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Bossuyt V, Provenzano E, Symmans WF, Webster F, Allison KH, Dang C, Gobbi H, Kulka J, Lakhani SR, Moriya T, Quinn CM, Sapino A, Schnitt S, Sibbering DM, Slodkowska E, Yang W, Tan PH, Ellis I. A dedicated structured data set for reporting of invasive carcinoma of the breast in the setting of neoadjuvant therapy: recommendations from the International Collaboration on Cancer Reporting (ICCR). Histopathology 2024; 84:1111-1129. [PMID: 38443320 DOI: 10.1111/his.15165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/11/2024] [Indexed: 03/07/2024]
Abstract
AIMS The International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations, is an initiative aimed at providing a unified international approach to reporting cancer. ICCR recently published new data sets for the reporting of invasive breast carcinoma, surgically removed lymph nodes for breast tumours and ductal carcinoma in situ, variants of lobular carcinoma in situ and low-grade lesions. The data set in this paper addresses the neoadjuvant setting. The aim is to promote high-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment that can be used for subsequent management decisions for each patient. METHODS The ICCR convened expert panels of breast pathologists with a representative surgeon and oncologist to critically review and discuss current evidence. Feedback from the international public consultation was critical in the development of this data set. RESULTS The expert panel concluded that a dedicated data set was required for reporting of breast specimens post-neoadjuvant therapy with inclusion of data elements specific to the neoadjuvant setting as core or non-core elements. This data set proposes a practical approach for handling and reporting breast resection specimens following neoadjuvant therapy. The comments for each data element clarify terminology, discuss available evidence and highlight areas with limited evidence that need further study. This data set overlaps with, and should be used in conjunction with, the data sets for the reporting of invasive breast carcinoma and surgically removed lymph nodes from patients with breast tumours, as appropriate. Key issues specific to the neoadjuvant setting are included in this paper. The entire data set is freely available on the ICCR website. CONCLUSIONS High-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment are critical for subsequent management decisions for each patient.
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Affiliation(s)
- Veerle Bossuyt
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Elena Provenzano
- Department of Histopathology, Addenbrookes Hospital, Cambridge, UK
| | - W Fraser Symmans
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fleur Webster
- International Collaboration on Cancer Reporting, Surry Hills, NSW, Australia
| | - Kimberly H Allison
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chau Dang
- Memorial Sloan Kettering Cancer Center, West Harrison, NY, USA
| | - Helenice Gobbi
- Department of Surgical Clinic, Federal University of Triangulo Mineiro, Uberaba, MG, Brazil
| | - Janina Kulka
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, Budapest, Hungary
| | - Sunil R Lakhani
- Centre for Clinical Research, and Pathology Queensland, University of Queensland, Brisbane, Qld, Australia
| | - Takuya Moriya
- Department of Pathology, Kawasaki Medical School, Okayama, Japan
| | - Cecily M Quinn
- Department of Histopathology, St Vincent's University Hospital, Dublin, Ireland
- School of Medicine, University College, Dublin, Ireland
| | - Anna Sapino
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Stuart Schnitt
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - D Mark Sibbering
- University Hospitals of Derby and Burton NHS Trust, Royal Derby Hospital, Derby, UK
| | - Elzbieta Slodkowska
- Department of Anatomic Pathology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | | | | | - Ian Ellis
- Department of Histopathology, Nottingham City Hospital, London, UK
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Gu K, Lee JH, Shin J, Hwang JA, Min JH, Jeong WK, Lee MW, Song KD, Bae SH. Using GPT-4 for LI-RADS feature extraction and categorization with multilingual free-text reports. Liver Int 2024. [PMID: 38651924 DOI: 10.1111/liv.15891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 01/24/2024] [Accepted: 02/21/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND AND AIMS The Liver Imaging Reporting and Data System (LI-RADS) offers a standardized approach for imaging hepatocellular carcinoma. However, the diverse styles and structures of radiology reports complicate automatic data extraction. Large language models hold the potential for structured data extraction from free-text reports. Our objective was to evaluate the performance of Generative Pre-trained Transformer (GPT)-4 in extracting LI-RADS features and categories from free-text liver magnetic resonance imaging (MRI) reports. METHODS Three radiologists generated 160 fictitious free-text liver MRI reports written in Korean and English, simulating real-world practice. Of these, 20 were used for prompt engineering, and 140 formed the internal test cohort. Seventy-two genuine reports, authored by 17 radiologists were collected and de-identified for the external test cohort. LI-RADS features were extracted using GPT-4, with a Python script calculating categories. Accuracies in each test cohort were compared. RESULTS On the external test, the accuracy for the extraction of major LI-RADS features, which encompass size, nonrim arterial phase hyperenhancement, nonperipheral 'washout', enhancing 'capsule' and threshold growth, ranged from .92 to .99. For the rest of the LI-RADS features, the accuracy ranged from .86 to .97. For the LI-RADS category, the model showed an accuracy of .85 (95% CI: .76, .93). CONCLUSIONS GPT-4 shows promise in extracting LI-RADS features, yet further refinement of its prompting strategy and advancements in its neural network architecture are crucial for reliable use in processing complex real-world MRI reports.
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Affiliation(s)
- Kyowon Gu
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Hyun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jaeseung Shin
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Ah Hwang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Min Woo Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyoung Doo Song
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sung Hwan Bae
- Department of Radiology, Soonchunhyang University College of Medicine, Seoul Hospital, Seoul, Republic of Korea
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Klebe S, Judge M, Brcic L, Dacic S, Galateau-Salle F, Nicholson AG, Roggli V, Nowak AK, Cooper WA. Mesothelioma in the pleura, pericardium and peritoneum: Recommendations from the International Collaboration on Cancer Reporting (ICCR). Histopathology 2024; 84:633-645. [PMID: 38044849 DOI: 10.1111/his.15106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 12/05/2023]
Abstract
AIMS Mesothelioma is a rare malignancy of the serosal membranes that is commonly related to exposure to asbestos. Despite extensive research and clinical trials, prognosis to date remains poor. Consistent, comprehensive and reproducible pathology reporting form the basis of all future interventions for an individual patient, but also ensures that meaningful data are collected to identify predictive and prognostic markers. METHODS AND RESULTS This article details the International Collaboration on Cancer Reporting (ICCR) process and the development of the international consensus mesothelioma reporting data set. It describes the 'core' and 'non-core' elements to be included in pathology reports for mesothelioma of all sites, inclusive of clinical, macroscopic, microscopic and ancillary testing considerations. An international expert panel consisting of pathologists and a medical oncologist produced a set of data items for biopsy and resection specimens based on a critical review and discussion of current evidence, and in light of the changes in the 2021 WHO Classification of Tumours. The commentary focuses particularly upon new entities such as mesothelioma in situ and provides background on relevant and essential ancillary testing as well as implementation of the new requirement for tumour grading. CONCLUSION We recommend widespread and consistent implementation of this data set, which will facilitate accurate reporting and enhance the consistency of data collection, improve the comparison of epidemiological data, support retrospective research and ultimately help to improve clinical outcomes. To this end, all data sets are freely available worldwide on the ICCR website (www.iccr-cancer.org/data-sets).
