Musaddiq J. Awan
Case Western Reserve University
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Radiotherapy and Oncology | 2014
Gary V. Walker; Musaddiq J. Awan; Randa Tao; Eugene J. Koay; Nicholas S. Boehling; Jonathan D. Grant; Dean F. Sittig; G.B. Gunn; Adam S. Garden; Jack Phan; William H. Morrison; David I. Rosenthal; Abdallah S.R. Mohamed; Clifton D. Fuller
BACKGROUND AND PURPOSE Target volumes and organs-at-risk (OARs) for radiotherapy (RT) planning are manually defined, which is a tedious and inaccurate process. We sought to assess the feasibility, time reduction, and acceptability of an atlas-based autosegmentation (AS) compared to manual segmentation (MS) of OARs. MATERIALS AND METHODS A commercial platform generated 16 OARs. Resident physicians were randomly assigned to modify AS OAR (AS+R) or to draw MS OAR followed by attending physician correction. Dice similarity coefficient (DSC) was used to measure overlap between groups compared with attending approved OARs (DSC=1 means perfect overlap). 40 cases were segmented. RESULTS Mean ± SD segmentation time in the AS+R group was 19.7 ± 8.0 min, compared to 28.5 ± 8.0 min in the MS cohort, amounting to a 30.9% time reduction (Wilcoxon p<0.01). For each OAR, AS DSC was statistically different from both AS+R and MS ROIs (all Steel-Dwass p<0.01) except the spinal cord and the mandible, suggesting oversight of AS/MS processes is required; AS+R and MS DSCs were non-different. AS compared to attending approved OAR DSCs varied considerably, with a chiasm mean ± SD DSC of 0.37 ± 0.32 and brainstem of 0.97 ± 0.03. CONCLUSIONS Autosegmentation provides a time savings in head and neck regions of interest generation. However, attending physician approval remains vital.
Oral Oncology | 2014
Musaddiq J. Awan; Abdallah S.R. Mohamed; Jan S. Lewin; Charles A. Baron; G. Brandon Gunn; David I. Rosenthal; F. Christopher Holsinger; David L. Schwartz; Clifton D. Fuller; Katherine A. Hutcheson
BACKGROUND AND OBJECTIVES Late radiation-associated dysphagia (late-RAD) is a rare delayed toxicity, in oropharyngeal cancer (OPC) survivors. Prevention of late-RAD is paramount because the functional impairment can be profound and refractory to standard therapies. The objective of this analysis is to identify candidate dosimetric predictors of late-RAD and associated lower cranial neuropathies after radiotherapy (RT) or chemo-RT (CRT) for OPC. MATERIALS AND METHODS An unmatched retrospective case-control analysis was conducted. Late-RAD cases were identified among OPC patients treated with definitive RT or CRT. Controls were selected with minimum of 6 years without symptoms of late-RAD. Dysphagia-aspiration related structures (DARS) and regions of interest containing cranial nerve paths (RCCNPs) were retrospectively contoured. Dose volume histograms were calculated. Non-parametric bivariate associations were analyzed with Bonferroni correction and multiple logistic regression models were fit. RESULTS Thirty-eight patients were included (12 late-RAD cases, 26 controls). Median latency to late-RAD was 5.8 years (range: 4.5-11.3 years). Lower cranial neuropathies were present in 10 of 12 late-RAD cases. Mean superior pharyngeal constrictor (SPC) dose was higher in cases relative to controls (median: 70.5 vs. 61.6 Gy). Mean SPC dose significantly predicted late-RAD (p = 0.036) and related cranial neuropathies (p = 0.019). RCCNPs did not significantly predict late-RAD or cranial neuropathies. CONCLUSIONS SPC dose may predict for late-RAD and related lower cranial neuropathies. These data, and those of previous studies that have associated SPC dose with classical dysphagia endpoints, suggest impetus to constrain dose to the SPCs when possible.
Radiology | 2015
Abdallah S.R. Mohamed; Manee Naad Ruangskul; Musaddiq J. Awan; Charles A. Baron; Jayashree Kalpathy-Cramer; Richard Castillo; Edward Castillo; Thomas Guerrero; Esengul Kocak-Uzel; Jinzhong Yang; L Court; M Kantor; G. Brandon Gunn; Rivka R. Colen; Steven J. Frank; Adam S. Garden; David I. Rosenthal; Clifton D. Fuller
PURPOSE To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy-simulation computed tomography (CT) with diagnostic CT coregistration. MATERIALS AND METHODS Radiation therapy-simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95% maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison. RESULTS A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P < .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. CONCLUSION Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation.
