Purpose: Radiomic models elaborate geometric and texture features of tumors extracted from imaging to develop predictors for clinical outcomes. Stereotactic body radiation therapy (SBRT) has been increasingly applied in the ablative treatment of thoracic tumors. This study aims to identify predictors of treatment responses in patients affected by early stage non-small cell lung cancer (NSCLC) or pulmonary oligo-metastases treated with SBRT and to develop an accurate machine learning model to predict radiological response to SBRT. Materials and Methods: Computed tomography (CT) images of 85 tumors (stage I–II NSCLC and pulmonary oligo-metastases) from 69 patients treated with SBRT were analyzed. Gross tumor volumes (GTV) were contoured on CT images. Patients that achieved complete response (CR) or partial response (PR) were defined as responders. One hundred ten radiomic features were extracted using PyRadiomics module based on the GTV. The association of features with response to SBRT was evaluated. A model using support vector machine (SVM) was then trained to predict response based solely on the extracted radiomics features. Receiver operating characteristic curves were constructed to evaluate model performance of the identified radiomic predictors. Results: Sixty-nine patients receiving thoracic SBRT from 2008 to 2018 were retrospectively enrolled. Skewness and root mean squared were identified as radiomic predictors of response to SBRT. The SVM machine learning model developed had an accuracy of 74.8%. The area under curves for CR, PR, and non-responder prediction were 0.86 (95% confidence interval [CI], 0.794–0.921), 0.946 (95% CI, 0.873–0.978), and 0.857 (95% CI, 0.789–0.915), respectively. Conclusion Radiomic analysis of pre-treatment CT scan is a promising tool that can predict tumor response to SBRT.

PURPOSE: The aims of this study were to investigate the prevalence of upper tract involvement in ketamine-associated uropathy, and to determine the predictors of hydronephrosis in patients with a history of ketamine abuse. METHODS: This was a cross-sectional study of a prospective cohort of patients with ketamine-associated uropathy. Data including demographics, pattern of ketamine abuse, pelvic pain and urgency or frequency (PUF) symptom score, uroflowmetry (UFM) parameters, serum renal function, and liver function tests were collected. Upon consultation, ultrasonography was performed to assess the function of the urinary system. RESULTS: From December 2011 to October 2015, we treated 572 patients with ketamine-associated uropathy. Of these patients, 207 (36.2%) had managed to achieve abstinence at the time of their first consultation. Ninety-six patients (16.8%) in the cohort were found to have hydronephrosis on ultrasonography. Univariate analysis identified age, duration of ketamine abuse, PUF symptom score, voided volume on UFM, serum creatinine levels >100 μmol/L, and an abnormal serum liver enzyme profile as factors associated with hydronephrosis. Logistic regression revealed the following parameters to be statistically related to hydronephrosis: age (adjusted odds ratio [OR], 1.090; 95% confidence interval [CI], 1.020–1.166; P=0.012), functional bladder capacity (adjusted OR, 0.997; 95% CI, 0.995–0.999; P=0.029), serum creatinine >100 μmol/L (adjusted OR, 3.107; 95% CI, 1.238–7.794; P=0.016, and an abnormal serum liver enzyme profile (adjusted OR, 1.967; 95% CI, 1.213–3.187; P=0.006). CONCLUSIONS: Ketamine-associated uropathy can involve the upper urinary tract. Patient demographics as well as investigations of UFM, renal function tests, and liver function tests may allow us to identify at-risk patients.
Cohort Studies ; Creatinine ; Cross-Sectional Studies ; Cystitis ; Demography ; Humans ; Hydronephrosis ; Ketamine ; Liver ; Liver Function Tests ; Logistic Models ; Lower Urinary Tract Symptoms ; Odds Ratio ; Pelvic Pain ; Prevalence ; Prospective Studies ; Ultrasonography ; Urinary Bladder ; Urinary Tract* ; Urination Disorders

Adolescent ; Adult ; Cross-Sectional Studies ; Female ; Health Knowledge, Attitudes, Practice ; Humans ; Intensive Care Units ; statistics & numerical data ; Male ; Middle Aged ; Organ Transplantation ; psychology ; statistics & numerical data ; Surveys and Questionnaires ; Tissue and Organ Procurement ; statistics & numerical data ; Young Adult