Clear cell renal cell carcinoma (ccRCC), the most common malignant renal neoplasm, is associated with lower disease-free survival and cancer-specific survival compared to other renal cell carcinomas [1,2]. Previous studies have highlighted the association between tumor angiogenesis, prognosis, and ability to metastasize [3]. Intratumor heterogeneity, however, is characteristically present in ccRCC [4] and likely drives the biological behavior of this disease. Moreover, assessment of intratumor heterogeneity ex vivo is challenged by the need to obtain multiple tissue samples in the same tumor. Arterial spin-labeled (ASL) perfusion MRI and diffusion-weighted imaging (DWI) allow direct quantification of blood flow and tissue diffusion, respectively, of the whole tumor [5,6]. The goal of this study was to investigate intratumor heterogeneity of perfusion and diffusion in vivo in ccRCC using ASL and DWI, and to correlate these measures with tumor vascularity and cellularity at histopathology.

All patients were consented to participate in this prospective, IRB-approved, HIPPA-compliant study. Twenty three ccRCCs were included in this report (16 men, 7 women, age 60±10 years). Prior to surgery (range 1-11 days), patients underwent 3T MRI with a 16-channel SENSE-XL-Torso coil (Achieva, Philips Healthcare, Best, The Netherlands). Coronal and axial T2-weighted (T2W) images were acquired followed by 2D coronal ASL imaging through the center of the tumor using pseudo-continuous labeling (pCASL) of the upper abdominal aorta (16 pairs of label-control) with background suppression, timed breathing, and single-shot turbo spin-echo readout [7]. Coronal DWI of both kidneys was acquired using a respiratory-triggered single-shot spin-echo echo-planar sequence with diffusion-weighted gradient applied in three orthogonal directions and b-values of 0, 50, 100, 200, 450, 600, and 1000 s/mm². Quantitative ASL perfusion maps were reconstructed from the complex k-space raw data using offline MATLAB code. Two regions of interest (ROIs), each about 1 cm², were manually drawn using a DICOM viewer (OsiriX) on the perfusion maps to measure high and low perfusion within the same tumor and then manually duplicated on the DWI for all b-values. ROI-based quantitative diffusion measurements were calculated using custom-written programs in MATLAB: (1) apparent diffusion coefficient (ADC) from monoexponential model; (2) tissue diffusion coefficient (D_t), pseudodiffusion coefficient (D_p), and perfusion fraction (f_p) from intravoxel incoherent motion (IVIM) model.

Histopathologic analysis served as the reference standard for all tumors. After partial (n=14) or radical (n=9) nephrectomy, tissue specimens were oriented using fiducial markers placed during surgery to match the anatomic orientation in vivo and subsequently bivalved to match the ASL acquisition. A tumor slab of the center of the tumor was obtained. CD31 and CD34 immunostains were used to measure the microvessel density (MVD) in high and low perfusion areas of the specimen matching the ROIs on MRI. Tumor cellularity was measured by manually counting the number of tumor cells within an area of 5,250,000 μm² in the same locations of the tumor. General linear mixed models were used to evaluate intratumor heterogeneity of perfusion and diffusion on MRI, and tumor vascularity and cellularity on histopathology. Spearman correlations between these quantitative measures were investigated. P<0.05 was considered statistically significant.

Representative MRI and corresponding pathology images of a ccRCC with Fuhrman Grade 2 are shown in Figure 1. ASL perfusion, tumor cellularity and vascularity from high and low perfusion areas were significantly different across all tumors (Table 1). However quantitative diffusion parameters did not show significant intratumor difference across all patients. Spearman test demonstrated: (1) a positive correlation between tumor cellularity and MVD from CD31 in tissue measurements; (2) a positive correlation between MVD from CD31 and CD34; (3) positive correlations between ASL perfusion and both cellularity, and MVD CD31; and (4) a negative correlation between tissue diffusion coefficient, D_t, and cellularity (Figure 2).The formation of new blood vessels, or tumor angiogenesis, is essential in tumor growth and metastasis. In our study, ccRCC demonstrated intratumor heterogeneity of blood flow on ASL imaging. Histopathologic analysis of tumor areas corresponding to high perfusion regions on ASL confirmed higher MVD and demonstrated higher cellularity compared to tumor areas with low perfusion on ASL. A negative correlation between in vivo MRI diffusion measures and tissue cellularity measurements further supports the use of these MRI techniques for assessment of heterogeneity in tumor angiogenesis and microenvironment in vivo.To our knowledge, this is the first demonstration of a correlation between tumor vascularity and cellularity in ccRCC. We confirm previous observations of a negative correlation between tumor diffusion and cellularity. Our MRI-directed tissue analysis provides a basis for exploring molecular alterations that drive tumor proliferation.