Abstract
The accuracy of renal mass biopsy to diagnose malignancy can be affected by multiple factors. Here, we investigated the feasibility of Raman spectroscopy to distinguish malignant and benign renal tumors using biopsy specimens. Samples were collected from 63 patients who received radical or partial nephrectomy, mass suspicious of cancer and distal parenchyma were obtained from resected kidney using an 18-gauge biopsy needle. Four Raman spectra were obtained for each sample, and Discriminant Analysis was applied for data analysis. A total of 383 Raman spectra were eventually gathered and each type of tumor had its characteristic spectrum. Raman could separate tumoral and normal tissues with an accuracy of 82.53%, and distinguish malignant and benign tumors with a sensitivity of 91.79% and specificity of 71.15%. It could classify low-grade and high-grade tumors with an accuracy of 86.98%. Besides, clear cell renal carcinoma was differentiated with oncocytoma and angiomyolipoma with accuracy of 100% and 89.25%, respectively. And histological subtypes of cell carcinoma were distinguished with an accuracy of 93.48%. When compared with final pathology and biopsy, Raman spectroscopy was able to correctly identify 7 of 11 “missed” biopsy diagnoses. These results suggested that Raman may serve as a promising non-invasive approach in the future for pre-operative diagnosis.
Highlights
Increased use of imaging technique has led to frequent diagnosis of incidental renal masses, especially small ones
383 spectra were eventually sent to Discriminant analysis (DA) (136 normal tissue, 165 clear cell renal cell carcinomas (RCC), 14 chromophobe RCC, 16 papillary RCC, 28 AML, 24 RO)
We demonstrated the availability of Raman spectroscopy (RS) to distinguish different pathological types of renal tumors using biopsy specimens
Summary
Increased use of imaging technique has led to frequent diagnosis of incidental renal masses, especially small ones. For patients who consider active surveillance or non-surgical treatments, renal mass biopsy (RMB) is often recommended to determine the pathological type of renal mass and guide treatment options. The accuracy of RMB depends on multiple factors, including interpretive skill of pathologists, the amount of specimens acquired, inherent sampling error, etc. The accuracy could fluctuate from 79 to 100% [1,2,3], and non-diagnostic findings such as fibrosis or necrosis were found to be present in 15–22% cases [4,5,6]. A technique that can provide objective evaluation of renal biopsy specimen is urgently needed
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