and fluorodeoxyglucose PET/CT findings. This allows consistent terminology and definitions, using metabolic and morphologic imaging to identify affected lymph nodes or extranodal regions and organs. The pattern of involvement, together with other individual risk factors, determines treatment strategy. In case of inadequate response to chemotherapy, radiation therapy is often required. Standardization of staging definitions for pediatric Hodgkin lymphoma is necessary for comparing treatment outcomes between North American and European clinical trials and a prerequisite for clear communication during tumor boards and central review. This comprehensive imaging atlas is intended to provide regional criteria for nodal involvement and to serve as a standardized guide for the anatomic assignment of lymph node involvement in pediatric Hodgkin lymphoma.
{"title":"CT, MRI, and FDG PET/CT in the Assessment of Lymph Node Involvement in Pediatric Hodgkin Lymphoma: An Expert Consensus Definition by an International Collaboration on Staging Evaluation and Response Criteria Harmonization for Children, Adolescent, and Young Adult Hodgkin Lymphoma (SEARCH for CAYAHL).","authors":"Dietrich Stoevesandt, Jonas Steglich, Jörg M Bartelt, Lars Kurch, Kathleen M McCarten, Jamie E Flerlage, Thomas W Georgi, Christine Mauz-Körholz, Steve Y Cho, Dieter Körholz, Regine Kluge, Kara M Kelly, Tanja Pelz, Dirk Vordermark, Bradford S Hoppe, Karin Dieckmann, Stephan D Voss","doi":"10.1148/radiol.232650","DOIUrl":"10.1148/radiol.232650","url":null,"abstract":"<p><p>Staging of pediatric Hodgkin lymphoma is currently based on the Ann Arbor classification, incorporating the Cotswold modifications and the Lugano classification. The Cotswold modifications provide guidelines for the use of CT and MRI. The Lugano classification emphasizes the importance of CT and PET/CT in evaluating both Hodgkin lymphoma and non-Hodgkin lymphoma but focuses on adult patients. This article presents consensus guidelines that extend the traditional classifications used for adult Hodgkin lymphoma staging and provide rigorous definitions of lymph node groups based on MRI, CT, and fluorodeoxyglucose PET/CT findings. This allows consistent terminology and definitions, using metabolic and morphologic imaging to identify affected lymph nodes or extranodal regions and organs. The pattern of involvement, together with other individual risk factors, determines treatment strategy. In case of inadequate response to chemotherapy, radiation therapy is often required. Standardization of staging definitions for pediatric Hodgkin lymphoma is necessary for comparing treatment outcomes between North American and European clinical trials and a prerequisite for clear communication during tumor boards and central review. This comprehensive imaging atlas is intended to provide regional criteria for nodal involvement and to serve as a standardized guide for the anatomic assignment of lymph node involvement in pediatric Hodgkin lymphoma.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 1","pages":"e232650"},"PeriodicalIF":12.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143010656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Wildman-Tobriner, Nicholas Felice, Kevin R Kalisz, Brian C Allen, Sarah P Thomas, Danielle E Kruse, William Paul Segars, Brian Harrawood, Mustafa R Bashir, Daniele Marin, Samantha Morrison, Alaattin Erkanli, Ehsan Samei, Ehsan Abadi
Ji Hyun Lee, Danbee Kang, Junghee Lee, Yeong Jeong Jeon, Seong Yong Park, Jong Ho Cho, Yong Soo Choi, Jhingook Kim, Young Mog Shim, Sunga Kong, Hong Kwan Kim, Juhee Cho
Lukas Meyer, Gabriel Broocks, Maria Alexandrou, Álex Lüttich, José Ángel Larrea, Wolfram Schwindt, Hermann Krähling, Weis Naziri, Daniel Behme, Maximilian Thormann, Hanna Styczen, Cornelius Deuschl, Christoph Kabbasch, Charlotte Zaeske, Charlotte Weyland, Moritz Roman Hernández Petzsche, Christian Maegerlein, Hanna Zimmermann, Marielle Ernst, Ala Jamous, Manuel Moreu Gamazo, Carlos Pérez-García, Pedro Navia, Andrés Fernández Prieto, Leonard Yeo, Benjamin Tan, Anil Gopinathan, Eberhard Siebert, Milena Miszczuk, Stefan Schob, Peter Sporns, Joaquín Zamarro Parra, Guillermo Parrilla, Fabian Arnberg, Tommy Andersson, Kamil Zeleňák, Panagiotis Papanagiotou, Marios Psychogios, Markus Möhlenbruch, André Kemmling, Franziska Dorn, Mohamed Elsharkawy, Jens Fiehler, Christian Paul Stracke
Domenico Mastrodicasa, Marly van Assen, Merel Huisman, Tim Leiner, Eric E Williamson, Edward D Nicol, Bradley D Allen, Luca Saba, Rozemarijn Vliegenthart, Kate Hanneman
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI. Each section is organized into questions and statements that address key steps of the cardiac imaging workflow, including ethical, legal, and environmental sustainability considerations. A technology readiness level range of 1 to 9 summarizes the maturity level of AI tools and reflects the progression from preliminary research to clinical implementation. This document aims to bridge the gap between burgeoning research developments and limited clinical applications of AI tools in cardiac CT and MRI.
