Radiomics in Kidney Cancer: MR Imaging

Abstract

Renal tumors encompass a heterogeneous disease spectrum, which confounds patient management and treatment. Percutaneous biopsy is limited by an inability to sample every part of the tumor. Radiomics may provide detail beyond what can be achieved from human interpretation. Understanding what new technologies offer will allow radiologists to play a greater role in caring for patients with renal cell carcinoma. In this article, we review the use of radiomics in renal cell carcinoma, in both the pretreatment assessment of renal masses and posttreatment evaluation of renal cell carcinoma, with special emphasis on the use of multiparametric MR imaging datasets.

Keywords: Kidney cancer; MR imaging; Quantitative imaging; Radiomics.

Figure 1.. Schematic representation of the goal of image-based analysis in kidney cancer.

Imaging provides analysis of the entire tumor and virtually every metastatic lesion in the patient. The imaging phenotype in the primary tumor and metastatic lesions may correlate to specific underlying molecular alteration (e.g. mutation status), which can be confirmed with genomics or immunohistochemistry during histopathologic evaluation. Mining of imaging data (radiomics) offers the opportunity to correlate objective, quantitative in vivo data with datasets generated with tissue-based analyses such as histopathology, genetic data (radiogenomics), metabolomics data (radiometabolomics), and potentially others. The spatial co-localization of imaging data with tissue-based data provides an avenue to address tumor heterogeneity in kidney cancer. H&E: Haemotoxylin and Eosin. PBRM1: polybromo 1. BAP1: BRCA1-Associated Protein 1; WT, wild-type

Figure 2.. Example of Haralick texture features using a 3 gray level image.

In this example, a 4×4 image with 3 gray levels is assessed (A). The first step in is constructing a gray-level co-occurrence matrix (GLCM) in a specified direction (B); in this example, a 45° degree (diagonal) direction is used. The value of the reference voxel (i) establishes the appropriate row, and the value of the neighbor pixel (j) determines the column. In this example, for the reference value of 0, the co-occurrence of a neighbor pixel of 0 in the 45° degree is 3 (annotated by the green arrows), and for a reference value of 2, the co-occurrence with a neighbor pixel of 1 is 2 (annotated by the red arrows). The GLCM can then be normalized by the sum of the elements to generate a probability of each combination to occur in the image (C). Haralick statistical features can then be subsequently extracted from the region of interest.

Figure 3.. Use of tumor enhancement characteristics on MRI to guide treatment.

Biopsy of renal mass (A) in patient presenting with a large tumor and inferior vena cava (IVC) thrombus and synchronous pulmonary metastases. Biopsy specimen was largely necrotic with only a small foci of high grade tumor with clear cytoplasm present on hematoxylin and eosin (top) exhibiting focal positive membranous staining with CAIX (bottom). Tumor was positive for PAX8 (not shown). The possibility of clear cell RCC was considered and antiangiogenic therapy with sunitinib was recommended. MRI was performed to assess the possibility of debulking nephrectomy. Multiphasic contrast-enhanced MRI (B) showed a large right renal mass and IVC thrombus, both exhibiting very low level progressive enhancement. Quantitative analysis of renal mass enhancement relative to the renal cortex (C) was performed and found to be 35% and 42% during the corticomedullary and nephrographic phases, respectively. These enhancement characteristics would not be typical of clear cell RCC, and more suggestive of papillary histology. Based on MRI findings, a repeated biopsy was performed (D) demonstrating prominent papillary architecture (top) with microcalcifications, negative CAIX stain (bottom) and strong CK7 and racemase (not shown). Final diagnosis was high grade papillary RCC and treatment recommendation was changed to temsirolimus (Panel in C from Sun MR, Ngo L, Genega EM, et al. Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes--correlation with pathologic findings. Radiology. 2009 Mar;250(3):793–802, with permission).

Figure 4.. Aggressive behavior detected by change in imaging phenotype in small renal mass.

48-yearold female with an incidentally detected small renal mass (SRM). Baseline MRI examination (top row) shows a well encapsulated round 1.8 cm renal mass in the upper pole of the left kidney (yellow arrow) with homogeneous low signal intensity on coronal T2-weighted single shot fast spin echo image (Cor T2), high signal intensity on coronal pre-contrast T1 weighted fat saturated spoiled gradient echo images (Pre T1) and low level progressive enhancement on same images acquired during the corticomedulary (CM), early nephrographic (NG), and sagittal images during excretory phase after administration of 0.1 mmol/kg body weight of gadobutrol. MR imaging findings are consistent with papillary RCC. Ax T1 post: Axial delayed postcontrast T1-weighted. The patient remained asymptomatic and follow up MRI exam 6 months later (middle row) shows a change in signal intensity on Cor T2 and Pre-T1 images (yellow arrows). Importantly, post-contrast images demonstrate an interval change in tumor shape now infiltrating the perirenal fat (NG, red arrow) and renal parenchyma (Sag T1 post, red arrow) despite minimal change in size (1.9 cm on axial T1-weighted post contrast image). Percutaneous biopsy (bottom row) obtained prior to percutaneous ablation confirmed high grade (ISUP 3 out of 4) papillary RCC, type II. H&E: haematoxylin and eosin, CAIX: Carbonic anhydrase IX protein.

