Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current radiomics models require ...large datasets of images with expert-segmented 3D regions of interest (ROIs). Full ROI segmentation is time consuming and oncologists often outline just RT treatment fields in clinical practice. This presents a challenge for real-world radiomics research. As such, a method that simplifies BM identification but does not compromise the power of radiomics is needed. The objective of this study was to investigate the feasibility of radiomics models for BM detection using lesion-center-based geometric ROIs. The planning-CT images of 170 patients with non-metastatic lung cancer and 189 patients with spinal BM were used. The point locations of 631 BM and 674 healthy bone (HB) regions were identified by experts. ROIs with various geometric shapes were centered and automatically delineated on the identified locations, and 107 radiomics features were extracted. Various feature selection methods and machine learning classifiers were evaluated. Our point-based radiomics pipeline was successful in differentiating BM from HB. Lesion-center-based segmentation approach greatly simplifies the process of preparing images for use in radiomics studies and avoids the bottleneck of full ROI segmentation.
We evaluated the presence of an 'obesity paradox' in coronary artery bypass grafting (CABG) patients, determined its time course and ascertained whether it is associated with improved cardiovascular ...(CV) survival versus non-CV survival.
A retrospective analysis of 3 prospectively collected databases was conducted. A fifteen-year Kaplan-Meier analysis in 7091 CABG patients was performed and repeated in 5 body mass index BMI (kg/m2) cohorts Normal (18.5-24.99 kg/m2), Overweight (25-29.99 kg/m2), Obese I (30-34.99 kg/m2), Obese II (35-39.99 kg/m2) and Obese III (≥40 kg/m2). Mortality hazard ratios {HR 95% confidence interval (CI)} were derived using comprehensive multivariable competing risk Cox regression, accounting for BMI categories for overall (0-15), Early (0-1), Intermediate (1-8) and Late (8-15) postoperative years, to relax the proportional hazards assumption. The regression was repeated using BMI as a continuous variable. Mortality was classified into any, CV and non-CV.
Obese patients were younger with more comorbidities. Fifteen-year survival was improved in the Overweight and Obese I groups (P < 0.001). Adjusted 15-year mortality was reduced in the Overweight HR (95% CI) = 0.88 (0.79-0.98) and Obese I HR = 0.88 (0.78-0.99) groups driven by improved CV and non-CV survival. This trend was noted in the early (Overweight) and intermediate postoperative periods (Overweight and Obese I) with no significance in the late period. Higher mortality in the Obese III HR = 1.28 (1.06-1.55) group was driven by a decreased CV survival. Using BMI as a continuous variable, a BMI of 29 kg/m2 was associated with optimal survival.
We identified a protective partial obesity paradox in the early and intermediate postoperative periods among Overweight and mildly obese (Obese I) patients with improved CV and non-CV survival. The morbidly obese (the Obese III group) had higher early and late CV mortality.
Radiotherapy-related fibrosis remains one of the most challenging treatment related side effects encountered by patients with head and neck cancer. Several established and ongoing novel therapies ...have been studied with paucity of data in how to best treat these patients. This review aims to provide researchers and health care providers with a comprehensive review on the presentation, etiology, and therapeutic options for this serious condition.
The multiarterial grafting survival advantage noted in the overall population undergoing coronary artery bypass grafting is not well defined in the obese. We investigated the early to late survival ...effects of the radial artery in left internal thoracic artery–based multiarterial bypass grafting (radial artery-multiarterial bypass grafting) versus single arterial bypass grafting (left internal thoracic artery-single arterial bypass grafting) in obese patients.
We analyzed 15-year Kaplan–Meier survival in 6102 patients receiving primary, left internal thoracic artery–based coronary artery bypass grafting with 2 or more grafts divided into body mass index groups: nonobese (<30 kg/m2) and all-obese, comprised of mildly obese (30-35 kg/m2) and morbidly obese (>35 kg/m2). Risk-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of radial artery-multiarterial bypass grafting versus left internal thoracic artery-single arterial bypass grafting were derived via Cox regression and applied separately for early (<0.5 years), intermediate (0.5-5 years), and late (5-15 years) follow-up in each body mass index cohort. Propensity score matching between radial artery-multiarterial bypass grafting and left internal thoracic artery-single arterial bypass grafting cohorts within the body mass index groups was performed as a corroborating analysis.