{"title":"Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA.","authors":"Domenico Mastrodicasa, Marly van Assen, Merel Huisman, Tim Leiner, Eric E Williamson, Edward D Nicol, Bradley D Allen, Luca Saba, Rozemarijn Vliegenthart, Kate Hanneman","doi":"10.1148/radiol.240516","DOIUrl":"10.1148/radiol.240516","url":null,"abstract":"<p><p>Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI. Each section is organized into questions and statements that address key steps of the cardiac imaging workflow, including ethical, legal, and environmental sustainability considerations. A technology readiness level range of 1 to 9 summarizes the maturity level of AI tools and reflects the progression from preliminary research to clinical implementation. This document aims to bridge the gap between burgeoning research developments and limited clinical applications of AI tools in cardiac CT and MRI.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 1","pages":"e240516"},"PeriodicalIF":12.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143053325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrej Lyshchik, Cristina Kuon Yeng Escalante, Tania Siu Xiao, Fabio Piscaglia, Yuko Kono, Alexandra Medellin-Kowalewski, Shuchi K Rodgers, Virginia Planz, Aya Kamaya, David T Fetzer, Annalisa Berzigotti, Iuliana-Pompilia Radu, Paul S Sidhu, Corinne E Wessner, Kristen Bradigan, John R Eisenbrey, Flemming Forsberg, Stephanie R Wilson
Lucy E M Finnigan, Mark Philip Cassar, Mehrsa Jafarpour, Antonella Sultana, Zakariye Ashkir, Karim Azer, Stefan Neubauer, Damian J Tyler, Betty Raman, Ladislav Valkovič
Background Emerging evidence suggests mitochondrial dysfunction may play a role in the fatigue experienced by individuals with post-COVID-19 condition (PCC), commonly called long COVID, which can be assessed using MR spectroscopy. Purpose To compare mitochondrial function between participants with fatigue-predominant PCC and healthy control participants using MR spectroscopy, and to investigate the relationship between MR spectroscopic parameters and fatigue using the 11-item Chalder fatigue questionnaire. Materials and Methods This prospective, observational, single-center study (June 2021 to January 2024) included participants with PCC who reported moderate to severe fatigue, with normal blood test and echocardiographic results, alongside control participants without fatigue symptoms. MR spectroscopy was performed using a 3-T MRI system, measuring hydrogen 1 (1H) and phosphorus 31 (31P) during exercise and recovery in the gastrocnemius muscle. General linear models were used to compare the phosphocreatine recovery rate time constant (hereafter, τPCr) and maximum oxidative flux, also known as mitochondrial capacity (hereafter, Qmax), between groups. Pearson correlations were used to assess the relationship between MR spectroscopic parameters and fatigue scores. Results A total of 41 participants with PCC (mean age, 44 years ± 9 [SD]; 23 male) (mean body mass index [BMI], 26 ± 4) and 29 healthy control participants (mean age, 34 years ± 11; 18 male) (mean BMI, 23 ± 3) were included in the study. Participants with PCC showed higher resting phosphocreatine levels (mean difference, 4.10 mmol/L; P = .03). Following plantar flexion exercise in situ (3-5 minutes), participants with PCC had a higher τPCr (92.5 seconds ± 35.3) compared with controls (51.9 seconds ± 31.9) (mean difference, 40.6; 95% CI: 24.3, 56.6; P ≤ .001), and Qmax was higher in the control group, with a mean difference of 0.16 mmol/L per second (95% CI: 0.07, 0.26; P = .008). There was no correlation between MR spectroscopic parameters and fatigue scores (r ≤ 0.25 and P ≥ .10 for all). Conclusion Participants with PCC showed differences in τPCr and Qmax compared with healthy controls, suggesting potential mitochondrial dysfunction. This finding did not correlate with fatigue scores. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Parraga and Eddy in this issue.