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Affiliation(s)
- Sonja Klebe
- Department of Anatomical Pathology, Flinders University and SA Pathology, Adelaide, SA, Australia
| | - Meagan Judge
- International Collaboration on Cancer Reporting, Sydney, NSW, Australia
| | - Luka Brcic
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Sanja Dacic
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | | | - Andrew G Nicholson
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Victor Roggli
- Department of Pathology, Duke University Medical Center, Durham, NC, USA
| | - Anna K Nowak
- Medical School, University of Western Australia, Crawley, WA, Australia
| | - Wendy A Cooper
- Department of Tissue Pathology and Diagnostic Oncology, NSW Health Pathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
- Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
- Discipline of Pathology, School of Medicine, Western Sydney University, Sydney, NSW, Australia
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Lien CY, Ting TY, Kuo LC, Chung PC, Chu YC, Kuo CT. Design of HL7 FHIR Profiles for Pathology Reports Integrated with Pathology Images. Stud Health Technol Inform 2024; 310:13-17. [PMID: 38269756 DOI: 10.3233/shti230918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
This paper describes the development of Health Level Seven Fast Healthcare Interoperability Resource (FHIR) profiles for pathology reports integrated with whole slide images and clinical data to create a pathology research database. A report template was designed to collect structured reports, enabling pathologists to select structured terms based on a checklist, allowing for the standardization of terms used to describe tumor features. We gathered and analyzed 190 non-small-cell lung cancer pathology reports in free text format, which were then structured by mapping the itemized vocabulary to FHIR observation resources, using international standard terminologies, such as the International Classification of Diseases, LOINC, and SNOMED CT. The resulting FHIR profiles were published as an implementation guide, which includes 25 profiles for essential data elements, value sets, and structured definitions for integrating clinical data and pathology images associated with the pathology report. These profiles enable the exchange of structured data between systems and facilitate the integration of pathology data into electronic health records, which can improve the quality of care for patients with cancer.
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Affiliation(s)
- Chung-Yueh Lien
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
| | - Tzu-Yun Ting
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
| | - Li-Chun Kuo
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
| | - Pau-Choo Chung
- Electrical Engineering and Computer Science, National Cheng Kung University, Tainan, Taiwan
| | - Yuan-Chia Chu
- Department of Information Management, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chen-Tsung Kuo
- Department of Information Management, Taipei Veterans General Hospital, Taipei, Taiwan
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Tiralongo F, Di Pietro S, Milazzo D, Galioto S, Castiglione DG, Ini’ C, Foti PV, Mosconi C, Giurazza F, Venturini M, Zanghi’ GN, Palmucci S, Basile A. Acute Colonic Diverticulitis: CT Findings, Classifications, and a Proposal of a Structured Reporting Template. Diagnostics (Basel) 2023; 13:3628. [PMID: 38132212 PMCID: PMC10742435 DOI: 10.3390/diagnostics13243628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/25/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023] Open
Abstract
Acute colonic diverticulitis (ACD) is the most common complication of diverticular disease and represents an abdominal emergency. It includes a variety of conditions, extending from localized diverticular inflammation to fecal peritonitis, hence the importance of an accurate diagnosis. Contrast-enhanced computed tomography (CE-CT) plays a pivotal role in the diagnosis due to its high sensitivity, specificity, accuracy, and interobserver agreement. In fact, CE-CT allows alternative diagnoses to be excluded, the inflamed diverticulum to be localized, and complications to be identified. Imaging findings have been reviewed, dividing them into bowel and extra-intestinal wall findings. Moreover, CE-CT allows staging of the disease; the most used classifications of ACD severity are Hinchey's modified and WSES classifications. Differential diagnoses include colon carcinoma, epiploic appendagitis, ischemic colitis, appendicitis, infectious enterocolitis, and inflammatory bowel disease. We propose a structured reporting template to standardize the terminology and improve communication between specialists involved in patient care.
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Affiliation(s)
- Francesco Tiralongo
- Radiology Unit 1, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (D.G.C.); (C.I.)
| | - Stefano Di Pietro
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
| | - Dario Milazzo
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
| | - Sebastiano Galioto
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
| | - Davide Giuseppe Castiglione
- Radiology Unit 1, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (D.G.C.); (C.I.)
| | - Corrado Ini’
- Radiology Unit 1, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (D.G.C.); (C.I.)
| | - Pietro Valerio Foti
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
| | - Cristina Mosconi
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Sant’Orsola-Malpighi Hospital, 40138 Bologna, Italy;
| | - Francesco Giurazza
- Interventional Radiology Department, Cardarelli Hospital of Naples, 80131 Naples, Italy;
| | - Massimo Venturini
- Department of Diagnostic and Interventional Radiology, Circolo Hospital, Insubria University, 21100 Varese, Italy;
| | | | - Stefano Palmucci
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
| | - Antonio Basile
- Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy; (S.D.P.); (D.M.); (S.G.); (P.V.F.); (S.P.); (A.B.)
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6
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Roden AC, Judge M, den Bakker MA, Fang W, Jain D, Marx A, Moreira AL, Rajan A, Stroebel P, Szolkowska M, Cooper WA. Dataset for reporting of thymic epithelial tumours: recommendations from the International Collaboration on Cancer Reporting (ICCR). Histopathology 2023; 83:967-980. [PMID: 37722860 DOI: 10.1111/his.15047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/11/2023] [Accepted: 08/25/2023] [Indexed: 09/20/2023]
Abstract
AIMS Thymic epithelial tumours (TET), including thymomas and thymic carcinomas and thymic neuroendocrine neoplasms, are malignant neoplasms that can be associated with morbidity and mortality. Recently, an updated version of the World Health Organization (WHO) Classification of Thoracic Tumours 5th Edition, 2021 has been released, which included various changes to the classification of these neoplasms. In addition, in 2017 the Union for International Cancer Control (UICC) / American Joint Committee on Cancer (AJCC) published the 8th Edition Staging Manual which, for the first time, includes a TNM staging that is applicable to thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms. METHODS AND RESULTS To standardize reporting of resected TET and thymic neuroendocrine neoplasms the accrediting bodies updated their reporting protocols. The International Collaboration on Cancer Reporting (ICCR), which represents a collaboration between various National Associations of Pathology, updated its 2017 histopathology reporting guide on TET and thymic neuroendocrine neoplasms accordingly. This report will highlight important changes in the reporting of TET and thymic neuroendocrine neoplasms based on the 2021 WHO, emphasize the 2017 TNM staging, and also comment on the rigour and various uncertainties for the pathologist when trying to follow that staging. CONCLUSION The ICCR dataset provides a comprehensive, standardized template for reporting of resected TET and thymic neuroendocrine neoplasms.