Radial artery-multiarterial bypass grafting was more frequently used in obese patients who were younger (62 ± 10 years; mild/morbid: 45.4%/54.4% radial artery-multiarterial bypass grafting) compared with nonobese patients (66 ± 10 years; 37.4% radial artery-multiarterial bypass grafting). Unadjusted 15-year survival was significantly better for radial artery-multiarterial bypass grafting in all body mass index groups. Multivariate analysis showed a survival benefit of radial artery-multiarterial bypass grafting over the entire 0- to 15-year study period in the all-obese cohort (HR, 0.85; 95% CI, 0.74-0.98) and was more pronounced in the mildly obese (HR, 0.79; 95% CI, 0.66-0.96) versus morbidly obese (HR, 0.88; 95% CI, 0.69-1.13). The radial artery-multiarterial bypass grafting survival benefit was realized between 0.5 and 5 years postoperatively and was comparable for all-obese (HR, 0.69; 95% CI, 0.51-0.94) and nonobese (HR, 0.68; 95% CI, 0.52-0.88) groups. Propensity score matching was confirmatory.
Radial artery-multiarterial bypass grafting confers a long-term survival advantage in both obese and nonobese patients.
Background
The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve ...the quality of life of patients with cancer. Artificial intelligence can aid in the extraction of objective pain biomarkers for patients with cancer with bone metastases (BMs).
Objective
This study aimed to develop and evaluate a scalable natural language processing (NLP)– and radiomics-based machine learning pipeline to differentiate between painless and painful BM lesions in simulation computed tomography (CT) images using imaging features (biomarkers) extracted from lesion center point–based regions of interest (ROIs).
Methods
Patients treated at our comprehensive cancer center who received palliative radiotherapy for thoracic spine BM between January 2016 and September 2019 were included in this retrospective study. Physician-reported pain scores were extracted automatically from radiation oncology consultation notes using an NLP pipeline. BM center points were manually pinpointed on CT images by radiation oncologists. Nested ROIs with various diameters were automatically delineated around these expert-identified BM center points, and radiomics features were extracted from each ROI. Synthetic Minority Oversampling Technique resampling, the Least Absolute Shrinkage And Selection Operator feature selection method, and various machine learning classifiers were evaluated using precision, recall, F1-score, and area under the receiver operating characteristic curve.
Results
Radiation therapy consultation notes and simulation CT images of 176 patients (mean age 66, SD 14 years; 95 males) with thoracic spine BM were included in this study. After BM center point identification, 107 radiomics features were extracted from each spherical ROI using pyradiomics. Data were divided into 70% and 30% training and hold-out test sets, respectively. In the test set, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of our best performing model (neural network classifier on an ensemble ROI) were 0.82 (132/163), 0.59 (16/27), 0.85 (116/136), and 0.83, respectively.
Conclusions
Our NLP- and radiomics-based machine learning pipeline was successful in differentiating between painful and painless BM lesions. It is intrinsically scalable by using NLP to extract pain scores from clinical notes and by requiring only center points to identify BM lesions in CT images.
The purpose of this study was to evaluate patient-related non-dosimetric predictors of cardiac sparing with the use of deep inspiration breath-hold (DIBH) in patients with left-sided breast cancer ...undergoing irradiation (RT).
We retrospectively reviewed charts and treatment plans of one-hundred and three patients with left-sided breast cancer. All patients had both free-breathing (FB) and DIBH (with body surface tracking) plans available. (MHD) and V4 (heart volume receiving at least 4 Gy) were extracted from dose volume histograms. Fisher's exact and Chi-square tests were used to identify predictors of reductions in MHD and V4 after DIBH.
One-hundred and three patients were identified and most underwent mastectomy. MHD and V4 decreased significantly in DIBH plans (0.74 ± 0.25 Gy vs. 1.72 ± 0.98 Gy,
< 0.0001 for MHD; 4 ± 4.98 cc vs. 20.79 ± 18.2 cc,
< 0.0001 for V4). Body mass index (BMI), smoking and timing of CT simulation (spring/winter vs. summer/fall) were significant predictors of reduction in MHD whereas BMI, field size, chemotherapy, axillary dissection, and timing of CT simulation predicted reduction in V4. On multivariate analysis, BMI, and timing of CT simulation remained significant predictors of the heart-sparing effect of DIBH.
In the setting of limited resources, identifying patients who will benefit the most from DIBH is extremely important. Prior studies have identified multiple dosimetric predictors of cardiac sparing and hereby we identified new non-dosimetric factors such as BMI and timing of treatments.
Every year, almost 62,000 are diagnosed with a head and neck cancer (HNC) and 13,000 will succumb to their disease. In the primary setting, intraoperative radiation therapy (IORT) can be used as a ...boost in select patients in order to optimize local control. Addition of external beam radiation to limited volumes results in improved disease control over surgery and IORT alone. In the recurrent setting, IORT can improve outcomes from salvage surgery especially in patients previously treated with external beam radiation. The use of IORT remains limited to select institutions with various modalities being currently employed including orthovoltage, electrons, and high-dose rate brachytherapy. Practically, execution of IORT requires a coordinated effort and careful planning by a multidisciplinary team involving the head and neck surgeon, radiation oncologist, and physicist. The current review summarizes common uses, outcomes, toxicities, and technical aspects of IORT in HNC patients.
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