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Ilki Y, Bulbul E, Gultekin MH, Erozenci A, Tutar O, Citgez S, Onal B. In-vivo or in-vitro stone attenuation: what is more valuable for the prediction of renal stone composition in non-contrast-enhanced abdominal computed tomography? Aktuelle Urol 2023; 54:30-36. [PMID: 36702134 DOI: 10.1055/a-1971-6759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES To compare the efficacy of in-vivo and in-vitro stone attenuation in the prediction of stone composition using non-contrast-enhanced abdominal computed tomography (NCCT). METHODS This study included a total of 104 patients with renal stones who received percutaneous nephrolithotomy treatment for renal stones between December 2016 and December 2019 and underwent NCCT before the procedure. Preoperative (in-vivo) and postoperative (in-vitro) kidney stone attenuations were compared using the NCCT images of the patients. Renal stone fragments were analysed with the infrared spectrophotometer method. RESULTS The mean age of the 104 patients was 49.5 (interquartile range: 37-61) years. According to the receiver operating characteristics analysis, the cut-off values for the prediction of uric acid stones were determined to be 556 HU for the in-vivo and 774 HU for the in-vitro attenuation measurement. Sensitivity and specificity were 100% and 96.6%, respectively, for the in-vivo and 90.9 and 91%, respectively, for the in-vitro images. The cut-off values for the prediction of calcium stones were determined to be 824 HU and 1065 HU for the in-vivo and in-vitro attenuation measurements, respectively. Sensitivity and specificity were 97.3 and 96% for the in-vivo and 96 and 96% for the in-vitro images. CONCLUSIONS In-vivo stone attenuation measurement in NCCT was slightly superior to in-vitro measurement due to the reduction in the composition and size of the stone. Our findings show that NCCT in-vivo stone attenuation might differentiate uric acid and calcium stones from the other stone types.
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Affiliation(s)
- Yavuz Ilki
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Emre Bulbul
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Mehmet Hamza Gultekin
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Ahmet Erozenci
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Onur Tutar
- Cerrahpasa Faculty of Medicine, Department of Radiology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Sinharib Citgez
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Bulent Onal
- Cerrahpasa Faculty of Medicine, Department of Urology, Istanbul University-Cerrahpasa, Istanbul, Turkey
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Kaviani P, Primak A, Bizzo B, Ebrahimian S, Saini S, Dreyer KJ, Kalra MK. Performance of threshold-based stone segmentation and radiomics for determining the composition of kidney stones from single-energy CT. Jpn J Radiol 2023; 41:194-200. [PMID: 36331701 DOI: 10.1007/s11604-022-01349-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/30/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE Knowledge of kidney stone composition can help in patient management; urine composition analysis and dual-energy CT are frequently used to assess stone type. We assessed if threshold-based stone segmentation and radiomics can determine the composition of kidney stones from single-energy, non-contrast abdomen-pelvis CT. METHODS With IRB approval, we identified 218 consecutive patients (mean age 64 ± 13 years; male:female 138:80) with the presence of kidney stones on non-contrast, abdomen-pelvis CT and surgical or biochemical proof of their stone composition. CT examinations were performed on one of the seven multidetector-row scanners from four vendors (GE, Philips, Siemens, Toshiba). Deidentified CT images were processed with a radiomics prototype (Frontier, Siemens Healthineers) to segment the entire kidney volumes with an AI-based organ segmentation tool. We applied a threshold of 130 HU to isolate stones in the segmented kidneys and to estimate radiomics over the segmented stone volume. A coinvestigator verified kidney stone segmentation and adjusted the volume of interest to include the entire stone volume when necessary. We applied multiple logistic regression tests with precision recall plots to obtain area under the curve (AUC) using a built-in R statistical program. RESULTS The threshold-based stone segmentation successfully isolated kidney stones (uric acid: n = 102 patients, calcium oxalate/phosphate: n = 116 patients) in all patients. Radiomics differentiated between calcium and uric acid stones with an AUC of 0.78 (p < 0.01, 95% CI 0.73-0.83), 0.79 sensitivity, and 0.90 specificity regardless of CT vendors (GE CT: AUC = 0.82, p < 0.01, 95% CI 0.740-0896; Siemens CT: AUC = 0.77, 95% CI 0.700-0.846, p < 0.01). CONCLUSION Automated threshold-based stone segmentation and radiomics can differentiate between calcium oxalate/phosphate and urate stones from non-contrast, single-energy abdomen CT.