Journal of Digital Imaging | 2014
Jayashree Kalpathy-Cramer; Musaddiq J. Awan; Steven Bedrick; Coen R. N. Rasch; David I. Rosenthal; Clifton D. Fuller
Modern radiotherapy requires accurate region of interest (ROI) inputs for plan optimization and delivery. Target delineation, however, remains operator-dependent and potentially serves as a major source of treatment delivery error. In order to optimize this critical, yet observer-driven process, a flexible web-based platform for individual and cooperative target delineation analysis and instruction was developed in order to meet the following unmet needs: (1) an open-source/open-access platform for automated/semiautomated quantitative interobserver and intraobserver ROI analysis and comparison, (2) a real-time interface for radiation oncology trainee online self-education in ROI definition, and (3) a source for pilot data to develop and validate quality metrics for institutional and cooperative group quality assurance efforts. The resultant software, Target Contour Testing/Instructional Computer Software (TaCTICS), developed using Ruby on Rails, has since been implemented and proven flexible, feasible, and useful in several distinct analytical and research applications.
Practical radiation oncology | 2013
Musaddiq J. Awan; Jayashree Kalpathy-Cramer; G. Brandon Gunn; Beth M. Beadle; Adam S. Garden; Jack Phan; Emma B. Holliday; William E. Jones; Elizabeth Maani; A.J. Patel; Jehee Choi; V. Clyburn; Bundhit Tantiwongkosi; David I. Rosenthal; Clifton D. Fuller
PURPOSE A number of studies have previously assessed the role of teaching interventions to improve organ-at-risk (OAR) delineation. We present a preliminary study demonstrating the benefit of a combined atlas and real time software-based feedback intervention to aid in contouring of OARs in the head and neck. METHODS AND MATERIALS The study consisted of a baseline evaluation, a real-time feedback intervention, atlas presentation, and a follow-up evaluation. At baseline evaluation, 8 resident observers contoured 26 OARs on a computed tomography scan without intervention or aid. They then received feedback comparing their contours both statistically and graphically to a set of atlas-based expert contours. Additionally, they received access to an atlas to contour these structures. The resident observers were then asked to contour the same 26 OARs on a separate computed tomography scan with atlas access. In addition, 6 experts (5 radiation oncologists specializing in the head and neck, and 1 neuroradiologist) contoured the 26 OARs on both scans. A simultaneous truth and performance level estimation (STAPLE) composite of the expert contours was used as a gold-standard set for analysis of OAR contouring. RESULTS Of the 8 resident observers who initially participated in the study, 7 completed both phases of the study. Dice similarity coefficients were calculated for each user-drawn structure relative to the expert STAPLE composite for each structure. Mean dice similarity coefficients across all structures increased between phase 1 and phase 2 for each resident observer, demonstrating a statistically significant improvement in overall OAR-contouring ability (P < .01). Additionally, intervention improved contouring in 16/26 delineated organs-at-risk across resident observers at a statistically significant level (P ≤ .05) including all otic structures and suprahyoid lymph node levels of the head and neck. CONCLUSIONS Our data suggest that a combined atlas and real-time feedback-based educational intervention detectably improves contouring of OARs in the head and neck.
Scientific Reports | 2016
Vlad C. Sandulache; Brian P. Hobbs; R. Abdallah S Mohamed; Steven J. Frank; Juhee Song; Yao Ding; Rachel B. Ger; L Court; Jayashree Kalpathy-Cramer; John D. Hazle; Jihong Wang; Musaddiq J. Awan; David I. Rosenthal; Adam S. Garden; G. Brandon Gunn; Rivka R. Colen; Nabil Elshafeey; Mohamed Elbanan; Katherine A. Hutcheson; Jan S. Lewin; Mark S. Chambers; Theresa M. Hofstede; Randal S. Weber; Stephen Y. Lai; Clifton D. Fuller
Normal tissue toxicity is an important consideration in the continued development of more effective external beam radiotherapy (EBRT) regimens for head and neck tumors. The ability to detect EBRT-induced changes in mandibular bone vascularity represents a crucial step in decreasing potential toxicity. To date, no imaging modality has been shown to detect changes in bone vascularity in real time during treatment. Based on our institutional experience with multi-parametric MRI, we hypothesized that DCE-MRI can provide in-treatment information regarding EBRT-induced changes in mandibular vascularity. Thirty-two patients undergoing EBRT treatment for head and neck cancer were prospectively imaged prior to, mid-course, and following treatment. DCE-MRI scans were co-registered to dosimetric maps to correlate EBRT dose and change in mandibular bone vascularity as measured by Ktrans and Ve. DCE-MRI was able to detect dose-dependent changes in both Ktrans and Ve in a subset of patients. One patient who developed ORN during the study period demonstrated decreases in Ktrans and Ve following treatment completion. We demonstrate, in a prospective imaging trial, that DCE-MRI can detect dose-dependent alterations in mandibular bone vascularity during chemoradiotherapy, providing biomarkers that are physiological correlates of acute of acute mandibular vascular injury and recovery temporal kinetics.
