Browsing by Author "Kelsey, Chris R"
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Item Open Access An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images(Scientific Reports, 2019-12) Lafata, Kyle J; Zhou, Zhennan; Liu, Jian-Guo; Hong, Julian; Kelsey, Chris R; Yin, Fang-FangItem Open Access Association of pre-treatment radiomic features with lung cancer recurrence following stereotactic body radiation therapy.(Physics in medicine and biology, 2019-01-08) Lafata, Kyle J; Hong, Julian C; Geng, Ruiqi; Ackerson, Bradley G; Liu, Jian-Guo; Zhou, Zhennan; Torok, Jordan; Kelsey, Chris R; Yin, Fang-FangThe purpose of this work was to investigate the potential relationship between radiomic features extracted from pre-treatment x-ray CT images and clinical outcomes following stereotactic body radiation therapy (SBRT) for non-small-cell lung cancer (NSCLC). Seventy patients who received SBRT for stage-1 NSCLC were retrospectively identified. The tumor was contoured on pre-treatment free-breathing CT images, from which 43 quantitative radiomic features were extracted to collectively capture tumor morphology, intensity, fine-texture, and coarse-texture. Treatment failure was defined based on cancer recurrence, local cancer recurrence, and non-local cancer recurrence following SBRT. The univariate association between each radiomic feature and each clinical endpoint was analyzed using Welch's t-test, and p-values were corrected for multiple hypothesis testing. Multivariate associations were based on regularized logistic regression with a singular value decomposition to reduce the dimensionality of the radiomics data. Two features demonstrated a statistically significant association with local failure: Homogeneity2 (p = 0.022) and Long-Run-High-Gray-Level-Emphasis (p = 0.048). These results indicate that relatively dense tumors with a homogenous coarse texture might be linked to higher rates of local recurrence. Multivariable logistic regression models produced maximum [Formula: see text] values of [Formula: see text], and [Formula: see text], for the recurrence, local recurrence, and non-local recurrence endpoints, respectively. The CT-based radiomic features used in this study may be more associated with local failure than non-local failure following SBRT for stage I NSCLC. This finding is supported by both univariate and multivariate analyses.Item Open Access Impact of Esophageal Motion on Dosimetry and Toxicity With Thoracic Radiation Therapy.(Technology in cancer research & treatment, 2019-01) Gao, Hao; Kelsey, Chris R; Boyle, John; Xie, Tianyi; Catalano, Suzanne; Wang, Xiaofei; Yin, Fang-FangPURPOSE:To investigate the impact of intra- and inter-fractional esophageal motion on dosimetry and observed toxicity in a phase I dose escalation study of accelerated radiotherapy with concurrent chemotherapy for locally advanced lung cancer. METHODS AND MATERIALS:Patients underwent computed tomography imaging for radiotherapy treatment planning (CT1 and 4DCT1) and at 2 weeks (CT2 and 4DCT2) and 5 weeks (CT3 and 4DCT3) after initiating treatment. Each computed tomography scan consisted of 10-phase 4DCTs in addition to a static free-breathing or breath-hold computed tomography. The esophagus was independently contoured on all computed tomographies and 4DCTs. Both CT2 and CT3 were rigidly registered with CT1 and doses were recalculated using the original intensity-modulated radiation therapy plan based on CT1 to assess the impact of interfractional motion on esophageal dosimetry. Similarly, 4DCT1 data sets were rigidly registered with CT1 to assess the impact of intrafractional motion. The motion was characterized based on the statistical analysis of slice-by-slice center shifts (after registration) for the upper, middle, and lower esophageal regions, respectively. For the dosimetric analysis, the following quantities were calculated and assessed for correlation with toxicity grade: the percent volumes of esophagus that received at least 20 Gy (V20) and 60 Gy (V60), maximum esophageal dose, equivalent uniform dose, and normal tissue complication probability. RESULTS:The interfractional center shifts were 4.4 ± 1.7 mm, 5.5 ± 2.0 mm and 4.9 ± 2.1 mm for the upper, middle, and lower esophageal regions, respectively, while the intrafractional center shifts were 0.6 ± 0.4 mm, 0.7 ± 0.7 mm, and 0.9 ± 0.7 mm, respectively. The mean V60 (and corresponding normal tissue complication probability) values estimated from the interfractional motion analysis were 7.8% (10%), 4.6% (7.5%), 7.5% (8.6%), and 31% (26%) for grade 0, grade 1, grade 2, and grade 3 toxicities, respectively. CONCLUSIONS:Interfractional esophageal motion is significantly larger than intrafractional motion. The mean values of V60 and corresponding normal tissue complication probability, incorporating interfractional esophageal motion, correlated positively with esophageal toxicity grade.Item Open Access Myeloablative conditioning with total body irradiation for AML: Balancing survival and pulmonary toxicity.