Min Gwan Kim1, Taek Min Kim1,2, Sang Youn Kim3,4, Jeong Yeon Cho1,2,5. 1. Department of Radiology, Seoul National University Hospital, 101 Daehakro, Jongro-gu, Seoul, 03080, Korea. 2. Department of Radiology, Seoul National University College of Medicine, Seoul, Korea. 3. Department of Radiology, Seoul National University Hospital, 101 Daehakro, Jongro-gu, Seoul, 03080, Korea. iwishluv@empas.com. 4. Department of Radiology, Seoul National University College of Medicine, Seoul, Korea. iwishluv@empas.com. 5. Institute of Radiation Medicine and Kidney Research Institute, Seoul National University Medical Research Center, Seoul, 03080, Korea.
Abstract
OBJECTIVES: To investigate predictive factors of treatment response following ethanol sclerotherapy of large renal cysts via computed tomography (CT). METHODS: Retrospective study reviewed 71 patients (61.0 ± 13.2 years; M:F = 32:39) who underwent pretreatment CT and were treated with sclerotherapy of a large (> 5 cm) renal cyst (mean volume: 279.8 cc) using 99% ethanol from January 2010 to February 2019. Patients were followed up at least two times, short-term (defined as < 6 months, median 2.1 months) and long-term (defined as > 1 year, median 15.5 months), via ultrasound or CT. Suboptimal response was defined as the volume of residual cyst > 20 mL in each follow-up. Predictive variables of radiologic findings and radiomics features were analyzed using logistic regression analysis. RESULTS: Suboptimal response rates were 33.8% and 18.3% at short-term and long-term follow-ups, respectively. In radiologic findings, patients with suboptimal response in the short-term follow-up showed a more frequent estimated cyst volume ≥ 270 mL (OR 14.8, 95% CI 3.9-55.9, p < 0.001) and sinus protrusion (OR 7.0, 95% CI 1.7-28.5, p = 0.007). Cyst volume ≥ 270 mL was also associated with suboptimal response in the long-term follow-up (OR 4.6, 95% CI 1.3-16.9, p = 0.021). When radiomics features were combined, the area under the curve increased from 0.83 to 0.86 and from 0.68 to 0.82 to predict suboptimal response in short-term and long-term follow-ups, respectively. CONCLUSION: Greater estimated volume, sinus protrusion, and radiomics features of the cysts in pretreatment CT can help predict suboptimal response of renal cyst after sclerotherapy.
OBJECTIVES: To investigate predictive factors of treatment response following ethanol sclerotherapy of large renal cysts via computed tomography (CT). METHODS: Retrospective study reviewed 71 patients (61.0 ± 13.2 years; M:F = 32:39) who underwent pretreatment CT and were treated with sclerotherapy of a large (> 5 cm) renal cyst (mean volume: 279.8 cc) using 99% ethanol from January 2010 to February 2019. Patients were followed up at least two times, short-term (defined as < 6 months, median 2.1 months) and long-term (defined as > 1 year, median 15.5 months), via ultrasound or CT. Suboptimal response was defined as the volume of residual cyst > 20 mL in each follow-up. Predictive variables of radiologic findings and radiomics features were analyzed using logistic regression analysis. RESULTS: Suboptimal response rates were 33.8% and 18.3% at short-term and long-term follow-ups, respectively. In radiologic findings, patients with suboptimal response in the short-term follow-up showed a more frequent estimated cyst volume ≥ 270 mL (OR 14.8, 95% CI 3.9-55.9, p < 0.001) and sinus protrusion (OR 7.0, 95% CI 1.7-28.5, p = 0.007). Cyst volume ≥ 270 mL was also associated with suboptimal response in the long-term follow-up (OR 4.6, 95% CI 1.3-16.9, p = 0.021). When radiomics features were combined, the area under the curve increased from 0.83 to 0.86 and from 0.68 to 0.82 to predict suboptimal response in short-term and long-term follow-ups, respectively. CONCLUSION: Greater estimated volume, sinus protrusion, and radiomics features of the cysts in pretreatment CT can help predict suboptimal response of renal cyst after sclerotherapy.
Authors: Marius E Mayerhoefer; Andrzej Materka; Georg Langs; Ida Häggström; Piotr Szczypiński; Peter Gibbs; Gary Cook Journal: J Nucl Med Date: 2020-02-14 Impact factor: 11.082