Koichi Hayano1, Sang Ho Lee2, Hiroyuki Yoshida2, Andrew X Zhu3, Dushyant V Sahani4. 1. Department of Radiology, Division of Abdominal Imaging and Intervention, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114. Electronic address: khayano@partners.org. 2. Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts. 3. Cancer Center, Massachusetts General Hospital, Boston, Massachusetts. 4. Department of Radiology, Division of Abdominal Imaging and Intervention, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114.
Abstract
RATIONALE AND OBJECTIVES: Tumor vascular heterogeneity is a recognized biomarker for cancer progression. Our purpose was to assess the tumor perfusion heterogeneity during antiangiogenic therapy in hepatocellular carcinoma (HCC) by means of fractal analysis on computed tomography perfusion (CTP) images. MATERIALS AND METHODS: Twenty-two patients (15 men and 7 women; mean age: 61.5 years) with advanced HCC underwent CTP at baseline and 2 weeks after administration of bevacizumab. Perfusion maps of blood flow (BF) were generated by the adiabatic approximation to the tissue homogeneity model with a motion registration, and fractal analyses were applied to gray-scale perfusion maps using a plugin tool on ImageJ software (NIH, Bethesda, MD). A differential box-counting method was applied, and the fractal dimension (FD) was calculated as a heterogeneity parameter. RESULTS: Patients were grouped into favorable progression-free survival (PFS) group (PFS>6 months, 11 patients) and unfavorable PFS group (PFS≤6, 11 patients). After 2 weeks of antiangiogenic therapy, the BF decreased significantly (P < .0001), whereas the FD showed no significant change (P = .69). The percent change of the FD in tumor BF was significantly different between patients with favorable PFS and those without (-2.52% vs. 3.72%, P = .01), whereas the change of tumor BF showed no significant difference between them (-28.93% vs. -25.47%, P = .64). In Kaplan-Meier analysis, patients with greater reduction in the percent change of FD and lower baseline FD in tumor BF showed significantly longer overall survival (P = .009, P = .005). CONCLUSIONS: Fractal analysis of tumor BF can be a biomarker for antiangiogenic therapy.
RATIONALE AND OBJECTIVES:Tumor vascular heterogeneity is a recognized biomarker for cancer progression. Our purpose was to assess the tumor perfusion heterogeneity during antiangiogenic therapy in hepatocellular carcinoma (HCC) by means of fractal analysis on computed tomography perfusion (CTP) images. MATERIALS AND METHODS: Twenty-two patients (15 men and 7 women; mean age: 61.5 years) with advanced HCC underwent CTP at baseline and 2 weeks after administration of bevacizumab. Perfusion maps of blood flow (BF) were generated by the adiabatic approximation to the tissue homogeneity model with a motion registration, and fractal analyses were applied to gray-scale perfusion maps using a plugin tool on ImageJ software (NIH, Bethesda, MD). A differential box-counting method was applied, and the fractal dimension (FD) was calculated as a heterogeneity parameter. RESULTS:Patients were grouped into favorable progression-free survival (PFS) group (PFS>6 months, 11 patients) and unfavorable PFS group (PFS≤6, 11 patients). After 2 weeks of antiangiogenic therapy, the BF decreased significantly (P < .0001), whereas the FD showed no significant change (P = .69). The percent change of the FD in tumor BF was significantly different between patients with favorable PFS and those without (-2.52% vs. 3.72%, P = .01), whereas the change of tumor BF showed no significant difference between them (-28.93% vs. -25.47%, P = .64). In Kaplan-Meier analysis, patients with greater reduction in the percent change of FD and lower baseline FD in tumor BF showed significantly longer overall survival (P = .009, P = .005). CONCLUSIONS: Fractal analysis of tumor BF can be a biomarker for antiangiogenic therapy.
Authors: Frances E Lennon; Gianguido C Cianci; Nicole A Cipriani; Thomas A Hensing; Hannah J Zhang; Chin-Tu Chen; Septimiu D Murgu; Everett E Vokes; Michael W Vannier; Ravi Salgia Journal: Nat Rev Clin Oncol Date: 2015-07-14 Impact factor: 66.675
Authors: Toru Tochigi; Sophia C Kamran; Anushri Parakh; Yoshifumi Noda; Balaji Ganeshan; Lawrence S Blaszkowsky; David P Ryan; Jill N Allen; David L Berger; Jennifer Y Wo; Theodore S Hong; Avinash Kambadakone Journal: Eur Radiol Date: 2021-10-13 Impact factor: 7.034