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Affiliation(s)
- Anja C Roden
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Meagan Judge
- International Collaboration on Cancer Reporting, Sydney, NSW, Australia
| | - Michael A den Bakker
- Maasstad Hospital, Rotterdam, The Netherlands
- Academic Hospital Erasmus MC, Rotterdam, The Netherlands
| | - Wentao Fang
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai, China
| | - Deepali Jain
- Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
| | - Alexander Marx
- Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
- Institute of Pathology, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany
| | - Andre L Moreira
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, USA
| | - Arun Rajan
- Thoracic and Gastrointestinal Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Philipp Stroebel
- Institute of Pathology, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany
| | - Malgorzata Szolkowska
- Department of Pathology, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - Wendy A Cooper
- Department of Tissue Pathology and Diagnostic Oncology, NSW Health Pathology, Royal Prince Alfred Hospital, NSW, Sydney, Australia
- Institute of Medicine and Health Pathology, University of Sydney, NSW, Sydney, Australia
- School of Medicine, Western Sydney University, Sydney, NSW, Australia
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7
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Pesapane F, Tantrige P, De Marco P, Carriero S, Zugni F, Nicosia L, Bozzini AC, Rotili A, Latronico A, Abbate F, Origgi D, Santicchia S, Petralia G, Carrafiello G, Cassano E. Advancements in Standardizing Radiological Reports: A Comprehensive Review. Medicina (Kaunas) 2023; 59:1679. [PMID: 37763797 PMCID: PMC10535385 DOI: 10.3390/medicina59091679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 08/18/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023]
Abstract
Standardized radiological reports stimulate debate in the medical imaging field. This review paper explores the advantages and challenges of standardized reporting. Standardized reporting can offer improved clarity and efficiency of communication among radiologists and the multidisciplinary team. However, challenges include limited flexibility, initially increased time and effort, and potential user experience issues. The efforts toward standardization are examined, encompassing the establishment of reporting templates, use of common imaging lexicons, and integration of clinical decision support tools. Recent technological advancements, including multimedia-enhanced reporting and AI-driven solutions, are discussed for their potential to improve the standardization process. Organizations such as the ACR, ESUR, RSNA, and ESR have developed standardized reporting systems, templates, and platforms to promote uniformity and collaboration. However, challenges remain in terms of workflow adjustments, language and format variability, and the need for validation. The review concludes by presenting a set of ten essential rules for creating standardized radiology reports, emphasizing clarity, consistency, and adherence to structured formats.
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Affiliation(s)
- Filippo Pesapane
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Priyan Tantrige
- Department of Radiology, King’s College Hospital NHS Foundation Trust, London SE5 9RS, UK;
| | - Paolo De Marco
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (P.D.M.); (D.O.)
| | - Serena Carriero
- Postgraduate School of Radiodiagnostics, University of Milan, 20122 Milan, Italy;
| | - Fabio Zugni
- Division of Radiology, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (F.Z.); (G.P.)
| | - Luca Nicosia
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Anna Carla Bozzini
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Anna Rotili
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Antuono Latronico
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Francesca Abbate
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
| | - Daniela Origgi
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (P.D.M.); (D.O.)
| | - Sonia Santicchia
- Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy; (S.S.); (G.C.)
| | - Giuseppe Petralia
- Division of Radiology, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (F.Z.); (G.P.)
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
| | - Gianpaolo Carrafiello
- Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy; (S.S.); (G.C.)
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (L.N.); (A.C.B.); (A.R.); (F.A.); (E.C.)
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8
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Bovée JVMG, Webster F, Amary F, Baumhoer D, Bloem JLH, Bridge JA, Cates JMM, de Alava E, Dei Tos AP, Jones KB, Mahar A, Nielsen GP, Righi A, Wagner AJ, Yoshida A, Fletcher CDM. Datasets for the reporting of primary tumour in bone: recommendations from the International Collaboration on Cancer Reporting (ICCR). Histopathology 2023; 82:531-540. [PMID: 36464647 PMCID: PMC10107487 DOI: 10.1111/his.14849] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND OBJECTIVES Bone tumours are relatively rare and, as a consequence, treatment in a centre with expertise is required. Current treatment guidelines also recommend review by a specialised pathologist. Here we report on international consensus-based datasets for the pathology reporting of biopsy and resection specimens of bone sarcomas. The datasets were produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations. METHODS AND RESULTS According to the ICCR's process for dataset development, an international expert panel consisting of pathologists, an oncologic orthopaedic surgeon, a medical oncologist, and a radiologist produced a set of core and noncore data items for biopsy and resection specimens based on a critical review and discussion of current evidence. All professionals involved were bone tumour experts affiliated with tertiary referral centres. Commentary was provided for each data item to explain the rationale for selecting it as a core or noncore element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the documents were finalised and ratified, and the datasets, including a synoptic reporting guide, were published on the ICCR website. CONCLUSION These first international datasets for bone sarcomas are intended to promote high-quality, standardised pathology reporting. Their widespread adoption will improve the consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will help to improve management of bone sarcoma patients.
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Affiliation(s)
- Judith V M G Bovée
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.,Leiden Center for Computational Oncology, LUMC, Leiden, The Netherlands
| | - Fleur Webster
- International Collaboration on Cancer Reporting, Sydney, NSW, Australia
| | - Fernanda Amary
- Department of Histopathology, Royal National Orthopaedic Hospital, Stanmore, Greater London, UK.,Cancer Institute, University College London, London, UK
| | - Daniel Baumhoer
- Bone Tumour Reference Centre, Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - J L Hans Bloem
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Julia A Bridge
- Division of Molecular Pathology, ProPath, Dallas, TX, USA.,Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Justin M M Cates
- Department of Pathology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Enrique de Alava
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital, CSIC, University of Seville, Seville, Spain.,Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, Seville, Spain
| | - Angelo Paolo Dei Tos
- Department of Pathology, Azienda Ospedaliera Universitaria di Padova, Padova, Italy.,Department of Medicine, University of Padua, School of Medicine, Padua, Italy
| | - Kevin B Jones
- Department of Orthopaedics, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT, USA.,Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Annabelle Mahar
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - G Petur Nielsen
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Alberto Righi
- Department of Pathology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Andrew J Wagner
- Harvard Medical School, Boston, MA, USA.,Center for Sarcoma and Bone Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Akihiko Yoshida
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo, Japan.,Rare Cancer Center, National Cancer Center Hospital, Tokyo, Japan
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9
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Loughrey MB, Webster F, Arends MJ, Brown I, Burgart LJ, Cunningham C, Flejou JF, Kakar S, Kirsch R, Kojima M, Lugli A, Rosty C, Sheahan K, West NP, Wilson RH, Nagtegaal ID. Dataset for Pathology Reporting of Colorectal Cancer: Recommendations From the International Collaboration on Cancer Reporting (ICCR). Ann Surg 2022; 275:e549-e561. [PMID: 34238814 PMCID: PMC8820778 DOI: 10.1097/sla.0000000000005051] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The aim of this study to describe a new international dataset for pathology reporting of colorectal cancer surgical specimens, produced under the auspices of the International Collaboration on Cancer Reporting (ICCR). BACKGROUND Quality of pathology reporting and mutual understanding between colorectal surgeon, pathologist and oncologist are vital to patient management. Some pathology parameters are prone to variable interpretation, resulting in differing positions adopted by existing national datasets. METHODS The ICCR, a global alliance of major pathology institutions with links to international cancer organizations, has developed and ratified a rigorous and efficient process for the development of evidence-based, structured datasets for pathology reporting of common cancers. Here we describe the production of a dataset for colorectal cancer resection specimens by a multidisciplinary panel of internationally recognized experts. RESULTS The agreed dataset comprises eighteen core (essential) and seven non-core (recommended) elements identified from a review of current evidence. Areas of contention are addressed, some highly relevant to surgical practice, with the aim of standardizing multidisciplinary discussion. The summation of all core elements is considered to be the minimum reporting standard for individual cases. Commentary is provided, explaining each element's clinical relevance, definitions to be applied where appropriate for the agreed list of value options and the rationale for considering the element as core or non-core. CONCLUSIONS This first internationally agreed dataset for colorectal cancer pathology reporting promotes standardization of pathology reporting and enhanced clinicopathological communication. Widespread adoption will facilitate international comparisons, multinational clinical trials and help to improve the management of colorectal cancer globally.
