Long-term oncological outcomes of cystic renal cell carcinoma according to the Bosniak classification

Pseudoenhancement in Cystic Renal Lesions - Impact of Virtual Monoenergetic Images of Photon-Counting Detector CT on Lesion Classification

RATIONALE AND OBJECTIVES

To investigate the impact of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) on the enhancement and classification of renal cysts.

MATERIALS AND METHODS

Adults with renal cysts (≥7 mm) who received a triphasic examination on a clinical PCD-CT (120 kVp; IQ level 68) between July 2021 and March 2022 were retrospectively identified. Only non-enhancing cysts (enhancement<10 HU between unenhanced and venous phase at 70 keV) were included. VMI from 40 to 190 keV with increments of 10 keV were reconstructed from the venous phase. Enhancement was measured to classify each lesion as non-enhancing (<10 HU), equivocally enhancing (10-19 HU), and definitely enhancing (≥20 HU). Classification changes as a function of VMI were assessed. Pearson correlation coefficient, the Kruskal-Wallis and the Chi-square test were used.

RESULTS

A total of 86 patients (mean age, 74 ± 9 years; 74 male) with 160 non-enhancing renal cysts (17.6 ± 10 mm) were included. CT attenuation of the cysts increased from higher to lower VMI levels with a mean attenuation of 4 ± 11 HU at 190 keV to 36 ± 17 HU at 40 keV. Mean attenuation of the renal parenchyma was 43 ± 4 HU at 190 keV and 414 ± 71 HU at 40 keV. No cyst exhibited enhancement from 70 keV to 190 keV. At 40, 50, and 60 keV, 35% (56/160), 29% (47/160) and 9% (15/160) of cysts showed equivocal and 46% (74/160), 10% (16/160), and 0% (0/160) definite enhancement, respectively. There was no significant influence of size (P=.13), cyst location (P=.9) and BMI (P=.19) on enhancement classification.

CONCLUSION

VMI has a relevant impact on enhancement and classification of renal cysts with misclassification in a large number of cases at energy levels below 70 keV.

Comparison of partial nephrectomy and radical nephrectomy for cystic renal cell carcinoma: a SEER-based and retrospective study

Cystic renal cell carcinoma (cRCC) is uncommon and surgical indication remains controversial. We compared radical nephrectomy (RN) with partial nephrectomy (PN) in patients with cRCC using data from the Surveillance, Epidemiology and End Results (SEER) database and a retrospective cohort including 106 cRCC patients hospitalized in Ruijin and Renji Hospitals from 2013 to 2022. The baseline characteristics between RN and PN groups in both cohorts were adjusted by propensity score-matching (PSM). A total of 640 patients were included in the SEER cohort. Before PSM, PN group in the SEER cohort had a lower level of T stage (p < 0.001) and comprised more Caucasians (p < 0.001). After PSM, RN was associated with worse overall survival (p < 0.001) and cancer-specific survival (p = 0.006) in contrast to PN. In the Chinese cohort, 86 patients who underwent PN and 20 patients who underwent RN were finally included. The mean proportions of estimated glomerular filtration rate preserved after RN were worse than PN. Therefore, PN should be preferred in cRCC patients.

Cystic Renal Masses: Old and New Paradigms

Cystic renal masses describe a spectrum of lesions with benign and/or malignant features. Cystic renal masses are most often identified incidentally with the Bosniak classification system stratifying their malignant potential. Solid enhancing components most often represent clear cell renal cell carcinoma yet display an indolent natural history relative to pure solid renal masses. This has led to an increased adoption of active surveillance as a management strategy in those who are poor surgical candidates. This article provides a contemporary overview of historical and emerging clinical paradigms in the diagnosis and management of this distinct clinical entity.

Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions

BACKGROUND

The rising prevalence of cystic renal lesions (CRLs) detected by computed tomography necessitates better identification of the malignant cystic renal neoplasms since a significant majority of CRLs are benign renal cysts. Using arterial phase CT scans combined with pathology diagnosis results, a fusion feature-based blending ensemble machine learning model was created to identify malignant renal neoplasms from cystic renal lesions (CRLs). Histopathology results were adopted as diagnosis standard. Pretrained 3D-ResNet50 network was selected for non-handcrafted features extraction and pyradiomics toolbox was selected for handcrafted features extraction. Tenfold cross validated least absolute shrinkage and selection operator regression methods were selected to identify the most discriminative candidate features in the development cohort. Feature's reproducibility was evaluated by intra-class correlation coefficients and inter-class correlation coefficients. Pearson correlation coefficients for normal distribution and Spearman's rank correlation coefficients for non-normal distribution were utilized to remove redundant features. After that, a blending ensemble machine learning model were developed in training cohort. Area under the receiver operator characteristic curve (AUC), accuracy score (ACC), and decision curve analysis (DCA) were employed to evaluate the performance of the final model in testing cohort.

RESULTS

The fusion feature-based machine learning algorithm demonstrated excellent diagnostic performance in external validation dataset (AUC = 0.934, ACC = 0.905). Net benefits presented by DCA are higher than Bosniak-2019 version classification for stratifying patients with CRL to the appropriate surgery procedure.

CONCLUSIONS

Fusion feature-based classifier accurately distinguished malignant and benign CRLs which outperformed the Bosniak-2019 version classification and illustrated improved clinical decision-making utility.

Stratification of malignant renal neoplasms from cystic renal lesions using deep learning and radiomics features based on a stacking ensemble CT machine learning algorithm

Using nephrographic phase CT images combined with pathology diagnosis, we aim to develop and validate a fusion feature-based stacking ensemble machine learning model to distinguish malignant renal neoplasms from cystic renal lesions (CRLs). This retrospective research includes 166 individuals with CRLs for model training and 47 individuals with CRLs in another institution for model testing. Histopathology results are adopted as diagnosis criterion. Nephrographic phase CT scans are selected to build the fusion feature-based machine learning algorithms. The pretrained 3D-ResNet50 CNN model and radiomics methods are selected to extract deep features and radiomics features, respectively. Fivefold cross-validated least absolute shrinkage and selection operator (LASSO) regression methods are adopted to identify the most discriminative candidate features in the development cohort. Intraclass correlation coefficients and interclass correlation coefficients are employed to evaluate feature’s reproducibility. Pearson correlation coefficients for normal distribution features and Spearman’s rank correlation coefficients for non-normal distribution features are used to eliminate redundant features. After that, stacking ensemble machine learning models are developed in the training cohort. The area under the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) are adopted in the testing cohort to evaluate the performance of each model. The stacking ensemble machine learning algorithm reached excellent diagnostic performance in the testing dataset. The calibration plot shows good stability when using the stacking ensemble model. Net benefits presented by DCA are higher than the Bosniak 2019 version classification when employing any machine learning algorithm. The fusion feature-based machine learning algorithm accurately distinguishes malignant renal neoplasms from CRLs, which outperformed the Bosniak 2019 version classification, and proves to be more applicable for clinical decision-making.

Surgical outcomes of robot-assisted laparoscopic partial nephrectomy for cystic renal cell carcinoma

To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with cystic renal cell carcinoma (cRCC) and those with solid RCC (sRCC). We retrospectively analyzed 1065 patients who underwent RAPN between 2013 and 2020 for a pathological diagnosis of RCC. Patients were divided into two groups: cRCC and sRCC. cRCC was diagnosed according to the Bosniak classification system. To minimize selection bias between the two groups, patient variables (patient characteristics) and tumor factors (such as size and complexity) were adjusted using 1:1 propensity score matching. Of the 1065 patients, 94 (9%) were diagnosed with cRCC. Bosniak categories of IIF, III, and IV were noted in 4 (4.2%), 31 (33%), and 59 (63%) patients, respectively. After matching, 83 patients each were assigned to the cRCC and sRCC groups. The operation time in cRCC tended to be longer than in sRCC but not significantly different (164 vs. 150 min, P = 0.0767). Other surgical outcomes, such as change in estimated glomerular filtration rate ( - 5.2 vs.  - 7.2%, P = 0.1577), perioperative complications (14.5 vs. 15.7%, P = 0.9225), estimated blood loss (62 vs. 58 mL, P = 0.5613), or negative surgical margin status (100 vs 99%, P = 0.236), were not significantly different between the two groups. During the follow-up period of about 2 years, one and two patients showed recurrence in the cRCC and sRCC groups, respectively. The surgical outcomes of RAPN were similar between cRCC and sRCC, demonstrating the feasibility of RAPN for cRCC.