Figure 5.. Extraction of MRI texture features for characterization of clear cell renal cell carcinoma.

Haralick features extracted from T2-weighted single-shot turbo spin echo (A) MRI exhibiting a statistically significant correlation with histopathologic tumor grade. LG= Low grade (ISUP grade 1–2). HG = high grade (ISUP grade 3–4). F6 = sum average. F9 = entropy. F12 = Information measures of correlation. Representative examples of tumors with high and low entropy on T2-weighted images (B) and high and low tumor grade at histopathology. q= false discovery rate.

Figure 6.. Quantitative MRI techniques for evaluation of tumor microenvironment in chromophobe renal cell carcinoma.

Coronal T2-weighted single-shot turbo spin echo (T2), gross specimen sectioned in the same anatomic plane after nephrectomy (gross image), and corresponding coronal ASL perfusion map and ADC map in the same location of the tumor are shown in the top panel. The bottom panel shows low (A,D; 10x) and high (B,E; 200x) magnification hematoxylin and eosin (H&E) stains and CD34 immunohistochemistry (C,F; 200x) slides corresponding to the tumor areas indicated on the MRI by the red square (top row) and green circle (bottom row). Areas with high flow on ASL (red square) also have marked restricted diffusion (i.e. low ADC) and this correlates with increased cellularity (B) and microvascular density (blue arrows, C). In contrast, areas with low flow on ASL (green circle) have increased diffusion (i.e. high ADC) indicating increased motion of water, which is likely the result of ischemia induced damage leading to the presence of cell membrane defects (E, yellow arrows). Decreased vascularity is also noted in the same area of the tumor (F).

Figure 7.. Multiparametric MRI as a platform to detect intra-tumor histologic heterogeneity in vivo.

Coronal T2-weighted single shot fast spin echo (A), arterial spin labeled (ASL) difference image (B), and T1-weighted gradient echo images acquired during the corticomedullary (C) and delayed (D) phases of a dynamic contrast enhanced (DCE) acquisition. After nephrectomy, tumor specimen (center panel) was sectioned with the help of fiducial markers placed during surgery in a coronal plane matching the anatomic location of the MRI images. Tumor samples were obtained in areas co-localized to regions of high flow (HF), low flow (LF), and invasive component on MRI. Histopathologic analysis of these samples revealed clear cell renal cell carcinoma (ISUP grade 3). Note differences in tumor architecture; small acinar pattern with more hyalinized stroma in the LF region (E), prototypical (“classic”) ccRCC with a small acinar pattern and thin arborizing vasculature in the high flow region (F), and a different trabecular pattern in the invasive area (G).

Figure 8.. Registration of imaging and pathology specimens for radiogenomic analysis.

(A) Coronal contrast-enhanced three-dimensional (3D) gradient echo image of a renal mass in the lower pole of the right kidney. (B) After segmentation of the tumor, a virtual 3D mold is created. Note an indentation in the 3D mold (arrow), corresponding to the anatomic location of the coronal MRI image displayed in A. (C) Creation of the physical mold with 3D printing technology. (D) After partial nephrectomy, the specimen is oriented and placed within the 3D mold. (E) The surgical specimen is sectioned using the indentation in the 3D mold (arrow). (F) A near perfect co-localization of the surgical specimen and MRI imaging is achieved allowing the sampling of specific areas in the tumor and subsequent correlation of tumor features on MRI with histopathology and other tissue based analysis (e.g. radiogenomics, radiometabolomics, etc).

Figure 9.. MR elastography (MRE) for the characterization of tissue properties in renal tumors.

Coronal T2-weighted single-shot fast spin echo image (T2) and contrast-enhanced T1-weighted gradient echo image (T1-Gad) acquired during the corticomedulary phase of a dynamic contrast-enhanced acquisition and corresponding magnitude and stiffness map from an MRE acquisition performed at the same anatomic level. Note an area of increased stiffness in the lower medial aspect of the mass (red arrow) compared with a relatively softer area in the upper medial aspect of the mass (light blue arrow). After nephrectomy, tumor specimen (right panel) was sectioned with the help of fiducial markers placed during surgery in a coronal plane matching the anatomic location of the MR images. Histopathologic assessment of both areas indicated by the red and light blue regions of interest (ROIs), which correspond with the red and light blue arrows on MRE, demonstrated no obvious differences in the International Society of Urological Pathology grade (ISUP grade 3 out of 4) of clear cell carcinoma (A, B; original magnification 200). Histopathologic images at lower magnification; however, show obvious morphologic/ architectural differences between both tumor areas (C, D; original magnification 10). Detailed analysis of the tumor region within red ROI (ie, area of increased stiffness) confirms the presence of nodular fibrosis (black arrows, E; original magnification 100) and smooth muscle in the stroma (yellow arrows, F; original magnification 100). The presence of fibromuscular stroma explains the increase stiffness detected by MRE.