Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation

Gregory, Adriana; Chebib, Fouad T.; Poudyal, Bhavya; Holmes, Heather L.; Yu, Alan; Landsittel, Douglas; Bae, Kyongtae T.; Chapman, Arlene B.; Frederic, Rahbari-Oskoui; Mrug, Michal; Bennett, William M.; Harris, Peter C.; Erickson, Bradley J.; Torres, Vicente E.; Kline, Timothy L.

doi:10.1016/j.kint.2023.01.010

Cited by 14 publications

(12 citation statements)

References 28 publications

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“…On the other hand, TKV may not be the only parameter related to the deterioration in renal function. As a recent study showed, other imaging factors, such as the total number of cysts or the surface of the renal parenchyma that encountered renal cysts, may be more tightly associated with the e-GFR decline [9].…”

Section: Discussionmentioning

confidence: 97%

The Efficacy, the Treatment Response and the Aquaretic Effects of a Three-Year Tolvaptan Regimen in Polycystic Kidney Disease Patients

Gkika,

Louka,

Tsagkatakis

et al. 2023

Clinics and Practice

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Tolvaptan, a selective vasopressin V2 receptor antagonist, is the first and only approved specific treatment for Autosomal-Dominant Polycystic Kidney Disease (ADPKD), and is used in current clinical practice. Real clinical data are missing. In this retrospective study, 41 ADPKD patients received tolvaptan for 3 years, from 2018 to 2021. Total kidney volume (TKV) was measured using Magnetic Resonance Imaging, at initiation and at the end of the treatment period. A complete biochemistry/hematology profile and a 24 h urine volume collection were performed monthly for the first 18 months and every 3 months thereafter. At the end of the treatment period, the median (IQR) estimated Glomerular Filtration Rate (e-GFR) was 5.3 (−1.3, 8.7) mL/min higher than the expected e-GFR decline without treatment, while the prediction for End Stage Chronic Kidney Disease (ESKD) had been prolonged by 1 (0, 2) year. Total Kidney Volume did not change significantly (2250 (1357) mL at 3 years of treatment vs. 2180 (1091) mL expected without treatment, p = 0.48). Younger patients with a relatively preserved e-GFR, lower hypertension burden, better familiar renal prognosis and more severe imaging data showed better outcomes. The aquaretic adverse effects of tolvaptan did not affect renal function and electrolyte balance in 51 patients, in a follow-up period of 18 months. Consequently, tolvaptan seems to be effective in preventing progression of ADPKD when administered in a timely manner in patients with better familiar renal history, shorter hypertension duration and worse imaging profile. Increased diuresis does not affect treatment efficacy.

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Section: Discussionmentioning

confidence: 97%

The Efficacy, the Treatment Response and the Aquaretic Effects of a Three-Year Tolvaptan Regimen in Polycystic Kidney Disease Patients

Gkika,

Louka,

Tsagkatakis

et al. 2023

Clinics and Practice

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“…Interestingly, in early PKD, the correlation between TCN (R = 0.8), cyst index (R = 0.88) and parenchymal index (R = –0.88) was much higher as compared with at the time of kidney failure (R = 0.39, R = 0.53 and R = –0.53, respectively). In a recent study, we explored the utility of TCN among others using data from the CRISP study [ 49 ]. Similarly, TCN showed a low correlation with HtTKV and superior prediction of the change in future GFR compared with TKV [ 49 ].…”

Section: Discussionmentioning

confidence: 99%

“…In a recent study, we explored the utility of TCN among others using data from the CRISP study [ 49 ]. Similarly, TCN showed a low correlation with HtTKV and superior prediction of the change in future GFR compared with TKV [ 49 ]. Higher cyst number at young age predisposes to rapidly progressive ADPKD [ 48 , 50 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of advanced imaging biomarkers at kidney failure in patients with ADPKD: a pilot study