Radiotherapy and Oncology | 2014
Panayiotis Mavroidis; Drosoula Giantsoudis; Musaddiq J. Awan; Jasper Nijkamp; Coen R. N. Rasch; J. Duppen; Charles R. Thomas; Paul Okunieff; William Elton Jones; Lisa A. Kachnic; N Papanikolaou; Clifton D. Fuller
PURPOSE The aim of this study is to ascertain the subsequent radiobiological impact of using a consensus guideline target volume delineation atlas. MATERIALS AND METHODS Using a representative case and target volume delineation instructions derived from a proposed IMRT rectal cancer clinical trial, gross tumor volume (GTV) and clinical/planning target volumes (CTV/PTV) were contoured by 13 physician observers (Phase 1). The observers were then randomly assigned to follow (atlas) or not-follow (control) a consensus guideline/atlas for anorectal cancers, and instructed to re-contour the same case (Phase 2). RESULTS The atlas group was found to have increased tumor control probability (TCP) after the atlas intervention for both the CTV (p<0.0001) and PTV1 (p=0.0011) with decreasing normal tissue complication probability (NTCP) for small intestine, while the control group did not. Additionally, the atlas group had reduced variance in TCP for all target volumes and reduced variance in NTCP for the bowel. In Phase 2, the atlas group had increased TCP relative to the control for CTV (p=0.03). CONCLUSIONS Visual atlas and consensus treatment guideline usage in the development of rectal cancer IMRT treatment plans reduced the inter-observer radiobiological variation, with clinically relevant TCP alteration for CTV and PTV volumes.
Journal of Applied Clinical Medical Physics | 2015
Charles A. Baron; Musaddiq J. Awan; Abdallah S.R. Mohamed; Imad Akel; David I. Rosenthal; G. Brandon Gunn; Adam S. Garden; Brandon A. Dyer; L Court; Parag R. Sevak; Esengul Kocak-Uzel; Clifton D. Fuller
Larynx may alternatively serve as a target or organs at risk (OAR) in head and neck cancer (HNC) image‐guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population‐based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT on‐rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior‐anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other six points were calculated postisocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all six points for all scans over the course of treatment was calculated. Residual systematic and random error and the necessary compensatory CTV‐to‐PTV and OAR‐to‐PRV margins were calculated, using both observational cohort data and a bootstrap‐resampled population estimator. The grand mean displacements for all anatomical points was 5.07 mm, with mean systematic error of 1.1 mm and mean random setup error of 2.63 mm, while bootstrapped POIs grand mean displacement was 5.09 mm, with mean systematic error of 1.23 mm and mean random setup error of 2.61 mm. Required margin for CTV‐PTV expansion was 4.6 mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9 mm. The calculated OAR‐to‐PRV expansion for the observed residual setup error was 2.7 mm and bootstrap estimated expansion of 2.9 mm. We conclude that the interfractional larynx setup error is a significant source of RT setup/delivery error in HNC, both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5 mm to compensate for setup error if the larynx is a target, or 3 mm if the larynx is an OAR, when using a nonlaryngeal bony isocenter. PACS numbers: 87.55.D‐, 87.55.QrLarynx may alternatively serve as a target or organs at risk (OAR) in head and neck cancer (HNC) image-guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population-based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT on-rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior-anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other six points were calculated postisocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all six points for all scans over the course of treatment was calculated. Residual systematic and random error and the necessary compensatory CTV-to-PTV and OAR-to-PRV margins were calculated, using both observational cohort data and a bootstrap-resampled population estimator. The grand mean displacements for all anatomical points was 5.07 mm, with mean systematic error of 1.1 mm and mean random setup error of 2.63 mm, while bootstrapped POIs grand mean displacement was 5.09 mm, with mean systematic error of 1.23 mm and mean random setup error of 2.61 mm. Required margin for CTV-PTV expansion was 4.6 mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9 mm. The calculated OAR-to-PRV expansion for the observed residual setup error was 2.7 mm and bootstrap estimated expansion of 2.9 mm. We conclude that the interfractional larynx setup error is a significant source of RT setup/delivery error in HNC, both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5 mm to compensate for setup error if the larynx is a target, or 3 mm if