Association of Tumor [18F]FDG Activity and Diffusion Restriction with Clinical Outcomes of Rhabdomyosarcomas
To evaluate whether the extent of restricted diffusion and 2-deoxy-2-[18F] fluoro-d-glucose ([18F]FDG) uptake of pediatric rhabdomyosarcomas (RMS) on positron emission tomography (PET)/magnetic resonance (MR) images provides prognostic information.
In a retrospective, IRB-approved study, we evaluated [18F]FDG PET/CT and diffusion-weighted (DW) MR imaging studies of 21 children and adolescents (age 1–20 years) with RMS of the head and neck. [18F]FDG PET and DW MR scans at the time of the initial tumor diagnosis were fused using MIM software. Quantitative measures of the tumor mass with restricted diffusion, [18F]FDG hypermetabolism, or both were dichotomized at the median and tested for significance using Gray’s test. Data were analyzed using a survival analysis and competing risk model with death as the competing risk.
[18F]FDG PET/MR images demonstrated a mismatch between tumor areas with increased [18F]FDG uptake and restricted diffusion. The DWI, PET, and DWI + PET tumor volumes were dichotomized at their median values, 23.7, 16.4, and 9.5 cm3, respectively, and were used to estimate survival. DWI, PET, and DWI + PET overlap tumor volumes above the cutoff values were associated with tumor recurrence, regardless of post therapy COG stage (p = 0.007, p = 0.04, and p = 0.07, respectively).
The extent of restricted diffusion within RMS and overlap of hypermetabolism plus restricted diffusion predict unfavorable clinical outcomes.
Key wordsRhabdomyosarcoma [18F]FDG Diffusion-weighted MR PET/MR
We thank the members of Daldrup-Link lab for the valuable input and discussions regarding this project.
This work was supported by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, grant number R01 HD081123.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the Institutional Review Board at our institution and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.”
- 3.Rodeberg DA, Stoner JA, Hayes-Jordan A, Kao SC, Wolden SL, Qualman SJ, Meyer WH, Hawkins DS (2009) Prognostic significance of tumor response at the end of therapy in group III rhabdomyosarcoma: a report from the children’s oncology group. J Clin Oncol 27:3705–3711CrossRefPubMedPubMedCentralGoogle Scholar
- 10.Padhani AR, Liu G, Mu-Koh D, Chenevert TL, Thoeny HC, Takahara T, Dzik-Jurasz A, Ross BD, van Cauteren M, Collins D, Hammoud DA, Rustin GJS, Taouli B, Choyke PL (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125CrossRefPubMedPubMedCentralGoogle Scholar
- 13.Ferrari A, Miceli R, Meazza C, Casanova M, Favini F, Morosi C, Trecate G, Marchianò A, Luksch R, Cefalo G, Terenziani M, Spreafico F, Polastri D, Podda M, Catania S, Schiavello E, Giannatempo P, Gandola L, Massimino M, Mariani L (2010) Comparison of the prognostic value of assessing tumor diameter versus tumor volume at diagnosis or in response to initial chemotherapy in rhabdomyosarcoma. J Clin Oncol 28:1322–1328CrossRefPubMedGoogle Scholar
- 14.Ries LAG SM, Gurney JG, Linet M, et al. (2005) Cancer incidence and survival among children and adolescents. National Cancer Institute, SEER ProgramGoogle Scholar
- 16.Bakhshi S, Radhakrishnan V, Sharma P, Kumar R, Thulkar S, Vishnubhatla S, Dhawan D, Malhotra A (2012) Pediatric nonlymphoblastic non-Hodgkin lymphoma: baseline, interim, and posttreatment PET/CT versus contrast-enhanced CT for evaluation—a prospective study. Radiology 262:956–968CrossRefPubMedGoogle Scholar
- 24.Gupta K, Pawaskar A, Basu S, Rajan MGR, Asopa RV, Arora B, Nair N, Banavali S (2011) Potential role of FDG PET imaging in predicting metastatic potential and assessment of therapeutic response to neoadjuvant chemotherapy in Ewing sarcoma family of tumors. Clin Nucl Med 36:973–977CrossRefPubMedGoogle Scholar
- 26.Kurland BF, Muzi M, Peterson LM, Doot RK, Wangerin KA, Mankoff DA, Linden HM, Kinahan PE (2016) Multicenter clinical trials using 18F-FDG PET to measure early response to oncologic therapy: effects of injection-to-acquisition time variability on required sample size. J Nucl Med 57:226–230CrossRefPubMedGoogle Scholar
- 27.Antonica F, Asabella AN, Ferrari C et al (2014) Useful diagnostic biometabolic data obtained by PET/CT and MR fusion imaging using open source software. Hellenic. J Nucl Med 17(Suppl 1):50–55Google Scholar