Malignant ascites following radical nephrectomy for cystic renal cell carcinoma

A 69-year-old man with a history of laparoscopic radical nephrectomy for papillary renal cell carcinoma presented with a 1-week history of generalised abdominal pain, distension and loss of appetite. Clinical examination and CT imaging demonstrated ascites associated with peritoneal nodules, raising the possibility of metastatic disease. Immunochemistry staining from ascites fluid cytology confirmed renal cell carcinoma. Following multidisciplinary discussions, the patient was commenced on a small-molecule tyrosine kinase inhibitor.

Imaging Characterization of Renal Masses

The detection of a renal mass is a relatively frequent occurrence in the daily practice of any Radiology Department. The diagnostic approaches depend on whether the lesion is cystic or solid. Cystic lesions can be managed using the Bosniak classification, while management of solid lesions depends on whether the lesion is well-defined or infiltrative. The approach to well-defined lesions focuses mainly on the differentiation between renal cancer and benign tumors such as angiomyolipoma (AML) and oncocytoma. Differential diagnosis of infiltrative lesions is wider, including primary and secondary malignancies and inflammatory disease, and knowledge of the patient history is essential. Radiologists may establish a possible differential diagnosis based on the imaging features of the renal masses and the clinical history. The aim of this review is to present the contribution of the different imaging techniques and image guided biopsies in the diagnostic management of cystic and solid renal lesions.

Computed tomography features predicting aggressiveness of malignant parenchymal renal tumors suitable for partial nephrectomy

The aim of this study was to identify and standardize computed tomography (CT) features having a potential role in predicting aggressiveness of malignant parenchymal renal tumors suitable for partial nephrectomy (PN). We performed a non-systematic review of the recent literature to evaluate the potential impact of CT variables proposed by the Society of Abdominal Radiology Disease-Focused Panel on Renal Cell Carcinoma in predicting aggressiveness of newly diagnosed malignant parenchymal renal tumors. The analyzed variables were clinical tumor size, tumor growth rate, enhancement characteristics, amount of cystic component, polar and capsular location, tumor margins and distance between tumor and renal sinus. Unfavorable behavior was defined as: 1) renal cell carcinoma (RCC) with stage ≥pT3; 2) nuclear grade 3 or 4; 3) presence of sarcomatoid de-differentiation; or 4) non-clear cell subtypes with unfavorable prognosis (type 2 papillary RCC, collecting duct or renal medullary carcinoma, unclassified RCC). Beyond clinical tumor size, tumor growth rate, enhancement characteristics, amount of cystic component, tumor margins and distance between tumor and renal sinus are highly relevant features predicting an unfavorable behavior. Moreover, several studies supported the role of necrosis as preoperative predictor of tumor aggressiveness. Peritumoral and intratumoral vasculature as well as capsule status are emerging variables that need to be further evaluated. Tumor size, enhancement characteristics, tumor margins and distance to the renal sinus are highly relevant CT features predicting biological aggressiveness of malignant parenchymal renal tumors. Combination of these parameters might be useful to generate tools to predict the unfavorable behavior of renal tumors suitable for PN.

Tubulocystic Renal Cell Carcinoma of the Native Kidney in a Renal Transplant Recipient: A Rare Case Report

Tubulocystic renal cell carcinoma (TCC) is a rare and newly recognized variant of renal cell carcinoma, which may mimic benign cystic disease of the kidney. To our knowledge, we present the first reported case of a patient who, despite standard preoperative workup, developed TCC of his native kidney soon after receiving kidney transplantation. He was appropriately treated with native nephrectomy and has had no signs of reoccurrence 7 years postoperatively. Given the significant risk of malignancy in renal transplant patients, this case emphasizes the need for close monitoring of native cystic disease before and after transplantation, with low threshold to proceed with surgical intervention.