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Affiliation(s)
- Maurice B Loughrey
- Centre for Public Health, Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, Northern Ireland, UK
- Department of Cellular Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK
| | - Fleur Webster
- International Collaboration on Cancer Reporting, Sydney, NSW, Australia
| | - Mark J Arends
- Division of Pathology, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ian Brown
- Envoi Pathology, Kelvin Grove, QLD, Australia
| | - Lawrence J Burgart
- Department of Pathology, Virginia Piper Cancer Institute, Abbott Northwestern Hospital, Minneapolis, MN
| | - Chris Cunningham
- Department of Colorectal Surgery, Churchill Hospital, Oxford University Hospitals NHSFT, Oxford, UK
| | - Jean-Francois Flejou
- Department of Pathology, Saint-Antoine Hospital, Sorbonne University, Paris, France
| | - Sanjay Kakar
- Department of Pathology, University of California San Francisco, San Francisco, CA
| | - Richard Kirsch
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Motohiro Kojima
- Division of Pathology, Research Center for Innovative Oncology, National Cancer Center, Chiba, Kashiwa, Japan
| | | | - Christophe Rosty
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Envoi Specialist Pathologists, Brisbane, QLD, Australia
- Department of Pathology, University of Melbourne, Melbourne, VIC, Australia
| | - Kieran Sheahan
- Department of Pathology, St Vincent's University Hospital & University College, Dublin, Ireland
| | - Nicholas P West
- Pathology and Data Analytics, Leeds Institute of Medical Research at St. James's, University of Leeds, Leeds, UK
| | - Richard H Wilson
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Iris D Nagtegaal
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
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10
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Khalikov AA, Galimov AR, Agzamov VV, Kuznetsov KO. [Analytical and synthesizing part of the forensic expert panel conclusion: a case study of professional violation of healthcare professionals]. Sud Med Ekspert 2022; 65:64-68. [PMID: 35947414 DOI: 10.17116/sudmed20226504164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The objective of the study is to develop scientific criteria for the analytical and synthesizing part of the expert report on 'medical cases.' We studied 15 conclusions of expert panels. The following research methods were used: logical and analytical, logical and synthetic (generalization), comparative, systemic and analytical (analysis of relations between facts). For the first time, a new algorithm for the analytical and synthesizing part of the expert report was proposed; and also ways to improve the quality of forensic reports for all types of expert examinations, including those involving non-state forensic experts, were described. These improvements make the results of expert examinations and reviews more convenient and objective. They are intended for non-state forensic experts, attorneys who use them, and state forensic experts, including during the training and professional development.
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Affiliation(s)
| | - A R Galimov
- Bashkir State Medical University, Ufa, Russia
- Forensic Consulting, Avdon, Russia
| | - V V Agzamov
- Bashkir State Medical University, Ufa, Russia
| | - K O Kuznetsov
- Pirogov Russian National Research Medical University, Moscow, Russia
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11
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Granata V, Morana G, D'Onofrio M, Fusco R, Coppola F, Grassi F, Cappabianca S, Reginelli A, Maggialetti N, Buccicardi D, Barile A, Rengo M, Bortolotto C, Urraro F, La Casella GV, Montella M, Ciaghi E, Bellifemine F, De Muzio F, Danti G, Grazzini G, Barresi C, Brunese L, Neri E, Grassi R, Miele V, Faggioni L. Structured Reporting of Computed Tomography and Magnetic Resonance in the Staging of Pancreatic Adenocarcinoma: A Delphi Consensus Proposal. Diagnostics (Basel) 2021; 11:2033. [PMID: 34829384 DOI: 10.3390/diagnostics11112033] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 10/31/2021] [Accepted: 11/01/2021] [Indexed: 12/12/2022] Open
Abstract
Background: Structured reporting (SR) in radiology has been recognized recently by major scientific societies. This study aims to build structured computed tomography (CT) and magnetic resonance (MR)-based reports in pancreatic adenocarcinoma during the staging phase in order to improve communication between the radiologist and members of multidisciplinary teams. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the CT-SR and MRI-SR, assessing a level of agreement for all report sections. Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. Results: The final CT-SR version was built by including n = 16 items in the “Patient Clinical Data” section, n = 11 items in the “Clinical Evaluation” section, n = 7 items in the “Imaging Protocol” section, and n = 18 items in the “Report” section. Overall, 52 items were included in the final version of the CT-SR. The final MRI-SR version was built by including n = 16 items in the “Patient Clinical Data” section, n = 11 items in the “Clinical Evaluation” section, n = 8 items in the “Imaging Protocol” section, and n = 14 items in the “Report” section. Overall, 49 items were included in the final version of the MRI-SR. In the first round for CT-SR, all sections received more than a good rating. The overall mean score of the experts was 4.85. The Cα correlation coefficient was 0.85. In the second round, the overall mean score of the experts was 4.87, and the Cα correlation coefficient was 0.94. In the first round, for MRI-SR, all sections received more than a good rating. The overall mean score of the experts was 4.73. The Cα correlation coefficient was 0.82. In the second round, the overall mean score of the experts was 4.91, and the Cα correlation coefficient was 0.93. Conclusions: The CT-SR and MRI-SR are based on a multi-round consensus-building Delphi exercise derived from the multidisciplinary agreement of expert radiologists in order to obtain more appropriate communication tools for referring physicians.
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12
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Granata V, Pradella S, Cozzi D, Fusco R, Faggioni L, Coppola F, Grassi R, Maggialetti N, Buccicardi D, Lacasella GV, Montella M, Ciaghi E, Bellifemine F, De Filippo M, Rengo M, Bortolotto C, Prost R, Barresi C, Cappabianca S, Brunese L, Neri E, Grassi R, Miele V. Computed Tomography Structured Reporting in the Staging of Lymphoma: A Delphi Consensus Proposal. J Clin Med 2021; 10:4007. [PMID: 34501455 DOI: 10.3390/jcm10174007] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 12/17/2022] Open
Abstract
Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports for lymphoma patients during the staging phase to improve communication between radiologists, members of multidisciplinary teams, and patients. A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology (SIRM), was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. The Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. The final SR version was divided into four sections: (a) Patient Clinical Data, (b) Clinical Evaluation, (c) Imaging Protocol, and (d) Report, including n = 13 items in the "Patient Clinical Data" section, n = 8 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section, and n = 32 items in the "Report" section. Overall, 62 items were included in the final version of the SR. A dedicated section of significant images was added as part of the report. In the first Delphi round, all sections received more than a good rating (≥3). The overall mean score of the experts and the sum of score for structured report were 4.4 (range 1-5) and 1524 (mean value of 101.6 and standard deviation of 11.8). The Cα correlation coefficient was 0.89 in the first round. In the second Delphi round, all sections received more than an excellent rating (≥4). The overall mean score of the experts and the sum of scores for structured report were 4.9 (range 3-5) and 1694 (mean value of 112.9 and standard deviation of 4.0). The Cα correlation coefficient was 0.87 in this round. The highest overall means value, highest sum of scores of the panelists, and smallest standard deviation values of the evaluations in this round reflect the increase of the internal consistency and agreement among experts in the second round compared to first round. The accurate statement of imaging data given to referring physicians is critical for patient care; the information contained affects both the decision-making process and the subsequent treatment. The radiology report is the most important source of clinical imaging information. It conveys critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to the referring physicians and records this information for future clinical and research use. The present SR was generated based on a multi-round consensus-building Delphi exercise and uses standardized terminology and structures, in order to adhere to diagnostic/therapeutic recommendations and facilitate enrolment in clinical trials, to reduce any ambiguity that may arise from non-conventional language, and to enable better communication between radiologists and clinicians.