(Adv Radiat Oncol, 2016-10) Stephens, Sarah J; Thomas, Samantha; Rizzieri, David A; Horwitz, Mitchell E; Chao, Nelson J; Engemann, Ashley M; Lassiter, Martha; Kelsey, Chris RPURPOSE: The purpose of this study was to compare leukemia-free survival (LFS) and other clinical outcomes in patients with acute myelogenous leukemia who underwent a myeloablative allogeneic stem cell transplant with and without total body irradiation (TBI). METHODS AND MATERIALS: Adult patients with acute myelogenous leukemia undergoing myeloablative allogeneic stem cell transplant at Duke University Medical Center between 1995 and 2012 were included. The primary endpoint was LFS. Secondary outcomes included overall survival (OS), nonrelapse mortality, and the risk of pulmonary toxicity. Kaplan-Meier survival estimates and Cox proportional hazards multivariate analyses were performed. RESULTS: A total of 206 patients were evaluated: 90 received TBI-based conditioning regimens and 116 received chemotherapy alone. Median follow-up was 36 months. For all patients, 2-year LFS and OS were 36% (95% confidence interval [CI], 29-43) and 39% (95% CI, 32-46), respectively. After adjusting for known prognostic factors using a multivariate analysis, TBI was associated with improved LFS (hazard ratio: 0.63; 95% CI: 0.44-0.91) and OS (hazard ratio: 0.63; 95% CI, 0.43-0.91). There was no difference in nonrelapse mortality between cohorts, but pulmonary toxicity was significantly more common with TBI (2-year incidence 42% vs 12%,P< .001). High-grade pulmonary toxicity predominated with both conditioning strategies (70% and 93% of cases were grade 3-5 with TBI and chemotherapy alone, respectively). CONCLUSIONS: TBI-based regimens were associated with superior LFS and OS but at the cost of increased pulmonary toxicity.Item Open Access Radiation therapy for primary cutaneous γδ T-cell lymphoma: Case report and literature review.(JAAD case reports, 2019-07) Kelsey, Chris R; Wang, Endi; Stefanovic, Alexandra; Kheterpal, MeenalItem Open Access Spatial-temporal variability of radiomic features and its effect on the classification of lung cancer histology.(Physics in medicine and biology, 2018-11-08) Lafata, Kyle; Cai, Jing; Wang, Chunhao; Hong, Julian; Kelsey, Chris R; Yin, Fang-FangThe purpose of this research was to study the sensitivity of Computed Tomography (CT) radiomic features to motion blurring and signal-to-noise ratios (SNR), and investigate its downstream effect regarding the classification of non-small cell lung cancer (NSCLC) histology. Forty-three radiomic features were considered and classified into one of four categories: Morphological, Intensity, Fine Texture, and Coarse Texture. First, a series of simulations were used to study feature-sensitivity to changes in spatial-temporal resolution. A dynamic digital phantom was used to generate images with different breathing amplitudes and SNR, from which features were extracted and characterized relative to initial simulation conditions. Stage I NSCLC patients were then retrospectively identified, from which three different acquisition-specific feature-spaces were generated based on free-breathing (FB), average-intensity-projection (AIP), and end-of-exhalation (EOE) CT images. These feature-spaces were derived to cover a wide range of spatial-temporal tradeoff. Normalized percent differences and concordance correlation coefficients (CCC) were used to assess the variability between the 3D and 4D acquisition techniques. Subsequently, three corresponding acquisition-specific logistic regression models were developed to classify lung tumor histology. Classification performance was compared between the different data-dependent models. Simulation results demonstrated strong linear dependences (p > 0.95) between respiratory motion and morphological features, as well as between SNR and texture features. The feature Short Run Emphasis was found to be particularly stable to both motion blurring and changes in SNR. When comparing FB-to-EOE, 37% of features demonstrated high CCC agreement (CCC > 0.8), compared to only 30% for FB-to-AIP. In classifying tumor histology, EoE images achieved an average AUC, Accuracy, Sensitivity, and Specificity of [Formula: see text], respectively. FB images achieved respective values of [Formula: see text], and AIP images achieved respective values of [Formula: see text]. Several radiomic features have been identified as being relatively robust to spatial-temporal variations based on both simulation data and patient data. In general, features that were sensitive to motion blurring were not necessarily the same features that were sensitive to changes in SNR. Our modeling results suggest that the EoE phase of a 4DCT acquisition may provide useful radiomic information, particularly for features that are highly sensitive to respiratory motion.