Literature DB >> 33585994

Introducing the Node Reporting and Data System 1.0 (Node-RADS): a concept for standardized assessment of lymph nodes in cancer.

Fabian H J Elsholtz1, Patrick Asbach1, Matthias Haas1, Minerva Becker2, Regina G H Beets-Tan3, Harriet C Thoeny4, Anwar R Padhani5, Bernd Hamm6.   

Abstract

"Node-RADS" addresses the lack of consensus in the radiologic assessment of lymph node involvement by cancer and meets the increasing demand for structured reporting on the likelihood of disease involvement. Node Reporting and Data System 1.0 (Node-RADS) systematically classifies the degree of suspicion of lymph node involvement based on the synthesis of established imaging findings. Straightforward definitions of imaging findings for two proposed scoring categories "size" and "configuration" are combined into assessment categories between 1 ("very low likelihood") and 5 ("very high likelihood"). This scoring system is suitable for assessing likely involvement of lymph nodes on CT and MRI scans. It can be applied at any anatomical site, and to regional and non-regional lymph nodes in relation to a primary tumor location. Node-RADS will improve communication with referring physicians and promote the consistency of reporting for primary staging and in response assessment settings. KEY POINTS: • Node-RADS standardizes reporting of possible cancer involvement of regional and distant lymph nodes on CT and MRI. • Node-RADS proposes the scoring categories "size" and "configuration" for assigning the 5-point Node-RADS score from 1 ("very low likelihood") to 5 ("very high likelihood"). • Node-RADS aims to increase consensus among radiologists for primary staging and in response assessment settings.
© 2021. The Author(s).

Entities:  

Keywords:  Consensus; Lymph nodes; Magnetic resonance imaging; Neoplasms; Tomography, X-ray computed

Mesh:

Year:  2021        PMID: 33585994     DOI: 10.1007/s00330-020-07572-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  1 in total

1.  Mammography interpretation: the BI-RADS method.

Authors:  C J D'Orsi; D B Kopans
Journal:  Am Fam Physician       Date:  1997-04       Impact factor: 3.292

  1 in total
  7 in total

Review 1.  The Role of Lymph Node Dissection for Non-Metastatic Renal Cell Carcinoma: An Updated Systematic Review and Meta-Analysis.

Authors:  Xu Shi; Dechao Feng; Dengxiong Li; Facai Zhang; Wuran Wei
Journal:  Front Oncol       Date:  2022-01-12       Impact factor: 6.244

2.  A Dual-Energy CT Radiomics of the Regional Largest Short-Axis Lymph Node Can Improve the Prediction of Lymph Node Metastasis in Patients With Rectal Cancer.

Authors:  Dongqing Wang; Zijian Zhuang; Shuting Wu; Jixiang Chen; Xin Fan; Mengsi Liu; Haitao Zhu; Ming Wang; Jinmei Zou; Qun Zhou; Peng Zhou; Jing Xue; Xiangpan Meng; Shenghong Ju; Lirong Zhang
Journal:  Front Oncol       Date:  2022-06-07       Impact factor: 5.738

Review 3.  Patients with Positive Lymph Nodes after Radical Prostatectomy and Pelvic Lymphadenectomy-Do We Know the Proper Way of Management?

Authors:  Bartosz Małkiewicz; Miłosz Knura; Małgorzata Łątkowska; Maximilian Kobylański; Krystian Nagi; Dawid Janczak; Joanna Chorbińska; Wojciech Krajewski; Jakub Karwacki; Tomasz Szydełko
Journal:  Cancers (Basel)       Date:  2022-05-08       Impact factor: 6.575

4.  Identifying the Candidates Who Will Benefit From Extended Pelvic Lymph Node Dissection at Radical Prostatectomy Among Patients With Prostate Cancer.

Authors:  Guanjie Yang; Jun Xie; Yadong Guo; Jing Yuan; Ruiliang Wang; Changcheng Guo; Bo Peng; Xudong Yao; Bin Yang
Journal:  Front Oncol       Date:  2022-01-26       Impact factor: 6.244

5.  Detection of distant metastases and distant second primary cancers in head and neck squamous cell carcinoma: comparison of [18F]FDG PET/MRI and [18F]FDG PET/CT.

Authors:  Eirini Katirtzidou; Olivier Rager; Arthur Damien Varoquaux; Antoine Poncet; Vincent Lenoir; Nicolas Dulguerov; Alexandra Platon; Valentina Garibotto; Habib Zaidi; Minerva Becker
Journal:  Insights Imaging       Date:  2022-07-28

6.  Inferring FDG-PET-positivity of lymph node metastases in proven lung cancer from contrast-enhanced CT using radiomics and machine learning.

Authors:  Marcus Makowski; Tobias Penzkofer; Boris Gorodetski; Philipp Hendrik Becker; Alexander Daniel Jacques Baur; Alexander Hartenstein; Julian Manuel Michael Rogasch; Christian Furth; Holger Amthauer; Bernd Hamm
Journal:  Eur Radiol Exp       Date:  2022-09-15

7.  Regional lymph node metastasis detected on preoperative CT and/or FDG-PET may predict early recurrence of pancreatic adenocarcinoma after curative resection.

Authors:  Ja Kyung Yoon; Mi-Suk Park; Seung-Seob Kim; Kyunghwa Han; Hee Seung Lee; Seungmin Bang; Ho Kyoung Hwang; Sang Hyun Hwang; Mijin Yun; Myeong-Jin Kim
Journal:  Sci Rep       Date:  2022-10-14       Impact factor: 4.996

  7 in total

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