{"title":"<sup>1</sup>H and <sup>31</sup>P MR Spectroscopy to Assess Muscle Mitochondrial Dysfunction in Long COVID.","authors":"Lucy E M Finnigan, Mark Philip Cassar, Mehrsa Jafarpour, Antonella Sultana, Zakariye Ashkir, Karim Azer, Stefan Neubauer, Damian J Tyler, Betty Raman, Ladislav Valkovič","doi":"10.1148/radiol.233173","DOIUrl":"10.1148/radiol.233173","url":null,"abstract":"<p><p>Background Emerging evidence suggests mitochondrial dysfunction may play a role in the fatigue experienced by individuals with post-COVID-19 condition (PCC), commonly called long COVID, which can be assessed using MR spectroscopy. Purpose To compare mitochondrial function between participants with fatigue-predominant PCC and healthy control participants using MR spectroscopy, and to investigate the relationship between MR spectroscopic parameters and fatigue using the 11-item Chalder fatigue questionnaire. Materials and Methods This prospective, observational, single-center study (June 2021 to January 2024) included participants with PCC who reported moderate to severe fatigue, with normal blood test and echocardiographic results, alongside control participants without fatigue symptoms. MR spectroscopy was performed using a 3-T MRI system, measuring hydrogen 1 (<sup>1</sup>H) and phosphorus 31 (<sup>31</sup>P) during exercise and recovery in the gastrocnemius muscle. General linear models were used to compare the phosphocreatine recovery rate time constant (hereafter, τ<sub>PCr</sub>) and maximum oxidative flux, also known as mitochondrial capacity (hereafter, Q<sub>max</sub>), between groups. Pearson correlations were used to assess the relationship between MR spectroscopic parameters and fatigue scores. Results A total of 41 participants with PCC (mean age, 44 years ± 9 [SD]; 23 male) (mean body mass index [BMI], 26 ± 4) and 29 healthy control participants (mean age, 34 years ± 11; 18 male) (mean BMI, 23 ± 3) were included in the study. Participants with PCC showed higher resting phosphocreatine levels (mean difference, 4.10 mmol/L; <i>P</i> = .03). Following plantar flexion exercise in situ (3-5 minutes), participants with PCC had a higher τ<sub>PCr</sub> (92.5 seconds ± 35.3) compared with controls (51.9 seconds ± 31.9) (mean difference, 40.6; 95% CI: 24.3, 56.6; <i>P</i> ≤ .001), and Q<sub>max</sub> was higher in the control group, with a mean difference of 0.16 mmol/L per second (95% CI: 0.07, 0.26; <i>P</i> = .008). There was no correlation between MR spectroscopic parameters and fatigue scores (<i>r</i> ≤ 0.25 and <i>P</i> ≥ .10 for all). Conclusion Participants with PCC showed differences in τ<sub>PCr</sub> and Q<sub>max</sub> compared with healthy controls, suggesting potential mitochondrial dysfunction. This finding did not correlate with fatigue scores. Published under a CC BY 4.0 license. <i>Supplemental material is available for this article.</i> See also the editorial by Parraga and Eddy in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"313 3","pages":"e233173"},"PeriodicalIF":12.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11694076/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142882912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
History A 65-year-old male patient with a history of sarcomatoid renal cell carcinoma and prior right nephrectomy developed recurrent disease adjacent to the inferior vena cava. The patient underwent surveillance imaging 7 months after initiation of treatment with maximum-dose pazopanib and less than 1 month after completing a 2-month regimen of palliative stereotactic body radiation therapy to the right nephrectomy bed and site of recurrence. (Stereotactic body radiation therapy was initiated 5 months after pazopanib treatment was initiated.) One month after initiating treatment with pazopanib and 6 months before the surveillance imaging, the patient developed diarrhea and required ongoing treatment with loperamide to control symptoms. He