ASCO GU 2020: Renal Cell Carcinoma: The Virtual Biopsy

San Francisco, California (UroToday.com) The treatment selection for localized renal tumors at the 2020 American Society of Clinical Oncology Genitourinary Cancers Symposium (ASCO GU) included a presentation by Dr. Ivan Pedrosa discussing the virtual renal biopsy. Dr. Pedrosa notes that kidney cancer is a radiological diagnosis in that 70% of “incidental” masses are found on imaging leading to earlier stages at diagnosis. However, our diagnostic algorithm for reporting on renal masses has not changed in many years: if fat is seen on a CT scan, then the diagnosis of angiomyolipoma is made, whereas if there is no fat and the mass enhances, the diagnosis is suggestive of renal cell carcinoma (RCC).


A SEER analysis suggests that only 3% of ~60,000 patients are offered active surveillance for small renal masses. Among T1a tumors, 20% of those surgical removed are benign, and there has been an 82% increase in surgery for benign disease between 2000 and 2009. The morbidity for kidney cancer surgery is not benign, estimated to be 13% for grade 2-3 complications and a mortality rate of 0.1% for partial nephrectomy. Nephron loss is associated with increased cardiovascular events and decreased survival. Furthermore, the cost of benign nephrectomies in the US in 2014 was $153 million, correlating to $55,573 at the individual level.

Why not biopsy every mass? The pros are that it gives a definitive diagnosis, with a sensitivity of 97.5%, a specificity of 97.26% and PPV of 99.8%. It also decreases the number of benign nephrectomies. The cons of a biopsy according to Dr. Pedrosa is that the patients don’t like having a biopsy, complications include hemorrhage (1%), pain, and hematuria, and there may be a 1% upstaging from cT1a to pT3a (peri-renal fat). Furthermore, it may not be feasible in some cases secondary to anatomical constraints and it is non-diagnostic in 14% with an NPV of 63%. As such, 37% of benign biopsies represent malignant disease.

Non-invasive assessment of small renal masses includes patient demographics (gender, age) and tumor size and growth kinetics. Options for a virtual biopsy include various imaging modalities including CT, US/CEUS, MRI, and 99Tc sestamibi SPECT/CT. A virtual biopsy with an MRI follows this algorithm:

algorithm for virtual biopsy with an MRI

Across all histologies, the histologic prediction with mpMRI for small renal masses has accuracies ranging from 81%-98%, sensitivities ranging from 14%-85%, and specificities ranging from 76%-98%. 99Tc Sestamibi SPECT/CT scans have recently garnered attention in the imaging of renal masses. Hot tumors are oncocytoma histology + hybrid oncocytic/chromophobe tumors. Cold tumors are ccRCC, papillary RCC and AML. Sestamibi has a sensitivity of 87.5% and specificity of 95.2%.

Dr. Pedrosa then discussed the clear cell likelihood score, based off of parameters from an mpMRI and scored as: 1-very unlikely, 2-unlikely, 3-equivocal, 4-likely, and 5-highly likely to be clear cell RCC (ccRCC). In their 2017 paper in the Journal of Urology, Dr. Pedrosa’s group retrospectively reviewed the records of patients with cT1a masses who underwent MRI and partial or radical nephrectomy from December 2011 to July 2015.1 Seven radiologists with different levels of experience who were blinded to final pathology findings independently reviewed studies based on a predefined algorithm. A total of 110 patients with 121 masses were identified, with a mean tumor size of 2.4 cm and 50% of the lesions were clear cell. Defining clear cell as scores of 4 or greater demonstrated 78% sensitivity and 80% specificity while scores of 3 or greater showed 95% sensitivity and 58% specificity. Interobserver agreement was moderate to good with a mean κ of 0.53 (range 0.38-0.64). In a subsequent validation study among patients receiving an mpMRI from 2016-2018,2 there were 57 patients (mean age 61.7 ± 14.9 years) with 63 cT1a renal masses. Defining clear cell likelihood score 4-5 lesions as positive demonstrated an overall accuracy of 84%, sensitivity of 89%, specificity of 79%, positive predictive value of 84%, and negative predictive value of 86%. A clear cell likelihood score of 1-2 demonstrates an 86% accuracy and 100% sensitivity/positive predictive value of identifying non-ccRCC histology.

A clear cell likelihood score of 1-2 makes up 30% of all T1a masses, of which in Dr. Pedrosa’s experience 84% were malignant, but none of these tumors were ccRCC. Thus, the implications are that active surveillance is likely safe in these individuals. The risk of placing a high-grade tumor on active surveillance is 12% for all T1a and only 4% for patients with clear cell likelihood score of 1-2. A clear cell likelihood score of 3 comprises 11% of all T1a masses, of which 43% are benign and 57% are ccRCC. In Dr. Pedrosa’s opinion, this is the time to biopsy the patient, as this has the highest diagnostic yield. However, 43% of these are oncocytic neoplasms, which highlights the role of Sestamibi scans in the clear cell likelihood score 3 patients.

Dr. Pedrosa concluded with several take-home messages from his virtual biopsy presentation:

  • Clear cell likelihood score and 99Tc-Sestamibi can assist in the management of small renal masses, which decreases the need for biopsy and decreases the nephrectomy rate for benign and low-grade tumors
  • This does require multicenter validation of the presented results
Presented by: Ivan Pedrosa, Md, PhD, Professor of Radiology, Chief of Magnetic Resonance Imaging (MRI), Jack Reynolds, M.D., Chair in Radiology, Co-Leader, Kidney Cancer Program, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas

Written by: Zachary Klaassen, MD, MSc, Assistant Professor of Urology, Georgia Cancer Center, Augusta University/Medical College of Georgia, Twitter: @zklaassen_md at the 2020 Genitourinary Cancers Symposium, ASCO GU #GU20, February 13-15, 2020, San Francisco, California

References:

1. Canvasser, Noah E., Fernando U. Kay, Yin Xi, Daniella F. Pinho, Daniel Costa, Alberto Diaz de Leon, Gaurav Khatri et al. "Diagnostic accuracy of multiparametric magnetic resonance imaging to identify clear cell renal cell carcinoma in cT1a renal masses." The Journal of urology 198, no. 4 (2017): 780-786.

2. Johnson, Brett A., Sandy Kim, Ryan L. Steinberg, Alberto Diaz de Leon, Ivan Pedrosa, and Jeffrey A. Cadeddu. "Diagnostic performance of prospectively assigned clear cell Likelihood scores (ccLS) in small renal masses at multiparametric magnetic resonance imaging." In Urologic Oncology: Seminars and Original Investigations, vol. 37, no. 12, pp. 941-946. Elsevier, 2019.