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13
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Granata V, Grassi R, Miele V, Larici AR, Sverzellati N, Cappabianca S, Brunese L, Maggialetti N, Borghesi A, Fusco R, Balbi M, Urraro F, Buccicardi D, Bortolotto C, Prost R, Rengo M, Baratella E, De Filippo M, Barresi C, Palmucci S, Busso M, Calandriello L, Sansone M, Neri E, Coppola F, Faggioni L. Structured Reporting of Lung Cancer Staging: A Consensus Proposal. Diagnostics (Basel) 2021; 11:1569. [PMID: 34573911 DOI: 10.3390/diagnostics11091569] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/20/2021] [Accepted: 08/27/2021] [Indexed: 11/30/2022] Open
Abstract
Background: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi exercise was used to build the structural report and to assess the level of agreement for all the report sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to perform a quality analysis according to the average inter-item correlation. Results: The final SR version was built by including 16 items in the “Patient Clinical Data” section, 4 items in the “Clinical Evaluation” section, 8 items in the “Exam Technique” section, 22 items in the “Report” section, and 5 items in the “Conclusion” section. Overall, 55 items were included in the final version of the SR. The overall mean of the scores of the experts and the sum of scores for the structured report were 4.5 (range 1–5) and 631 (mean value 67.54, STD 7.53), respectively, in the first round. The items of the structured report with higher accordance in the first round were primary lesion features, lymph nodes, metastasis and conclusions. The overall mean of the scores of the experts and the sum of scores for staging in the structured report were 4.7 (range 4–5) and 807 (mean value 70.11, STD 4.81), respectively, in the second round. The Cronbach’s alpha (Cα) correlation coefficient was 0.89 in the first round and 0.92 in the second round for staging in the structured report. Conclusions: The wide implementation of SR is critical for providing referring physicians and patients with the best quality of service, and for providing researchers with the best quality of data in the context of the big data exploitation of the available clinical data. Implementation is complex, requiring mature technology to successfully address pending user-friendliness, organizational and interoperability challenges.
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14
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Smith WC, Khatri G, Dunn SH, Zeidan N, Browning TG, Kubiliun N, Mansour JC, Minter RM, Vu L, Coleman VL, Pedrosa I, Leyendecker JR. Facilitating Surveillance of Incidental Findings Using a Novel Reporting Template: Proof of Concept in Patients With Pancreatic Abnormalities. J Am Coll Radiol 2021; 18:1246-57. [PMID: 34283988 DOI: 10.1016/j.jacr.2021.07.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/30/2021] [Accepted: 07/01/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVE To determine the surveillance impact of utilizing a discrete field in structured radiology reports in patients with incidental pancreatic findings. METHODS We implemented a dictation template containing a discrete structured field element to auto-trigger listing of patients with incidental pancreatic findings on a pancreas clinic registry in the electronic health record. We isolated CT and MRI reports with incidental pancreatic findings over a 24-month period. We stratified patients by presence or absence of the discrete field element in reports (flagged versus unflagged) and evaluated the impact of report flagging on likelihood of clinic follow-up, follow-up imaging, endoscopic ultrasound, surgical intervention, genetics referral, obtaining pathologic diagnosis, and time interval between index imaging to various outcomes. RESULTS Patients with flagged reports were more likely to be seen or discussed in a pancreas clinic compared with those with unflagged reports (189 of 376, 50.3% versus 79 of 474, 16.7%; P <. 001). Patients with flagged reports were more likely to get follow-up imaging than patients with unflagged reports (188 of 376, 50.0% versus 121 of 474, 25.5%; P < .001) and were more likely to undergo appropriate management of actionable findings compared with patients in the unflagged group (23 of 62, 37.1% versus 28 of 129, 21.7%; P = .036). DISCUSSION Implementation of a structured discrete field element for reporting of patients with incidental pancreatic findings had positive impact on surveillance measures and can be applied in other organ systems with established surveillance guidelines to standardize patient care.
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15
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Vujanić GM, D'Hooghe E, Vokuhl C, Collini P. Dataset for the reporting of nephrectomy specimens for Wilms' tumour treated with preoperative chemotherapy: recommendations from the International Society of Paediatric Oncology Renal Tumour Study Group. Histopathology 2021; 79:678-686. [PMID: 33942359 DOI: 10.1111/his.14394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 04/26/2021] [Accepted: 04/29/2021] [Indexed: 11/28/2022]
Abstract
Datasets for histopathological reporting of many cancer types are developed by the International Collaboration on Cancer Reporting (ICCR), and are used in order to ensure standardised and uniformly accepted reporting as one of the essential requirements for comparison across patient populations in evaluating and validating pathological prognostic and predictive factors. Wilms' tumours are rare, and international reporting guidelines have not yet been published by the ICCR. The assessment of Wilms' tumours differs according to the treatment approach. The Children's Oncology Group, whose approach is followed mainly in North America, advocates primary surgery, and the International Society of Paediatric Oncology Renal Tumour Study Group (SIOP-RTSG), whose approach is followed in most countries around the world, uses preoperative chemotherapy as a first step, resulting in different subclassifications, staging criteria, and histopathological prognostic factors. This dataset is developed for the countries and institutions following the SIOP-RTSG approach, and it contains core (required) and non-core (recommended) elements, based on the results of the previous SIOP-RTSG studies, which are incorporated in the latest SIOP-RTSG UMBRELLA 2016 Study protocol. The core elements include clinical information, additional specimen submitted, macroscopic tumour site and appearance, tumour focality, tumour dimensions, macroscopic extent of invasion, block identification key, histological tumour type, histological tumour grade and risk group assessment, microscopic extent of invasion, lymphovascular invasion, resection margin status, regional lymph node status, histologically confirmed distant metastases, and pathological staging (SIOP staging system). The dataset should improve communication for patient care and prognostic determination of the old and new histopathological features.