denied any fatigue, mouth sores, or extremity pain, but described some abdominal pain and discomfort associated with the diarrhea. He was not experiencing any fevers, and vital signs were normal. White blood cell count was normal at 5100/μL (5.1 ×109/L) (reference range, 4200-10 200/μL [4.2-10.2 ×109/L]), with all components of the differential count also being normal. A normal serum albumin level of 3.9 g/dL (39 g/L) (reference range, 3.5-5.0 g/dL [35-50 g/L]) and low serum total protein level of 6.1 g/dL (61 g/L) (reference range, 6.3-7.9 g/dL [63-79 g/L]) were noted. A comprehensive metabolic panel was performed, indicating a serum chloride level of 98 mmol/L (reference range, 100-108 mmol/L) and an alkaline phosphatase level of 121 U/L (2.02 μkat/L) (reference range, 45-115 U/L [0.75-1.92 μkat/L]). The patient underwent surveillance imaging with contrast-enhanced CT of the abdomen and pelvis in the venous phase.
{"title":"Case 332: Tyrosine Kinase Inhibitor-induced Intestinal Lymphangiectasia.","authors":"Cameron Adler, Christine Menias","doi":"10.1148/radiol.232148","DOIUrl":"https://doi.org/10.1148/radiol.232148","url":null,"abstract":"<p><p>History A 65-year-old male patient with a history of sarcomatoid renal cell carcinoma and prior right nephrectomy developed recurrent disease adjacent to the inferior vena cava. The patient underwent surveillance imaging 7 months after initiation of treatment with maximum-dose pazopanib and less than 1 month after completing a 2-month regimen of palliative stereotactic body radiation therapy to the right nephrectomy bed and site of recurrence. (Stereotactic body radiation therapy was initiated 5 months after pazopanib treatment was initiated.) One month after initiating treatment with pazopanib and 6 months before the surveillance imaging, the patient developed diarrhea and required ongoing treatment with loperamide to control symptoms. He denied any fatigue, mouth sores, or extremity pain, but described some abdominal pain and discomfort associated with the diarrhea. He was not experiencing any fevers, and vital signs were normal. White blood cell count was normal at 5100/μL (5.1 ×10<sup>9</sup>/L) (reference range, 4200-10 200/μL [4.2-10.2 ×10<sup>9</sup>/L]), with all components of the differential count also being normal. A normal serum albumin level of 3.9 g/dL (39 g/L) (reference range, 3.5-5.0 g/dL [35-50 g/L]) and low serum total protein level of 6.1 g/dL (61 g/L) (reference range, 6.3-7.9 g/dL [63-79 g/L]) were noted. A comprehensive metabolic panel was performed, indicating a serum chloride level of 98 mmol/L (reference range, 100-108 mmol/L) and an alkaline phosphatase level of 121 U/L (2.02 μkat/L) (reference range, 45-115 U/L [0.75-1.92 μkat/L]). The patient underwent surveillance imaging with contrast-enhanced CT of the abdomen and pelvis in the venous phase.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"313 3","pages":"e232148"},"PeriodicalIF":12.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142882915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A New Era for Quantitative MRI Biomarkers of the Liver: A Challenge and Opportunity for the Radiology Community.","authors":"Claude B Sirlin, Scott B Reeder","doi":"10.1148/radiol.241876","DOIUrl":"https://doi.org/10.1148/radiol.241876","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"313 3","pages":"e241876"},"PeriodicalIF":12.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142771785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Family History of Lung Cancer in Women Who Have Never Smoked Is a Recognizable Risk Factor in Lung Cancer Screening.","authors":"Yeun-Chung Chang","doi":"10.1148/radiol.243281","DOIUrl":"https://doi.org/10.1148/radiol.243281","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"313 3","pages":"e243281"},"PeriodicalIF":12.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142802206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}