Wigerinck

Gregory

Smith

et al. 2023

Clinical Kidney Journal

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Background and objectives Autosomal Dominant Polycystic Kidney Disease (ADPKD) presents with variable disease severity and progression. Advanced imaging biomarkers may provide insights into cystic and non-cystic processes leading to kidney failure in different age groups. Methods This pilot study included 39 ADPKD patients with kidney failure, stratified into three age groups (<46, 46–56, >56 years old). Advanced imaging biomarkers were assessed using an automated instance cyst segmentation tool. The biomarkers were compared with an age- and sex-matched ADPKD cohort in early chronic kidney disease (CKD). Results Ht-total parenchymal volume correlated negatively with age at kidney failure. The median Ht-total parenchymal volume was significantly lower in patients older than 56 years. Cystic burden was significantly higher at time of kidney failure and especially in patients who reached it before age 46. The cyst index at kidney failure was comparable across age groups and Mayo Imaging Classes. Advanced imaging biomarkers showed higher correlation with Ht-total kidney volume in early CKD than at kidney failure. Cyst index and parenchymal index were relatively stable over five years prior to kidney failure, whereas Ht-total cyst volume and cyst parenchymal surface area increased significantly. Conclusion Age-related differences in advanced imaging biomarkers suggest variable pathophysiological mechanisms in ADPKD patients with kidney failure. Further studies are needed to validate the utility of these biomarkers in predicting disease progression and guiding treatment strategies.

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“…Precisely identifying the components of CRLs is crucial for deciding on suitable treatment approaches. Contrast-enhanced computed tomography (CECT) imaging is frequently utilized to distinguish among the different types of CRLs [ 5 ]. However, the complex pattern of malignant CRLs on CECT images, including septal thickness, mural nodule enhancement, and calcifications presence, pose significant challenges for both diagnosis and management, particularly when dealing with early-stage cases [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Deep learning system for malignancy risk prediction in cystic renal lesions: a multicenter study

He,

Feng,

et al. 2024

Insights Imaging

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Objectives To develop an interactive, non-invasive artificial intelligence (AI) system for malignancy risk prediction in cystic renal lesions (CRLs). Methods In this retrospective, multicenter diagnostic study, we evaluated 715 patients. An interactive geodesic-based 3D segmentation model was created for CRLs segmentation. A CRLs classification model was developed using spatial encoder temporal decoder (SETD) architecture. The classification model combines a 3D-ResNet50 network for extracting spatial features and a gated recurrent unit (GRU) network for decoding temporal features from multi-phase CT images. We assessed the segmentation model using sensitivity (SEN), specificity (SPE), intersection over union (IOU), and dice similarity (Dice) metrics. The classification model’s performance was evaluated using the area under the receiver operator characteristic curve (AUC), accuracy score (ACC), and decision curve analysis (DCA). Results From 2012 to 2023, we included 477 CRLs (median age, 57 [IQR: 48–65]; 173 men) in the training cohort, 226 CRLs (median age, 60 [IQR: 52–69]; 77 men) in the validation cohort, and 239 CRLs (median age, 59 [IQR: 53–69]; 95 men) in the testing cohort (external validation cohort 1, cohort 2, and cohort 3). The segmentation model and SETD classifier exhibited excellent performance in both validation (AUC = 0.973, ACC = 0.916, Dice = 0.847, IOU = 0.743, SEN = 0.840, SPE = 1.000) and testing datasets (AUC = 0.998, ACC = 0.988, Dice = 0.861, IOU = 0.762, SEN = 0.876, SPE = 1.000). Conclusion The AI system demonstrated excellent benign-malignant discriminatory ability across both validation and testing datasets and illustrated improved clinical decision-making utility. Critical relevance statement In this era when incidental CRLs are prevalent, this interactive, non-invasive AI system will facilitate accurate diagnosis of CRLs, reducing excessive follow-up and overtreatment. Key Points The rising prevalence of CRLs necessitates better malignancy prediction strategies. The AI system demonstrated excellent diagnostic performance in identifying malignant CRL. The AI system illustrated improved clinical decision-making utility. Graphical Abstract

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Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation

Cited by 14 publications

References 28 publications

The Efficacy, the Treatment Response and the Aquaretic Effects of a Three-Year Tolvaptan Regimen in Polycystic Kidney Disease Patients

The Efficacy, the Treatment Response and the Aquaretic Effects of a Three-Year Tolvaptan Regimen in Polycystic Kidney Disease Patients

Evaluation of advanced imaging biomarkers at kidney failure in patients with ADPKD: a pilot study

Deep learning system for malignancy risk prediction in cystic renal lesions: a multicenter study

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