the larynx is an OAR, when using a nonlaryngeal bony isocenter. PACS numbers: 87.55.D-, 87.55.Qr.Larynx may alternatively serve as a target or organs at risk (OAR) in head and neck cancer (HNC) image‐guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population‐based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT on‐rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior‐anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other six points were calculated postisocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all six points for all scans over the course of treatment was calculated. Residual systematic and random error and the necessary compensatory CTV‐to‐PTV and OAR‐to‐PRV margins were calculated, using both observational cohort data and a bootstrap‐resampled population estimator. The grand mean displacements for all anatomical points was 5.07 mm, with mean systematic error of 1.1 mm and mean random setup error of 2.63 mm, while bootstrapped POIs grand mean displacement was 5.09 mm, with mean systematic error of 1.23 mm and mean random setup error of 2.61 mm. Required margin for CTV‐PTV expansion was 4.6 mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9 mm. The calculated OAR‐to‐PRV expansion for the observed residual setup error was 2.7 mm and bootstrap estimated expansion of 2.9 mm. We conclude that the interfractional larynx setup error is a significant source of RT setup/delivery error in HNC, both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5 mm to compensate for setup error if the larynx is a target, or 3 mm if the larynx is an OAR, when using a nonlaryngeal bony isocenter. PACS numbers: 87.55.D‐, 87.55.Qr
Scientific Reports | 2017
Rachel B. Ger; Abdallah S.R. Mohamed; Musaddiq J. Awan; Yao Ding; Kimberly Li; Xenia Fave; Andrew Beers; Brandon Driscoll; Hesham Elhalawani; David A. Hormuth; Petra J. van Houdt; Renjie He; Shouhao Zhou; Kelsey B. Mathieu; Heng Li; C. Coolens; Caroline Chung; James A. Bankson; Wei Huang; Jihong Wang; Vlad C. Sandulache; Stephen Y. Lai; Rebecca M. Howell; R. Jason Stafford; Thomas E. Yankeelov; Uulke A. van der Heide; Steven J. Frank; Daniel P. Barboriak; John D. Hazle; L Court
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. Ktrans, ve) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known Ktrans and ve values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain Ktrans and ve kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of Ktrans and 84% of ve algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in ve of the primary gross tumor volume with time. Algorithmic differences in Ktrans and ve values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. Ktrans, ve) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known Ktrans and ve values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain Ktrans and ve kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of Ktrans and 84% of ve algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in ve of the primary gross tumor volume with time. Algorithmic differences in Ktrans and ve values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.
Oral Oncology | 2015
Chad Tang; Clifton D. Fuller; Adam S. Garden; Musaddiq J. Awan; Rivka R. Colen; William H. Morrison; Steven J. Frank; Beth M. Beadle; Jack Phan; Erich M. Sturgis; Mark E. Zafereo; Randal S. Weber; David I. Rosenthal; G. Brandon Gunn
BACKGROUND AND PURPOSE We sought to characterize the pattern of lymph node regression and morphology following definitive radiation therapy (RT) for human papilloma virus (HPV)-associated oropharyngeal carcinoma in patients with disease control. MATERIALS AND METHODS Radiographically positive cervical lymph nodes from patients treated with definitive RT for HPV-associated oropharyngeal carcinoma were segmented on initial pre- and subsequent post-RT contrast enhanced CT images. Pre-specified quantitative nodal parameters were calculated. Initial nodal parameter correlates of final nodal size, final nodal volume, and time to <1 cm short-axis diameter were determined. RESULTS Sixty-six radiographically positive lymph node were analyzed in 36 patients. Lymph nodes exhibited initial volume decreases with size stabilization at ∼4 months. Fifteen nodes (23%) underwent complete radiographic response (median 6.4 months following RT; range 2.9-25.6 months). On multivariate time-to-event analysis, initial hypodense/fat component, nodal volume, and short-axis diameter exhibited inverse association, while higher HU standard deviation exhibited a positive association, with reaching <1 cm short-axis diameter (all p<0.05). CONCLUSIONS Our results showed a substantial decrease in nodal volume within the first 1-2 months following RT. These findings support our current nodal imaging paradigm, propose a quantitative methodology, and describe a reference dataset for further validation and comparison studies.