Complex Renal Cysts (Bosniak ≥ IIF): Outcomes in a Population-Based Cohort Study

Simple Summary

Researchers from the University of Dundee have found that not all kidney cancers will need urgent surgery. In a published research in the Cancers, Dr Lucocq et al have carefully established database record of patients with kidney cancer looking like water filled sacs on CT scan and reported that these cancers are low grade and perhaps less harmful on long-term follow-up. In fact, behaviour of these cancer cells is much slower compared to other diseases such as heart failure and high blood pressure. Most people die from chronic disease much before cancer spread or progression. The researchers in this group have shown that surgical removal of these cancers, particularly in elderly people and those with other health conditions such as heart failure may not be necessary. Patients in Tayside Urological Cancers (TUCAN) database were carefully assessed using CT scans and discussed in multidisciplinary meetings and were followed up for more than 6 years. This kind of population-based study adds new knowledge to the understanding behaviour of a subset kidney cancers which otherwise have very poor outcome. The researchers and paper highlight careful documentation of cohort to understand natural history of disease.

Abstract

There is emerging evidence to suggest that con-current medical conditions influence the outcome of cancers, irrespective of therapy offered. The prevalence and impact of co-morbidities on the survival outcome of complex renal cystic masses in not known. The objective was to study complex renal cysts (Bosniak ≥IIF ) and assess the overall and renal cancer-specific survival in a population-based database including impact of con-current morbidities. The Tayside Urological Cancer Network (TUCAN) database covering a stable population of more than 416,090 inhabitants in a defined geographical area identified 452 complex renal cysts in 415 patients between 2009 and 2019. Each patient was tracked and followed up using a unique identifier and deterministic linkage methodology. The last date of follow-up including cause of death was determined. Co-morbidities were recorded from primary care referrals. Renal cancer-specific mortality was 1.7% at a median follow-up of 76.0 months; however, overall survival was poor, particularly in patients ≥ 70 years of age and with ≥ 2 significant co-morbid conditions (p < 0.0001). A total of 38.3% of the cohort showed con-current morbidities. Age and co-morbidities were significant risk factors for overall survival in patients with complex renal cystic disease and a careful assessment should be made to recommend surgical intervention in the elderly population, in particular in those with other health-related conditions.

Complex renal cysts (Bosniak ≥IIF): interobserver agreement, progression and malignancy rates

Objective

The objective was to assess the interobserver agreement rate, progression rates and malignancy rates in the assessment of complex renal cysts (≥ Bosniak IIF) using a population-based database.

Methods

A regional database identified 452 complex renal cysts in 415 patients between 2009 and 2019. Each patient was tracked and followed up using a unique identifier and deterministic linkage methodology. The interobserver agreement rate between radiologists was calculated using a weighted kappa statistic. Progression and malignancy rates of cysts (Bosniak ≥IIF) over the 11-year period were calculated.

Results

The linear-weighted kappa value was 0.69 for all complex cysts. The rate of progression and regression of Bosniak IIF cysts was 4.6% (7/151) and 3.3% (5/151), respectively. All malignant IIF cysts progressed within 16 months of diagnosis. The malignancy rate of surgically resected Bosniak III and IV cysts was 79.3% (23/29) and 84.5% (39/46), respectively. Of all malignant tumours, 73.8% and 93.7% were of low ISUP grade and low stage, respectively.

Conclusions

This study further confirms that there is a good degree of agreement between radiologists in classifying complex renal masses using the Bosniak classification. The progression rate of Bosniak IIF cysts is low, but the malignancy rates of surgically resected Bosniak IIF, III and IV cysts are high. Benign cysts are frequently resected, and a very high proportion of histopathologically confirmed cancers in complex renal cysts are of low grade and stage.

Key Points

•There is a good degree of agreement between radiologists in classifying complex renal masses using the Bosniak classification.

•The rate of progression of Bosniak IIF cysts is low, and malignant cysts progress early during surveillance. Although the malignancy rates of resected Bosniak IIF, III and IV cysts are high, the rate of benign cyst resection is significant.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07186-w) contains supplementary material, which is available to authorized users.