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Affiliation(s)
- Gordan M Vujanić
- Department of Pathology, Sidra Medicine, Doha, Qatar.,Weill Cornell Medicine-Qatar, Doha
| | - Ellen D'Hooghe
- Department of Pathology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | | | - Paola Collini
- Department of Diagnostic Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
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16
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Reginelli A, Grassi R, Feragalli B, Belfiore MP, Montanelli A, Patelli G, La Porta M, Urraro F, Fusco R, Granata V, Petrillo A, Giacobbe G, Russo GM, Sacco P, Grassi R, Cappabianca S. Coronavirus Disease 2019 (COVID-19) in Italy: Double Reading of Chest CT Examination. Biology (Basel) 2021; 10:biology10020089. [PMID: 33504028 PMCID: PMC7911408 DOI: 10.3390/biology10020089] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 01/22/2021] [Indexed: 12/28/2022]
Abstract
To assess the performance of the second reading of chest compute tomography (CT) examinations by expert radiologists in patients with discordance between the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test for COVID-19 viral pneumonia and the CT report. Three hundred and seventy-eight patients were included in this retrospective study (121 women and 257 men; 71 years median age, with a range of 29-93 years) and subjected to RT-PCR tests for suspicious COVID-19 infection. All patients were subjected to CT examination in order to evaluate the pulmonary disease involvement by COVID-19. CT images were reviewed first by two radiologists who identified COVID-19 typical CT patterns and then reanalyzed by another two radiologists using a CT structured report for COVID-19 diagnosis. Weighted к values were used to evaluate the inter-reader agreement. The median temporal window between RT-PCRs execution and CT scan was zero days with a range of (-9,11) days. The RT-PCR test was positive in 328/378 (86.8%). Discordance between RT-PCR and CT findings for viral pneumonia was revealed in 60 cases. The second reading changed the CT diagnosis in 16/60 (26.7%) cases contributing to an increase the concordance with the RT-PCR. Among these 60 cases, eight were false negative with positive RT-PCR, and 36 were false positive with negative RT-PCR. Sensitivity, specificity, positive predictive value and negative predictive value of CT were respectively of 97.3%, 53.8%, 89.0%, and 88.4%. Double reading of CT scans and expert second readers could increase the diagnostic confidence of radiological interpretation in COVID-19 patients.
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Affiliation(s)
- Alfonso Reginelli
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | - Roberta Grassi
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | - Beatrice Feragalli
- Oral and Biotechnological Sciences—Radiology Unit “G. D’Annunzio”, Department of Medical, University of Chieti-Pescara, 66100 Chieti, Italy;
| | - Maria Paola Belfiore
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | | | | | | | - Fabrizio Urraro
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | - Roberta Fusco
- Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy; (V.G.); (A.P.)
- Correspondence: ; Tel.: +39-081-590-3714
| | - Vincenza Granata
- Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy; (V.G.); (A.P.)
| | - Antonella Petrillo
- Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy; (V.G.); (A.P.)
| | - Giuliana Giacobbe
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | - Gaetano Maria Russo
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
| | - Palmino Sacco
- Diagnostic Imaging Unit, Department of Radiological Sciences, Azienda Ospedaliera Universitaria Senese, 53100 Siena, Italy;
| | - Roberto Grassi
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
- Foundation SIRM, 20122 Milan, Italy
| | - Salvatore Cappabianca
- Department of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy; (A.R.); (R.G.); (M.P.B.); (F.U.); (G.G.); (G.M.R.); (R.G.); (S.C.)
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17
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Granata V, Coppola F, Grassi R, Fusco R, Tafuto S, Izzo F, Reginelli A, Maggialetti N, Buccicardi D, Frittoli B, Rengo M, Bortolotto C, Prost R, Lacasella GV, Montella M, Ciaghi E, Bellifemine F, De Muzio F, Danti G, Grazzini G, De Filippo M, Cappabianca S, Barresi C, Iafrate F, Stoppino LP, Laghi A, Grassi R, Brunese L, Neri E, Miele V, Faggioni L. Structured Reporting of Computed Tomography in the Staging of Neuroendocrine Neoplasms: A Delphi Consensus Proposal. Front Endocrinol (Lausanne) 2021; 12:748944. [PMID: 34917023 PMCID: PMC8670531 DOI: 10.3389/fendo.2021.748944] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 11/12/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in Neuroendocrine Neoplasms during the staging phase in order to improve communication between the radiologist and members of multidisciplinary teams. MATERIALS AND METHODS A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A Modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS The final SR version was built by including n=16 items in the "Patient Clinical Data" section, n=13 items in the "Clinical Evaluation" section, n=8 items in the "Imaging Protocol" section, and n=17 items in the "Report" section. Overall, 54 items were included in the final version of the SR. Both in the first and second round, all sections received more than a good rating: a mean value of 4.7 and range of 4.2-5.0 in the first round and a mean value 4.9 and range of 4.9-5 in the second round. In the first round, the Cα correlation coefficient was a poor 0.57: the overall mean score of the experts and the sum of scores for the structured report were 4.7 (range 1-5) and 728 (mean value 52.00 and standard deviation 2.83), respectively. In the second round, the Cα correlation coefficient was a good 0.82: the overall mean score of the experts and the sum of scores for the structured report were 4.9 (range 4-5) and 760 (mean value 54.29 and standard deviation 1.64), respectively. CONCLUSIONS The present SR, based on a multi-round consensus-building Delphi exercise following in-depth discussion between expert radiologists in gastro-enteric and oncological imaging, derived from a multidisciplinary agreement between a radiologist, medical oncologist and surgeon in order to obtain the most appropriate communication tool for referring physicians.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”, Naples, Italy
| | - Francesca Coppola
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Roberta Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | | | - Salvatore Tafuto
- Medical Oncology Unit, Istituto Nazionale Tumori IRCCS ‘Fondazione G. Pascale’, Naples, Italy
| | - Francesco Izzo
- Department of Surgery, Istituto Nazionale Tumori -IRCCS- Fondazione G. Pascale, Naples, Italy
| | - Alfonso Reginelli
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | | | | | - Barbara Frittoli
- Department of Radiology, Ospedali Civili, Hospital of Brescia, University of Brescia, Brescia, Italy
| | - Marco Rengo
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome - I.C.O.T. Hospital, Latina, Italy
| | - Chandra Bortolotto
- Department of Radiology, I.R.C.C.S. Policlinico San Matteo Foundation, Pavia, Italy
| | - Roberto Prost
- Radiology Unit, Azienda Ospedaliera Brotzu, Cagliari, Italy
| | - Giorgia Viola Lacasella
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | - Marco Montella
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | | | | | - Federica De Muzio
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, Campobasso, Italy
| | - Ginevra Danti
- Division of Radiology, “Azienda Ospedaliera Universitaria Careggi”, Florence, Italy
- *Correspondence: Ginevra Danti,
| | - Giulia Grazzini
- Division of Radiology, “Azienda Ospedaliera Universitaria Careggi”, Florence, Italy
| | - Massimo De Filippo
- Department of Medicine and Surgery, Unit of Radiology, University of Parma, Maggiore Hospital, Parma, Italy
| | - Salvatore Cappabianca
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | - Carmelo Barresi
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy
| | - Franco Iafrate
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | | | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant’Andrea University Hospital, Rome, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, Naples, Italy
| | - Luca Brunese
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, Campobasso, Italy
| | - Emanuele Neri
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Translational Research, University of Pisa, Pisa, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Division of Radiology, “Azienda Ospedaliera Universitaria Careggi”, Florence, Italy
| | - Lorenzo Faggioni
- Department of Translational Research, University of Pisa, Pisa, Italy
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18
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Wang T, Xiong Z, Zhou H, Luo W, Tang H, Liu J. Design, validation, and clinical practice of standardized imaging diagnostic report for COVID-19. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2020; 45:229-235. [PMID: 32386012 DOI: 10.11817/j.issn.1672-7347.2020.200152] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVES To design a standardized imaging diagnostic reporting mode for screening coronavirus disease 2019 (COVID-19), and to prospectively verify its effectiveness in clinical practice. METHODS A new classification and standardized imaging diagnosis report mode of viral pneumonia was established by studying and summarizing the imaging findings of various kinds of viral pneumonia, combining with lesion density, interstitial changes, pleural effusion, lymph nodes, and some special signs. After systematic training, the radiologist experienced clinical practice for screening CT features. COVID-19 cases were screened retrospectively in the single-center. The confirmed cases were verified, and the diagnostic efficacy of the standardized imaging reporting system in screening COVID-19 was tested. RESULTS There were 912 patients in this stage receiving the screening imaging examination. Of them, 190 patients were screened in the report mode and 30 patients were diagnosed as COVID-19. The CT manifestation of COVID-19 was characterized by pure ground glass lesions or with a few solid components, predominant subpleural distribution, no lymph node enlargement and pleural effusion, and often with paving-way sign and air bronchus sign. In combination with the above signs, the diagnostic efficacy of COVID-19 was 0.942. CONCLUSIONS The standardized imaging diagnosis report mode based on COVID-19 chest image features is effective and practical, which should be popularized.
