scholarly journals Usefulness of FDG-PET/CT-Based Radiomics for the Characterization and Genetic Orientation of Pheochromocytomas Before Surgery

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2424
Author(s):  
Catherine Ansquer ◽  
Delphine Drui ◽  
Eric Mirallié ◽  
Karine Renaudin-Autain ◽  
Antoine Denis ◽  
...  

Purpose: To assess the potential added value of FDG-PET/CT radiomics for the characterization of pheochromocytomas (PHEO) and their genetic orientation prior to surgery and genetic testing. Methods: This retrospective monocentric study, included 49 patients (52 tumors) that underwent both FDG-PET/CT and MIBG scan before surgery. A germline mutation was secondarily identified in 13 patients in one of the genes related to Cluster 1 (n = 4) or Cluster 2 (n = 9). No mutation was identified in 32 patients and 4 did not have genetic testing. Correlation between several PET-based biomarkers, including SUVmax, metabolic tumor volume (MTV), total lesion glycolysis (TLG) and textural features, and biochemical and genetic features were analyzed. Results: Sensitivity of FDG-PET/CT alone was 92%, and 98% when combined to MIBG. The SUVmax was significantly higher for mutated tumors classified in Cluster 1 than in Cluster 2 (p = 0.002) or for tumors with no identified mutations (p = 0.04). MTV and TLG of the tumors with the most intense uptake discriminated mutated Cluster 2 from sporadic tumors, but not from Cluster 1 tumors. Textural features combined with MTV led to better differentiation between sporadic and mutated tumors (p < 0.05). Conclusion: FDG-PET/CT is useful for preoperative characterization of PHEO, and when combined with radiomics biomarkers, provides evidences for a genetic predisposition.

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 513.1-513
Author(s):  
T. Kameda ◽  
S. Nakashima ◽  
H. Shimada ◽  
R. Wakiya ◽  
M. Mahmoud Fahmy Mansour ◽  
...  

Background:Recently, there are many reports from Japan about methotrexate associated lymphoproliferative disorder (MTX-LPD). We are investigating the predictive factor of spontaneous regression (SR) in MTX-LPD. On the other hand, FDG-PET/CT is used for diagnosis of LPD including malignant lymphoma. In addition, it was reported that imaging biomarkers such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) could predict the prognosis of malignant tumor (1, 2). However, there is no report that these imaging biomarkers could predict the SR of MTX-LPD.Objectives:We investigate the usefulness of FDG-PET/CT for predictive factor of SR in MTX-LPD.Methods:We enrolled 24 RA patients who diagnosed MTX-LPD and performed FDG-PET/CT from 2005 to 2019. We divided these cases into spontaneous regression cases (SR group; 15 cases) and cases that treated with chemotherapy after MTX discontinuation (CTx group; 9 cases), and compared the difference as follow subjects between two groups; clinical data including histopathological findings, SUVmax to evaluate malignant tumor activity by FDG-PET/CT, MTV and TLG which refer to metabolically active volume of the tumor segmented FDG-PET/CT. In addition, we analyzed cut off levels, sensitivity and specificity using statistical software JMP.Results:Diffuse large B cell lymphoma (DLBCL) and Hodgkin lymphoma (HL) were 5 and 1 cases in SR group, and 1 and 5 cases in CTx group. In addition, MTV and TLG by FDG-PET/CT was significantly lower in SR group, although SUVmax is no difference between two groups (figure 1). Cut off levels of MTV and TLG were 103.12 ml (sensitivity; 88.9%, specificity; 86.7%) and 361.75 ml (sensitivity; 88.9%, specificity; 86.7%), respectively.Conclusion:We suggested that MTV and TLG were useful for predict of SR in MTX-LPD.References:[1]Chen HH, Chiu NT, Su WC. et al. Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer. Radiology. 2012 Aug;264(2):559-66.[2]Chu KP, Murphy JD, La TH. et al. Prognostic value of metabolic tumor volume and velocity in predicting head-and-neck cancer outcomes. Int J Radiat Oncol Biol Phys. 2012 Aug 1;83(5):1521-7.Figure 1.Comparison of the level of MTV(a) and TLG (b).Disclosure of Interests:None declared


2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 8555-8555 ◽  
Author(s):  
Ashley Knight-Greenfield ◽  
Richard Aaron Marshall ◽  
Martin Hutchings ◽  
John Doucette ◽  
Jamie Stern ◽  
...  

8555 Background: Previous studies in cHL have demonstrated that conventional methods to risk stratify patients into various prognostic groups and predict PFS may not be sufficient to individualize therapy. Metabolic parameters using FDG-PET may be helpful for developing a prognostic algorithm and predict PFS. Objectives: To determine the best predictor of PFS among various variables of tm metabolic measurements at baseline and at interim PET/CT compared to conventional methods in cHL patients. Methods: Retrospective evaluation of prospectively acquired data in 58 cHL pts, all stages [IIB-IV:41%, >IPS-3:24%, unfavorable (UF):44%]. Eligibility: PET/CT prior to and after 1 cycle (PET1) ABVD therapy, imaging at 60min+15min, follow-up>24 mo. Baseline PET parameters including metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, and SULpeak were determined using gradient method (PETVCAR2, GE Healthcare, WI). Data were also evaluated at PET1 for %ΔMTV, %ΔSUVmax, %ΔTLG, PERCIST criteria and visually with Deauville 5-PS. Variables were correlated with PFS. Results: Median follow-up: 32.2 mo. Of 58 pts 14 relapsed (median PFS:6.5 mo). Results for PFS are displayed in the Table. No baseline conventional (stage, IPS, UF vs F) or PET variable was associated with PFS. The best predictor of PFS was Deauville 5-PS at PET1. PERCIST and %ΔTLG using gradient method trended toward significance. Conclusions: Deauville 5-PS best predicts PFS at PET1 in cHL. Neither baseline PET nor conventional prognostic factors correlated with PFS in this group of cHL pts. Risk-stratification of cHL using tumor metabolic volumetry and PERCIST criteria may require a larger sample size and further assessment of various methodologies. [Table: see text]


2019 ◽  
Vol 40 (11) ◽  
pp. 1099-1104
Author(s):  
Mehmet Erdogan ◽  
Evrim Erdemoglu ◽  
Şehnaz Evrimler ◽  
Candost Hanedan ◽  
Sevim S. Şengül

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