Assessment of Apparent Diffusion Coefficients and SUVs as Predicators of Histological Differentiation in Anal Squamous Cell Carcinoma.

Aim: The study aims to assess minimal apparent diffusion coefficient (ADCmin) and SUVmax as predictors of histological differentiation in patients with anal squamous cell carcinoma (ASCC) and to determine cutoff values for each histopathological tumor grade.

Patients And Methods: A retrospective study of 41 ASCC patients (14 males, 27 females; mean age, 65 ± 13 years) staged with FDG PET/CT and MRI (mean scan time interval, 21 ± 11 days). SUVmax and ADCmin values were measured and compared with histopathological tumor grading obtained from biopsy.

Results: The mean size and tumor volume were 3 ± 2 cm and 16.5 ± 27.3 cm3, respectively. The mean ADCmin values for well-, moderately, and poorly differentiated ASCC were 935 ± 179, 896 ± 123, and 637 ± 114, respectively. The mean SUVmax for well-, moderately, and poorly differentiated ASCC were 6.9 ± 1.8, 11.5 ± 4.1, and 13.4 ± 2.6, respectively. The difference in mean ADCmin values between poorly and moderately/well-differentiated tumors was statistically significant, whereas this was not significant between moderately and well-differentiated tumors. Differences in SUVmax values were statistically significant between poorly/moderately and well-differentiated tumors, whereas there was no statistical significance between poorly and moderately differentiated tumors. By combining the 2 modalities using cutoff values of 675 × 10-6 mm2·s-1 for ADCmin and 8.5 for SUVmax, it was possible to differentiate the tumor categories with a sensitivity, specificity, positive predictive value, and negative predictive value, respectively, of 84.6%, 96.4%, 91.7%, and 93.1% for well-differentiated ASCC, 76.5%, 87.5%, 81.3%, and 84% for moderately, and 90.9%, 89.3%, 76.9%, and 96.2% for poorly differentiated ASCC, respectively.

Conclusions: ADCmin and SUVmax values correlated with the degree of differentiation in ASCC and can be used as predictors of tumor grading and aggressiveness. Combined ADCmin and SUVmax cutoff values can therefore be used for early patient risk stratification and treatment decision making.