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Affiliation(s)
- Tianming Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Zeng Xiong
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Hui Zhou
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Weijun Luo
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Haixiong Tang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Jinkang Liu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China
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19
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Benson J, Burgstahler M, Zhang L, Rischall M. The value of structured radiology reports to categorize intracranial metastases following radiation therapy. Neuroradiol J 2019; 32:267-272. [PMID: 31017073 DOI: 10.1177/1971400919845365] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
PURPOSE Radiology descriptions of intracranial metastases following radiotherapy are often imprecise. This study sought to improve such reports by creating and disseminating a structured template that encourages discrete categorization of intracranial lesions. METHODS Following initiation of the structured template, a retrospective review assessed patients with intracranial metastases that underwent radiotherapy, comparing 'pre-template' with 'post-template' reports. A total of 139 patients were included; 94 patients (67.6%) were imaged pre-template, 45 (32.4%) post-template. Reports were assessed for discrete versus non-specific descriptions of lesions: '(presumed) new metastases', 'treated metastases', and 'indeterminate lesions'. Non-specific language was subdivided based on the type of lesion(s) described: e.g. 'stable enhancing foci' was deemed a non-specific description of 'treated metastases'. RESULTS Non-specific descriptions of lesions were used in 25/94 reports (26.6%) pre-template, and eight reports (17.8%) post-template. No significant difference was found in the frequency of inappropriate/ambiguous descriptions of intracranial lesions following template initiation (P = 0.52). However, only 27/45 (60.0%) of the reports in the post-template time period used the structured report; the other reports were written as free prose. Of the reports that did use the structured template, the authors used significantly less ambiguous language structured template (P = 0.02). CONCLUSION When utilized, a structured report template resulted in decreased non-specific descriptions and improved discrete characterization of intracranial metastases in patients treated with radiation. However, the frequency of non-specific language usage before and after template initiation was unchanged, probably due to poor compliance with template utilization.
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Affiliation(s)
| | | | - Lei Zhang
- 3 Clinical and Translational Science Institute, University of Minnesota, USA
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20
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Awaysheh A, Wilcke J, Elvinger F, Rees L, Fan W, Zimmerman K. Identifying free-text features to improve automated classification of structured histopathology reports for feline small intestinal disease. J Vet Diagn Invest 2017; 30:211-217. [PMID: 29188759 DOI: 10.1177/1040638717744002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The histologic evaluation of gastrointestinal (GI) biopsies is the standard for diagnosis of a variety of GI diseases (e.g., inflammatory bowel disease [IBD] and alimentary lymphoma [ALA]). The World Small Animal Veterinary Association (WSAVA) Gastrointestinal International Standardization Group proposed a reporting standard for GI biopsies consisting of a defined set of microscopic features. We compared the machine classification accuracy of free-text microscopic findings with those represented in the WSAVA format with a diagnosis of IBD and ALA. Unstructured free-text duodenal biopsy pathology reports from cats ( n = 60) with a diagnosis of IBD ( n = 20), ALA ( n = 20), or normal ( n = 20) were identified. Biopsy samples from these cases were then scored following the WSAVA guidelines to create a set of structured reports. Three supervised machine-learning algorithms were trained using the structured and then the unstructured reports. Diagnosis classification accuracy for the 3 algorithms was compared using the structured and unstructured reports. Using naive Bayes and neural networks, unstructured information-based models achieved higher diagnostic accuracy (0.90 and 0.88, respectively) compared to the structured information-based models (0.74 and 0.72, respectively). Results suggest that discriminating diagnostic information was lost using current WSAVA microscopic guideline features. Addition of free-text features (number of plasma cells) increased WSAVA auto-classification performance. The methodologies reported in our study represent a way of identifying candidate microscopic features for use in structured histopathology reports.
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Affiliation(s)
- Abdullah Awaysheh
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
| | - Jeffrey Wilcke
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
| | - François Elvinger
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
| | - Loren Rees
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
| | - Weiguo Fan
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
| | - Kurt Zimmerman
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine (Awaysheh, Wilcke, Zimmerman), Virginia Tech, Blacksburg, VA.,Department of Business Information Technology, Pamplin College of Business (Fan, Rees), Virginia Tech, Blacksburg, VA.,Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
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21
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Nicholson AG, Detterbeck F, Marx A, Roden AC, Marchevsky AM, Mukai K, Chen G, Marino M, den Bakker MA, Yang WI, Judge M, Hirschowitz L. Dataset for reporting of thymic epithelial tumours: recommendations from the International Collaboration on Cancer Reporting (ICCR). Histopathology 2016; 70:522-538. [PMID: 27735079 DOI: 10.1111/his.13099] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 10/10/2016] [Indexed: 12/18/2022]
Abstract
AIMS The International Collaboration on Cancer Reporting (ICCR) is a not-for-profit organization formed by the Royal Colleges of Pathologists of Australasia and the United Kingdom, the College of American Pathologists, the Canadian Association of Pathologists-Association Canadienne des Pathologists in association with the Canadian Partnership Against Cancer, and the European Society of Pathology. Its goal is to produce standardized, internationally agreed, evidence-based datasets for use throughout the world. METHODS AND RESULTS This article describes the development of a cancer dataset by the multidisciplinary ICCR expert panel for the reporting of thymic epithelial tumours. The dataset includes 'required' (mandatory) and 'recommended' (non-mandatory) elements, which are validated by a review of current evidence and supported by explanatory text. Seven required elements and 12 recommended elements were agreed by the international dataset authoring committee to represent the essential information for the reporting of thymic epithelial tumours. CONCLUSIONS The use of an internationally agreed, structured pathology dataset for reporting thymic tumours provides all of the necessary information for optimal patient management, facilitates consistent and accurate data collection, and provides valuable data for research and international benchmarking. The dataset also provides a valuable resource for those countries and institutions that are not in a position to develop their own datasets.
