title: Diffusion-weighted magnetic resonance imaging of thymoma: ability of the Apparent Diffusion Coefficient in predicting the World Health Organization (WHO) classification and the Masaoka-Koga staging system and its prognostic significance on disease-free survival.
abstract: OBJECTIVE
  To evaluate the usefulness of diffusion-weighted magnetic resonance for distinguishing thymomas according to WHO and Masaoka-Koga classifications and in predicting disease-free survival (DFS) by using the apparent diffusion coefficient (ADC).
  
  
  METHODS
  Forty-one patients were grouped based on WHO (low-risk vs. high-risk) and Masaoka-Koga (early vs. advanced) classifications. For prognosis, seven patients with recurrence at follow-up were grouped separately from healthy subjects. Differences on ADC levels between groups were tested using Student-t testing. Logistic regression models and areas under the ROC curve (AUROC) were estimated.
  
  
  RESULTS
  Mean ADC values were different between groups of WHO (low-risk = 1.58 ± 0.20 × 10(-3)mm(2)/sec; high-risk = 1.21 ± 0.23 × 10(-3)mm(2)/sec; p < 0.0001) and Masaoka-Koga (early = 1.43 ± 0.26 × 10(-3)mm(2)/sec; advanced = 1.31 ± 0.31 × 10(-3)mm(2)/sec; p = 0.016) classifications. Mean ADC of type-B3 (1.05 ± 0.17 × 10(-3)mm(2)/sec) was lower than type-B2 (1.32 ± 0.20 × 10(-3)mm(2)/sec; p = 0.023). AUROC in discriminating groups was 0.864 for WHO classification (cut-point = 1.309 × 10(-3)mm(2)/sec; accuracy = 78.1 %) and 0.730 for Masaoka-Koga classification (cut-point = 1.243 × 10(-3)mm(2)/sec; accuracy = 73.2 %). Logistic regression models and two-way ANOVA were significant for WHO classification (odds ratio[OR] = 0.93, p = 0.007; p < 0.001), but not for Masaoka-Koga classification (OR = 0.98, p = 0.31; p = 0.38). ADC levels were significantly associated with DFS recurrence rate being higher for patients with ADC ≤ 1.299 × 10(-3)mm(2)/sec (p = 0.001; AUROC, 0.834; accuracy = 78.0 %).
  
  
  CONCLUSIONS
  ADC helps to differentiate high-risk from low-risk thymomas and discriminates the more aggressive type-B3. Primary tumour ADC is a prognostic indicator of recurrence.
  
  
  CONCLUSIONS
  • DW-MRI is useful in characterizing thymomas and in predicting disease-free survival. • ADC can differentiate low-risk from high-risk thymomas based on different histological composition • The cutoff-ADC-value of 1.309 × 10 (-3) mm (2) /sec is proposed as optimal cut-point for this differentiation • The ADC ability in predicting Masaoka-Koga stage is uncertain and needs further validations • ADC has prognostic value on disease-free survival and helps in stratification of risk.
authors.affiliation: Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy. adriano.priola@inwind.it.
authors.forename: Adriano Massimiliano
authors.initials: AM
authors.lastname: Priola
authors.affiliation: Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Sandro Massimo
authors.initials: SM
authors.lastname: Priola
authors.affiliation: Department of Mathematics "Giuseppe Peano", University of Torino, Via Carlo Alberto 10, 10123, Torino, Italy.
authors.forename: Maria Teresa
authors.initials: MT
authors.lastname: Giraudo
authors.affiliation: Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Dario
authors.initials: D
authors.lastname: Gned
authors.affiliation: Department of Pathology, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Fornari
authors.affiliation: Department of Neurology, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Bruno
authors.initials: B
authors.lastname: Ferrero
authors.affiliation: Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Lorena
authors.initials: L
authors.lastname: Ducco
authors.affiliation: Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Veltri
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D012189:Retrospective Studies; D013945:Thymoma / Q000000981:diagnostic imaging* / Q000473:pathology*; D013953:Thymus Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D014944:World Health Organization
keywords: Apparent diffusion coefficient; Diffusion-weighted magnetic resonance imaging; Masaoka-Koga staging system; Thymoma; WHO classification