title: Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification.
abstract: In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.0), with a short-TE classifier, provided the best results. Since then, the DSS evolved into a version 2.0 that contains an additional long-TE classifier. This study has two objectives. First, to determine whether clinicians with no experience of spectroscopy are comparable with spectroscopists in the use of the system, when only minimum training in the use of the system was given. Second, to assess whether or not a version with another TE is better than the initial version. We undertook a second study with the same cases and nine evaluators to assess whether the diagnostic accuracy of DSS 2.0 was comparable with the values obtained with DSS 1.0. In the second study, the analysis protocol was flexible in comparison with the first one to mimic a clinical environment. In the present study, on average, each case required 5.4 min by neuroradiologists and 9 min by spectroscopists for evaluation. Most classes and superclasses of tumours gave the same results as with DSS 1.0, except for astrocytomas of World Health Organization (WHO) grade III, in which performance measured as the area under the curve (AUC) decreased: AUC = 0.87 (0.72-1.02) with DSS 1.0 and AUC = 0.62 (0.55-0.70) with DSS 2.0. When analysing the performance of radiologists and spectroscopists with respect to DSS 1.0, the results were the same for most classes. Having data with two TEs instead of one did not affect the results of the evaluation.
authors.affiliation: Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain; Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, UAB, Cerdanyola del Vallès, Spain; Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, UAB, Cerdanyola del Vallès, Spain.
authors.forename: Margarida
authors.initials: M
authors.lastname: Julià-Sapé
authors.forename: Carles
authors.initials: C
authors.lastname: Majós
authors.forename: Àngels
authors.initials: À
authors.lastname: Camins
authors.forename: Alejandro
authors.initials: A
authors.lastname: Samitier
authors.forename: Miguel
authors.initials: M
authors.lastname: Baquero
authors.forename: Marta
authors.initials: M
authors.lastname: Serrallonga
authors.forename: Sira
authors.initials: S
authors.lastname: Doménech
authors.forename: Elisenda
authors.initials: E
authors.lastname: Grivé
authors.forename: Franklyn A
authors.initials: FA
authors.lastname: Howe
authors.forename: Kirstie
authors.initials: K
authors.lastname: Opstad
authors.forename: Jorge
authors.initials: J
authors.lastname: Calvar
authors.forename: Carles
authors.initials: C
authors.lastname: Aguilera
authors.forename: Carles
authors.initials: C
authors.lastname: Arús
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D001932:Brain Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism*; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods; D066244:Proton Magnetic Resonance Spectroscopy / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013030:Spain
chemical_list: D014408:Biomarkers, Tumor
keywords: MRI; MRS; ROC curve; brain neoplasms; diagnosis, computer-assisted; diagnostic techniques and procedures