Literature DB >> 34233509

Impact of double reading on NI-RADS diagnostic accuracy in reporting oral squamous cell carcinoma surveillance imaging - a single-center study.

Fabian Henry Jürgen Elsholtz1, Sa-Ra Ro1, Seyd Shnayien1, Patrick Dinkelborg2, Bernd Hamm1, Lars-Arne Schaafs1.   

Abstract

OBJECTIVES: The Neck Imaging Reporting and Data System (NI-RADS) is an increasingly utilized risk stratification tool for imaging surveillance after treatment for head and neck cancer. This study aims to measure the impact of supervision by subspecialized radiologists on diagnostic accuracy of NI-RADS when initial reading is performed by residents.
METHODS: 150 CT and MRI datasets were initially read by two trained residents, and then supervised by two subspecialized radiologists. Recurrence rates by NI-RADS category were calculated, and receiver operating characteristic (ROC) curves were plotted. After dichotomization of the NI-RADS system (category 1 vs categories 2 + 3+4 and categories 1 + 2 vs 3 + 4), sensitivity, specificity, positive and negative predictive value were calculated.
RESULTS: 26% of the reports were modified by the supervising radiologists. Area under the curve of ROC plots values of the supervision session were higher than those of the initial reading session for both the primary site (0.89 vs 0.86) and the neck (0.94 vs 0.91), but the difference was not statistically significant. For dichotomized NI-RADS category assignments, differences between the initial reading and the supervision session were statistically significant regarding specificity and PPV for the primary site (1 + 2 vs 3 + 4 and 1 vs 2 + 3+4) or even for both sites combined (1 vs 2 + 3+4).
CONCLUSION: NI-RADS enables trained resident radiologists to report surveillance imaging in patients with treated oral squamous cell carcinoma with high discriminatory power. Additional supervision by a subspecialized head and neck radiologist particularly improves specificity of radiological reports.

Entities:  

Keywords:  Education; Head and neck cancer; NI-RADS; Squamous cell carcinoma; Surveillance

Mesh:

Year:  2021        PMID: 34233509      PMCID: PMC8693328          DOI: 10.1259/dmfr.20210168

Source DB:  PubMed          Journal:  Dentomaxillofac Radiol        ISSN: 0250-832X            Impact factor:   2.419


  17 in total

1.  Comparisons of predictive values of binary medical diagnostic tests for paired designs.

Authors:  W Leisenring; T Alonzo; M S Pepe
Journal:  Biometrics       Date:  2000-06       Impact factor: 2.571

2.  Implementation of a Novel Surveillance Template for Head and Neck Cancer: Neck Imaging Reporting and Data System (NI-RADS).

Authors:  Ashley H Aiken; April Farley; Kristen L Baugnon; Amanda Corey; Mark El-Deiry; Richard Duszak; Jonathan Beitler; Patricia A Hudgins
Journal:  J Am Coll Radiol       Date:  2015-11-11       Impact factor: 5.532

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

Authors:  Fabian H J Elsholtz; Patrick Asbach; Matthias Haas; Minerva Becker; Regina G H Beets-Tan; Harriet C Thoeny; Anwar R Padhani; Bernd Hamm
Journal:  Eur Radiol       Date:  2021-03-19       Impact factor: 5.315

Review 4.  Running a Radiology Residency Program: Strategies for Success.

Authors:  David S Sarkany; Anuradha S Shenoy-Bhangle; Tara M Catanzano; Tabitha A Fineberg; Ronald L Eisenberg; Priscilla J Slanetz
Journal:  Radiographics       Date:  2018-10       Impact factor: 5.333

5.  ACR Neck Imaging Reporting and Data Systems (NI-RADS): A White Paper of the ACR NI-RADS Committee.

Authors:  Ashley H Aiken; Tanya J Rath; Yoshimi Anzai; Barton F Branstetter; Jenny K Hoang; Richard H Wiggins; Amy F Juliano; Christine Glastonbury; C Douglas Phillips; Richard Brown; Patricia A Hudgins
Journal:  J Am Coll Radiol       Date:  2018-07-06       Impact factor: 5.532

6.  Effect of training on ultrasonography (US) BI-RADS features for radiology residents: a multicenter study comparing performances after training.

Authors:  Jung Hyun Yoon; Hye Sun Lee; You Me Kim; Ji Hyun Youk; Sung Hun Kim; Sun Hye Jeong; Ji Young Hwang; Jin Hee Moon; Young Mi Park; Min Jung Kim
Journal:  Eur Radiol       Date:  2019-01-07       Impact factor: 5.315

Review 7.  Neck Imaging Reporting and Data System.

Authors:  Ashley H Aiken; Patricia A Hudgins
Journal:  Magn Reson Imaging Clin N Am       Date:  2017-11-06       Impact factor: 2.266

8.  Multiparametric Magnetic Resonance Imaging Second Opinion May Reduce the Number of Unnecessary Prostate Biopsies: Time to Improve Radiologists' Training Program?

Authors:  Stefano Luzzago; Giuseppe Petralia; Gennaro Musi; Michele Catellani; Sarah Alessi; Ettore Di Trapani; Francesco A Mistretta; Alessandro Serino; Andrea Conti; Paola Pricolo; Sebastiano Nazzani; Vincenzo Mirone; Deliu-Victor Matei; Emanuele Montanari; Ottavio de Cobelli
Journal:  Clin Genitourin Cancer       Date:  2018-10-23       Impact factor: 2.872

9.  The Learning Curve in Prostate MRI Interpretation: Self-Directed Learning Versus Continual Reader Feedback.

Authors:  Andrew B Rosenkrantz; Abimbola Ayoola; David Hoffman; Anunita Khasgiwala; Vinay Prabhu; Paul Smereka; Molly Somberg; Samir S Taneja
Journal:  AJR Am J Roentgenol       Date:  2016-12-27       Impact factor: 3.959

Review 10.  Evaluation of cervical lymph nodes in head and neck cancer with CT and MRI: tips, traps, and a systematic approach.

Authors:  Jenny K Hoang; Jyotsna Vanka; Benjamin J Ludwig; Christine M Glastonbury
Journal:  AJR Am J Roentgenol       Date:  2013-01       Impact factor: 3.959

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.