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Affiliation(s)
- Andrew G Nicholson
- Department of Histopathology, Royal Brompton and Harefield NHS Foundation Trust and National Heart and Lung Division, Imperial College, London, UK
| | - Frank Detterbeck
- Division of Thoracic Surgery, Department of Surgery, Yale University, New Haven, CN, USA
| | - Alexander Marx
- Department of Pathology, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
| | - Anja C Roden
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Alberto M Marchevsky
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Kiyoshi Mukai
- Department of Diagnostic Pathology, Saiseikai Central Hospital, Tokyo, Japan
| | - Gang Chen
- Department of Pathology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Mirella Marino
- Department of Pathology, Regina Elena National Cancer Institute, Rome, Italy
| | - Michael A den Bakker
- Department of Pathology, Maasstad Hospital and Department of Pathology of the Erasmus MC, Rotterdam, the Netherlands
| | - Woo-Ick Yang
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Meagan Judge
- Royal College of Pathologists of Australasia, Sydney, Australia
| | - Lynn Hirschowitz
- Department of Cellular Pathology, Birmingham Women's Hospital, Birmingham, UK
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22
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Barbosa F, Traina AJ, Muglia VF. Meta-generalis: A novel method for structuring information from radiology reports. Appl Clin Inform 2016; 7:803-16. [PMID: 27580980 DOI: 10.4338/aci-2016-03-ra-0037] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 07/22/2016] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND A structured report for imaging exams aims at increasing the precision in information retrieval and communication between physicians. However, it is more concise than free text and may limit specialists' descriptions of important findings not covered by pre-defined structures. A computational ontological structure derived from free texts designed by specialists may be a solution for this problem. Therefore, the goal of our study was to develop a methodology for structuring information in radiology reports covering specifications required for the Brazilian Portuguese language, including the terminology to be used. METHODS We gathered 1,701 radiological reports of magnetic resonance imaging (MRI) studies of the lumbosacral spine from three different institutions. Techniques of text mining and ontological conceptualization of lexical units extracted were used to structure information. Ten radiologists, specialists in lumbosacral MRI, evaluated the textual superstructure and terminology extracted using an electronic questionnaire. RESULTS The established methodology consists of six steps: 1) collection of radiology reports of a specific MRI examination; 2) textual decomposition; 3) normalization of lexical units; 4) identification of textual superstructures; 5) conceptualization of candidate-terms; and 6) evaluation of superstructures and extracted terminology by experts using an electronic questionnaire. Three different textual superstructures were identified, with terminological variations in the names of their textual categories. The number of candidate-terms conceptualized was 4,183, yielding 727 concepts. There were a total of 13,963 relationships between candidate-terms and concepts and 789 relationships among concepts. CONCLUSIONS The proposed methodology allowed structuring information in a more intuitive and practical way. Indications of three textual superstructures, extraction of lexicon units and the normalization and ontologically conceptualization were achieved while maintaining references to their respective categories and free text radiology reports.
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Affiliation(s)
| | | | - Valdair Francisco Muglia
- Valdair Muglia, MD., Ph.D., Universidade de Sao Paulo Ribeirao Preto School of Medicine, Internal Medicine, Av Bandeirantes 3900, Campus Monte Alegre, Ribeirao Preto, Sao Paulo 14049900, Brazil,
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23
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Silveira PC, Dunne R, Sainani NI, Lacson R, Silverman SG, Tempany CM, Khorasani R. Impact of an Information Technology-Enabled Initiative on the Quality of Prostate Multiparametric MRI Reports. Acad Radiol 2015; 22:827-33. [PMID: 25863794 DOI: 10.1016/j.acra.2015.02.018] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Revised: 02/20/2015] [Accepted: 02/22/2015] [Indexed: 01/24/2023]
Abstract
RATIONALE AND OBJECTIVES Assess the impact of implementing a structured report template and a computer-aided diagnosis (CAD) tool on the quality of prostate multiparametric magnetic resonance imaging (mp-MRI) reports. MATERIALS AND METHODS Institutional Review Board approval was obtained for this Health Insurance Portability and Accountability Act-compliant study performed at an academic medical center. The study cohort included all prostate mp-MRI reports (n = 385) finalized 6 months before and after implementation of a structured report template and a CAD tool (collectively the information technology [IT] tools) integrated into the picture archiving and communication system workstation. Primary outcome measure was quality of prostate mp-MRI reports. An expert panel of our institution's subspecialty-trained abdominal radiologists defined prostate mp-MRI report quality as optimal, satisfactory, or unsatisfactory based on documentation of nine variables. Reports were reviewed to extract the predefined quality variables and determine whether the IT tools were used to create each report. Chi-square and Student's t tests were used to compare report quality before and after implementation of IT tools. RESULTS The overall proportion of optimal or satisfactory reports increased from 29.8% (47/158) to 53.3% (121/227) (P < .001) after implementing the IT tools. Although the proportion of optimal or satisfactory reports increased among reports generated using at least one of the IT tools (47/158 = [29.8%] vs. 105/161 = [65.2%]; P < .001), there was no change in quality among reports generated without use of the IT tools (47/158 = [29.8%] vs. 16/66 = [24.2%]; P = .404). CONCLUSIONS The use of a structured template and CAD tool improved the quality of prostate mp-MRI reports compared to free-text report format and subjective measurement of contrast enhancement kinetic curve.
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24
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Manoonchai N, Kaewlai R, Wibulpolprasert A, Boonpramarn U, Tohmee A, Phongkitkarun S. Satisfaction of imaging report rendered in emergency setting: a survey of radiology and referring physicians. Acad Radiol 2015; 22:760-70. [PMID: 25754801 DOI: 10.1016/j.acra.2015.01.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2014] [Revised: 01/10/2015] [Accepted: 01/15/2015] [Indexed: 11/30/2022]
Abstract
RATIONALE AND OBJECTIVES To determine physicians' preference toward three types of structured imaging reports (basic structured report [BSR], itemized report [IR], and point-and-click report [PCR]) used in emergency radiology. MATERIALS AND METHODS Survey questions were created and considered valid and reliable based on index of item objective congruence from three specialists (>0.75) and a pilot of 25 subjects (Cronbach alpha, 0.83-1.00). Respondents included trainees and attendings in radiology and referring physicians working in the academic emergency department at the time of survey rollout. They were provided report examples of each type and asked to complete a questionnaire consisting of the following five parts: demographics, necessity of imaging report, report quality (content, format and organization, and language), process of reporting, and components of imaging report. For rating scores, the higher value means the higher preference and agreement. RESULTS The survey received 79.5% response rate. Respondents included 101 physicians (mean age, 29.4 years; 61 radiology physicians and 40 referring physicians; 81 trainees and 20 attending). Overall, IR was preferred over PCR and BSR by all physicians with scores (out of 10) as follows: IR, 7.62-8.83; PCR, 6.62-8.55; BSR, 5.23-6.65; P < .001. IR received scores (out of 5) of 4.03-4.37, PCR 3.32-4.52, and BSR 2.59-3.86 for report quality. For process of reporting, IR had scores (out of 5) of 3.80-4.56, PCR 2.79-4.09, and BSR 2.32-3.56. CONCLUSIONS In emergency setting, physicians preferred IR over PCR and BSR. IR and PCR were equal in report quality metrics, but IR was most preferred in the process of reporting. BSR ranked last in both quality and process.
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Affiliation(s)
- Naree Manoonchai
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270, Rama VI road, Ratchathewi, Bangkok 10400, Thailand
| | - Rathachai Kaewlai
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270, Rama VI road, Ratchathewi, Bangkok 10400, Thailand.
| | - Arrug Wibulpolprasert
- Department of Emergency Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Ugrit Boonpramarn
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270, Rama VI road, Ratchathewi, Bangkok 10400, Thailand
| | - Adul Tohmee
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270, Rama VI road, Ratchathewi, Bangkok 10400, Thailand
| | - Sith Phongkitkarun
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270, Rama VI road, Ratchathewi, Bangkok 10400, Thailand
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