165P - Preoperative positron emission tomography fractal biopsy of thymic epithelial neoplasm

Date 17 April 2015
Event ELCC 2015
Session Poster lunch
Topics Thymoma and Thymic Cancer
Imaging, Diagnosis and Staging
Presenter Luca Bertolaccini
Citation Annals of Oncology (2015) 26 (suppl_1): 51-54. 10.1093/annonc/mdv053
Authors L. Bertolaccini1, G. Felloni2, M. Salgarello2, A. Viti3, A. Bianchi4, A. Terzi1
  • 1Thoracic Surgery, Sacro Cuore - Don Calabria Research Hospital, 37024 - Negrar Verona/IT
  • 2Nuclear Medicine, Sacro Cuore - Don Calabria Research Hospital, 37024 - Negrar Verona/IT
  • 3Thoracic Surgery, Azienda Ospedaliera St. Croce e Carle, 12100 - Cuneo/IT
  • 4Nuclear Medicine, Azienda Ospedaliera St. Croce e Carle, 12100 - Cuneo/IT

Abstract

Aim/Background

To determine whether fractal analysis of FDG PET uptake, that quantifies tumor complexity and heterogeneity, helps or not preoperative identification of Low Risk (LR) Thymic Epithelial Neoplasm (TEN) & High Risk (HR) TEN.

Methods

Retrospective cohort of 26 consecutive patients with pathologically proven TEN, categorized according to WHO classification. PET Standardized Uptake Value Tumor/Mediastinum (SUV T/M) ratio was calculated. Fractal geometry, characterized by relationship between measure (M), scale (ϵ), scaling constant (k), self-affinity dimension (D), was used: M(ϵ) = kϵ−D. Cutoffs were ruler ϵ, voxels (radioactivity > cutoff) were M(ϵ), pixels were D. Morphological Fractal Dimension (m-FD), quantitative index of morphological complexity, and density Fractal Dimension (d-FD), expression of FDG distribution heterogeneity, were calculated. Comparison of SUV T/M, m-FD, d-FD between LR TEN & HR TEN was performed with unpaired t – test. Pearson's correlation coefficients evaluated relationships. Values plotted nearest upper left corner from Receiver Operating Characteristics (ROC) analyses indicated best diagnostic accuracy. Sensitivity, specificity, accuracy were calculated, using appropriate cutoffs. Diagnostic accuracy was compared using Areas under ROC Curves (AUC); ROC curves were compared using critical z test. Significance level was set to 0.05.

Results

SUV T/M ratio and d-FD highly correlate with stage (SUV T/M: r = 0.71, p = 0.0001; d-FD: r = 0.70, p = 0.0001) and classes of risk (SUV T/M: r = 0.83, p < 0.0001; d-FD: r = 0.76, p < 0.0001). Cutoff values were: SUV T/M = 2.63, m-FD = 0.031, d-FD = 0.584. Combined use of PET parameters for differential diagnosis was examined: pooled d-FD with SUV T/M improved accuracy to 89%.

Distribution of PET parameters

WHO Classification SUV T/M m-DF d-DF
- Type a (#3, 11.5%) 1.82 ± 0.63 0.024 ± 0.004 0.099 ± 0.091
- Type ab (#11, 42.3%) 1.86 ± 0.43 0.029 ± 0.007 0.256 ± 0.247
- Type b1 (#5, 19.3%) 1.99 ± 0.49 0.030 ± 0.011 0.246 ± 0.399
- Type b2 (#3, 11.5%) 4.33 ± 0.91 0.036 ± 0.001 0.979 ± 0.176
- Type b3 (#4, 15.4%) 3.59 ± 1.05 0.037 ± 0.014 0.793 ± 0.163
Classes of Risk * SUV T/M m-DF d-DF
- Low Risk (#19, 73.1%) 1.89 ± 0.45 0.028 ± 0.008 0.228 ± 0.251
- High Risk (#7, 26.9%) 3.91 ± 0.99 0.037 ± 0.012 0.872 ± 0.183
Comparison of Diagnostic Ability SUV T/M m-DF d-DF
- AUC 0.974 0.737 0.947
- Cutoff 2.63 0.031 0.584
- Sensitivity (%) 92.11 42.11 89.47
- Specificity (%) 85.71 57.14 78.57
- Accuracy (%) 84.62 53.85 80.77

* Low Risk included thymoma types a, ab and b1; High Risk included thymoma types b2 and b3

Conclusions

d-FD and SUV T/M provided information useful to predict histology and classes of risk. Heterogeneity of PET FDG uptake evaluated by fractal analysis was useful to discriminate preoperatively LR TEN from HR TEN.

Disclosure

All authors have declared no conflicts of interest.