Can 18F FDG PET/CT metabolic parameters be used to noninvasively differentiate between different histopathological subtypes and Fuhrman grades of renal cell cancer?

Author:

Jain Yash1,Agrawal Archi1,Joshi Amit2,Menon Santosh3,Prakash Gagan4,Murthy Vedang5,Purandare Nilendu1,Shah Sneha1,Puranik Ameya1,Choudhury Sayak1,Shukla Varun6,Dev Indraja1,Prabhash Kumar2,Noronha Vanita2,Rangarajan Venkatesh1

Affiliation:

1. Department of Nuclear Medicine and Moleular Imaging, Tata Memorial Hospital, Homi Bhabha National Institute,

2. Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute,

3. Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute,

4. Department of Uro Oncology, Tata Memorial Hospital, Homi Bhabha National Institute,

5. Department of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai and

6. Department of Nuclear Medicine and Molecular imaging, Mahamana Pandit Madan Mohan Malviya Cancer Center, Tata Memorial Centre, Homi Bhabha National Institute, India

Abstract

Aim To evaluate relationship between metabolic PET metabolic parameters and size of the primary tumor, various histopathological subtypes of renal cell carcinoma (RCC) and Fuhrman grade of the tumors. Material and methods Retrospective analysis of 93 biopsy-proven RCC patients who underwent pretreatment flourine 18 flourodeoxyglucose PET/computed tomography (18F FDG PET/CT) was performed. Quantitative PET parameters, size of the primary tumor, histopathological subtypes and Fuhrman grades of the tumor were extracted. We tried to assess if there was any significant difference in the metabolic patterns of various histopathological subtypes of RCCs, Fuhrman grade of the tumors and size of the primary tumor. Results A significant correlation was noted between the size of primary tumor and maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) (P < 0.01, P < 0.001 and P < 0.001, respectively). SUVmax values correlated significantly with the histopathological subtype (P < 0.001). Further sub-analyses was also done by segregating the patients into Low grade (Fuhrman grade 1 and 2) vs. High grade (Fuhrman grade 3 and 4). SUVmax, MTV and TLG were significantly different between high grade vs. low grade tumors. ROC analysis yielded cut off values for SUVmax, MTV and TLG to differentiate between high grade from low grade tumors. Conclusion FDG PET/CT with the use of metabolic PET parameters can differentiate between different histopathological subtypes of RCC. Incorporation of metabolic parameters into clinical practice can potentially noninvasively identify patients with low-grade vs. high-grade RCC.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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