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Article

How Using Dedicated Software Can Improve RECIST Readings

by
Amandine René
1,*,†,
Sophie Aufort
2,†,
Salim Si Mohamed
2,†,
Jean Pierre Daures
3,†,
Stéphane Chemouny
4,†,
Christophe Bonnel
4,† and
Benoit Gallix
5,†
1
University of Montpellier I & II/Intrasense SA, Montpellier 34000, France
2
Medical Imaging Service, Clinique du Parc, Castelnau-Le-Lez 34170, France
3
University of Montpellier I, Epidemiology Biostatistics and Public Health, IURC, Montpellier 34000, France
4
Intrasense, SA, 1231 Avenue du Mondial 98, Montpellier 34000, France
5
Department of Radiology, McGill University, Montréal, QC, Canada
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Informatics 2014, 1(2), 160-173; https://doi.org/10.3390/informatics1020160
Submission received: 31 March 2014 / Revised: 22 August 2014 / Accepted: 1 September 2014 / Published: 8 September 2014
(This article belongs to the Special Issue Biomedical Imaging and Visualization)

Abstract

Decision support tools exist for oncologic follow up. Their main interest is to help physicians improve their oncologic readings but this theoretical benefit has to be quantified by concrete evidence. The purpose of the study was to evaluate and quantify the impact of using dedicated software on RECIST readings. A comparison was made between RECIST readings without dedicated application vs. readings using dedicated software (Myrian® XL-Onco, Intrasense, France) with specific functionalities such as 3D elastic target matching and automated calculation of tumoral response. A retrospective database of 40 patients who underwent a CT scan follow up was used (thoracic/abdominal lesions). The reading panel was composed of two radiologists. Reading times, intra/inter-operator reproducibility of measurements and RECIST response misclassifications were evaluated. On average, reading time was reduced by 49.7% using dedicated software. A more important saving was observed for lung lesions evaluations (63.4% vs. 36.1% for hepatic targets). Inter and intra-operator reproducibility of measurements was excellent for both reading methods. Using dedicated software prevented misclassifications on 10 readings out of 120 (eight due to calculation errors). The use of dedicated oncology software optimises RECIST evaluation by decreasing reading times significantly and avoiding response misclassifications due to manual calculation errors or approximations.
Keywords: software evaluation; oncology; follow-up; clinical research; daily routine; workflow improvement; efficiency; decision support software software evaluation; oncology; follow-up; clinical research; daily routine; workflow improvement; efficiency; decision support software
Graphical Abstract

Share and Cite

MDPI and ACS Style

René, A.; Aufort, S.; Mohamed, S.S.; Daures, J.P.; Chemouny, S.; Bonnel, C.; Gallix, B. How Using Dedicated Software Can Improve RECIST Readings. Informatics 2014, 1, 160-173. https://doi.org/10.3390/informatics1020160

AMA Style

René A, Aufort S, Mohamed SS, Daures JP, Chemouny S, Bonnel C, Gallix B. How Using Dedicated Software Can Improve RECIST Readings. Informatics. 2014; 1(2):160-173. https://doi.org/10.3390/informatics1020160

Chicago/Turabian Style

René, Amandine, Sophie Aufort, Salim Si Mohamed, Jean Pierre Daures, Stéphane Chemouny, Christophe Bonnel, and Benoit Gallix. 2014. "How Using Dedicated Software Can Improve RECIST Readings" Informatics 1, no. 2: 160-173. https://doi.org/10.3390/informatics1020160

APA Style

René, A., Aufort, S., Mohamed, S. S., Daures, J. P., Chemouny, S., Bonnel, C., & Gallix, B. (2014). How Using Dedicated Software Can Improve RECIST Readings. Informatics, 1(2), 160-173. https://doi.org/10.3390/informatics1020160

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