Comparison of 2 Computed Tomography–based Methods to Estimate Preoperative and Postoperative Renal Parenchymal Volume and Correlation With Functional Changes After Partial Nephrectomy

Fully Automated Versions of Clinically Validated Nephrometry Scores Demonstrate Superior Predictive Utility versus Human Scores

OBJECTIVE

To automate the generation of three validated nephrometry scoring systems on preoperative computerised tomography (CT) scans by developing artificial intelligence (AI)-based image processing methods. Subsequently, we aimed to evaluate the ability of these scores to predict meaningful pathological and perioperative outcomes.

PATIENTS AND METHODS

A total of 300 patients with preoperative CT with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumours, and then geometric algorithms were used to measure the components of the concordance index (C-Index), Preoperative Aspects and Dimensions Used for an Anatomical classification of renal tumours (PADUA), and tumour contact surface area (CSA) nephrometry scores. Human scores were independently calculated by medical personnel blinded to the AI scores. AI and human score agreement was assessed using linear regression and predictive abilities for meaningful outcomes were assessed using logistic regression and receiver operating characteristic curve analyses.

RESULTS

The median (interquartile range) age was 60 (51-68) years, and 40% were female. The median tumour size was 4.2 cm and 91.3% had malignant tumours. In all, 27% of the tumours were high stage, 37% high grade, and 63% of the patients underwent partial nephrectomy. There was significant agreement between human and AI scores on linear regression analyses (R ranged from 0.574 to 0.828, all P < 0.001). The AI-generated scores were equivalent or superior to human-generated scores for all examined outcomes including high-grade histology, high-stage tumour, indolent tumour, pathological tumour necrosis, and radical nephrectomy (vs partial nephrectomy) surgical approach.

CONCLUSIONS

Fully automated AI-generated C-Index, PADUA, and tumour CSA nephrometry scores are similar to human-generated scores and predict a wide variety of meaningful outcomes. Once validated, our results suggest that AI-generated nephrometry scores could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making.

AI-generated R.E.N.A.L.+ Score Surpasses Human-generated Score in Predicting Renal Oncologic Outcomes

OBJECTIVE

To determine whether we can surpass the traditional R.E.N.A.L. nephrometry score (H-score) prediction ability of pathologic outcomes by creating artificial intelligence (AI)-generated R.E.N.A.L.+ score (AI+ score) with continuous rather than ordinal components. We also assessed the AI+ score components' relative importance with respect to outcome odds.

METHODS

This is a retrospective study of 300 consecutive patients with preoperative computed tomography scans showing suspected renal cancer at a single institution from 2010 to 2018. H-score was tabulated by three trained medical personnel. Deep neural network approach automatically generated kidney segmentation masks of parenchyma and tumor. Geometric algorithms were used to automatically estimate score components as ordinal and continuous variables. Multivariate logistic regression of continuous R.E.N.A.L. components was used to generate AI+ score. Predictive utility was compared between AI+, AI, and H-scores for variables of interest, and AI+ score components' relative importance was assessed.

RESULTS

Median age was 60years (interquartile range 51-68), and 40% were female. Median tumor size was 4.2 cm (2.6-6.12), and 92% were malignant, including 27%, 37%, and 23% with high-stage, high-grade, and necrosis, respectively. AI+ score demonstrated superior predictive ability over AI and H-scores for predicting malignancy (area under the curve [AUC] 0.69 vs 0.67 vs 0.64, respectively), high stage (AUC 0.82 vs 0.65 vs 0.71, respectively), high grade (AUC 0.78 vs 0.65 vs 0.65, respectively), pathologic tumor necrosis (AUC 0.81 vs 0.72 vs 0.74, respectively), and partial nephrectomy approach (AUC 0.88 vs 0.74 vs 0.79, respectively). Of AI+ score components, the maximal tumor diameter ("R") was the most important outcomes predictor.

CONCLUSION

AI+ score was superior to AI-score and H-score in predicting oncologic outcomes. Time-efficient AI+ score can be used at the point of care, surpassing validated clinical scoring systems.

Does the Renal Parenchyma Adjacent to the Tumor Contribute to Kidney Function? A Critical Analysis of Glomerular Viability in Partial Nephrectomy Specimens

OBJECTIVE

To evaluate the viability of glomeruli in the peritumor parenchyma of partial nephrectomy specimens removed for renal cell carcinoma (RCC) and relate it to kidney function, to better understand the contribution of peritumor parenchyma to renal function.

MATERIALS AND METHODS

A retrospective analysis of 53 partial nephrectomies containing RCC was performed. Glomeruli within 0.25-cm increments from the tumor were quantified and histologically assessed for viability. Tumor size, minimum and maximum margin size, and pre- and postoperative estimated glomerular filtration rate (eGFR) were obtained.

RESULTS

Glomerular viability positively correlated with distance from tumor with mean viable glomeruli in successive 0.25-cm increments of 0-0.25 cm, 58%; 0.25-0.5 cm, 80%; 0.5-0.75 cm, 90%; and 0.75-1.0 cm, 92%. Glomerular viability near the tumor did not correlate with preoperative eGFR, whereas decreased viability further from the tumor did correlate with worse preoperative eGFR. Tumor size showed a nonstatistically significant positive trend with minimum (median 0.15 cm) and maximum margin (median 0.7 cm) sizes. Percent change of glomerular filtration rate did not correlate with margin size (P = .190).

CONCLUSION

Renal parenchyma immediately adjacent to RCC contains fewer viable glomeruli compared with the parenchyma further from the tumor. Based on this information, attempts to preserve all non-neoplastic renal parenchyma via a surgical margin approaching zero may not necessarily result in clinically relevant differences in the amount of viable glomeruli remaining or the renal function preserved.