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Affiliation(s)
- Parisa Kaviani
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA, 02114, USA
| | - Andrew Primak
- Siemens Medical Solutions USA Inc, Malvern, PA, 19355, USA
| | - Bernardo Bizzo
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA, 02114, USA.,MGH and BWH Center for Clinical Data Science, Boston, USA
| | - Shadi Ebrahimian
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA, 02114, USA
| | - Sanjay Saini
- Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA, 02114, USA
| | - Keith J Dreyer
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA, 02114, USA.,MGH and BWH Center for Clinical Data Science, Boston, USA.,Department of Radiology, Massachusetts General Hospital, 25 New Chardon Street, Boston, MA, 02114, USA
| | - Mannudeep K Kalra
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA, 02114, USA.
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Single-energy CT predicts uric acid stones with accuracy comparable to dual-energy CT-prospective validation of a quantitative method. Eur Radiol 2021; 31:5980-5989. [PMID: 33635394 PMCID: PMC8270827 DOI: 10.1007/s00330-021-07713-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 12/10/2020] [Accepted: 01/21/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVES To prospectively validate three quantitative single-energy CT (SE-CT) methods for classifying uric acid (UA) and non-uric acid (non-UA) stones. METHODS Between September 2018 and September 2019, 116 study participants were prospectively included in the study if they had at least one 3-20-mm urinary stone on an initial urinary tract SE-CT scan. An additional dual-energy CT (DE-CT) scan was performed, limited to the stone of interest. Additionally, to include a sufficient number of UA stones, eight participants with confirmed UA stone on DE-CT were retrospectively included. The SE-CT stone features used in the prediction models were (1) maximum attenuation (maxHU) and (2) the peak point Laplacian (ppLapl) calculated at the position in the stone with maxHU. Two prediction models were previously published methods (ppLapl-maxHU and maxHU) and the third was derived from the previous results based on the k-nearest neighbors (kNN) algorithm (kNN-ppLapl-maxHU). The three methods were evaluated on this new independent stone dataset. The reference standard was the CT vendor's DE-CT application for kidney stones. RESULTS Altogether 124 participants (59 ± 14 years, 91 men) with 106 non-UA and 37 UA stones were evaluated. For classification of UA and non-UA stones, the sensitivity, specificity, and accuracy were 100% (37/37), 97% (103/106), and 98% (140/143), respectively, for kNN-ppLapl-maxHU; 95% (35/37), 98% (104/106), and 97% (139/143) for ppLapl-maxHU; and 92% (34/37), 94% (100/106), and 94% (134/143) for maxHU. CONCLUSION A quantitative SE-CT method (kNN-ppLapl-maxHU) can classify UA stones with accuracy comparable to DE-CT. KEY POINTS • Single-energy CT is the first-line diagnostic tool for suspected renal colic. • A single-energy CT method based on the internal urinary stone attenuation distribution can classify urinary stones into uric acid and non-uric acid stones with high accuracy. • This immensely increases the availability of in vivo stone analysis.
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Fitri LA, Haryanto F, Arimura H, YunHao C, Ninomiya K, Nakano R, Haekal M, Warty Y, Fauzi U. Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network. Phys Med 2020; 78:201-208. [DOI: 10.1016/j.ejmp.2020.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 08/02/2020] [Accepted: 09/03/2020] [Indexed: 10/23/2022] Open
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Abstract
PURPOSE OF REVIEW Radiological imaging techniques are a fast developing field in medicine. Therefore, the purpose of this review was to identify and discuss the latest changes of modern imaging techniques in the management of urinary stone disease. RECENT FINDINGS The introduction of iterative image reconstruction enables low-dose and ultra-low-dose (ULD) protocols. Although current guidelines recommend their utilization in nonobese patients recent studies indicate that low-dose imaging may be feasible in obese (<30 kg/m) but not in bariatric patients. Use of dual energy computed tomography (CT) technologies should balance between additional information and radiation dose aspects. If available on a dose neutral basis, dual energy imaging and analysis should be performed. Current guidelines recommend measuring the largest diameter for clinical decision making; however, recent studies suggest a benefit from measuring the volume based on multiplanar reformation. Quantitative imaging is still an experimental approach. SUMMARY The use of low-dose and even ULD CT protocols should be diagnostic standard, even in obese patients. If dual energy imaging is available, it should be limited to specific clinical questions. The stone volume should be reported in addition to the largest diameter for treatment decision and a more valid comparability of upcoming studies.
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