Publications by authors named "Joey Cheung"

25 Publications

  • Page 1 of 1

Gender Differences in the Relationship between Anger and Aggressive Behavior.

J Interpers Violence 2021 Feb 5:886260521991870. Epub 2021 Feb 5.

The Ohio State University Wexner Medical Center, Columbus, OH, USA.

Evidence is mixed regarding differences in prevalence of aggressive behavior, with many (though not all) studies suggesting that men are more aggressive than women. Furthermore, while aggression often occurs in response to provocation-induced anger, this relationship may be stronger for men; women may be more likely to engage in non-aggressive (e.g., affiliative) behaviors in response to provocation, particularly at low-level provocation. This study examined gender differences in aggression as well as differences in the relationship between anger and aggression for men and women. Adults ( = 424) participated in a behavioral aggression task, and a subset of participants ( = 304) completed a questionnaire assessing trait levels of anger as part of a larger study at a large midwestern university. Results indicated that while men and women aggressed at similar levels, aggression was significantly associated with trait anger for men only, at low levels of provocation, with only a trending relationship for high provocation. This suggests that while men and women may be equally aggressive in certain situations, this behavior may be differentially associated with anger.
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http://dx.doi.org/10.1177/0886260521991870DOI Listing
February 2021

Studying pre-treatment and ketamine-induced changes in white matter microstructure in the context of ketamine's antidepressant effects.

Transl Psychiatry 2020 12 15;10(1):432. Epub 2020 Dec 15.

Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Ketamine is increasingly being used as a therapeutic for treatment-resistant depression (TRD), yet the effects of ketamine on the human brain remain largely unknown. This pilot study employed diffusion magnetic resonance imaging (dMRI) to examine relationships between ketamine treatment and white matter (WM) microstructure, with the aim of increasing the current understanding of ketamine's neural mechanisms of action in humans. Longitudinal dMRI data were acquired from 13 individuals with TRD two hours prior to (pre-infusion), and four hours following (post-infusion), an intravenous ketamine infusion. Free-water imaging was employed to quantify cerebrospinal fluid-corrected mean fractional anisotropy (FA) in 15 WM bundles pre- and post-infusion. Analyses revealed that higher pre-infusion FA in the left cingulum bundle and the left superior longitudinal fasciculus was associated with greater depression symptom improvement 24 h post-ketamine. Moreover, four hours after intravenous administration of ketamine, FA rapidly increased in numerous WM bundles in the brain; this increase was significantly associated with 24 h symptom improvement in select bundles. Overall, the results of this preliminary study suggest that WM properties, as measured by dMRI, may have a potential impact on clinical improvement following ketamine. Ketamine administration additionally appears to be associated with rapid WM diffusivity changes, suggestive of rapid changes in WM microstructure. This study thus points to pre-treatment WM structure as a potential factor associated with ketamine's clinical efficacy, and to post-treatment microstructural changes as a candidate neuroimaging marker of ketamine's cellular mechanisms.
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http://dx.doi.org/10.1038/s41398-020-01122-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738670PMC
December 2020

Studying pre-treatment and ketamine-induced changes in white matter microstructure in the context of ketamine's antidepressant effects.

Transl Psychiatry 2020 12 15;10(1):432. Epub 2020 Dec 15.

Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Ketamine is increasingly being used as a therapeutic for treatment-resistant depression (TRD), yet the effects of ketamine on the human brain remain largely unknown. This pilot study employed diffusion magnetic resonance imaging (dMRI) to examine relationships between ketamine treatment and white matter (WM) microstructure, with the aim of increasing the current understanding of ketamine's neural mechanisms of action in humans. Longitudinal dMRI data were acquired from 13 individuals with TRD two hours prior to (pre-infusion), and four hours following (post-infusion), an intravenous ketamine infusion. Free-water imaging was employed to quantify cerebrospinal fluid-corrected mean fractional anisotropy (FA) in 15 WM bundles pre- and post-infusion. Analyses revealed that higher pre-infusion FA in the left cingulum bundle and the left superior longitudinal fasciculus was associated with greater depression symptom improvement 24 h post-ketamine. Moreover, four hours after intravenous administration of ketamine, FA rapidly increased in numerous WM bundles in the brain; this increase was significantly associated with 24 h symptom improvement in select bundles. Overall, the results of this preliminary study suggest that WM properties, as measured by dMRI, may have a potential impact on clinical improvement following ketamine. Ketamine administration additionally appears to be associated with rapid WM diffusivity changes, suggestive of rapid changes in WM microstructure. This study thus points to pre-treatment WM structure as a potential factor associated with ketamine's clinical efficacy, and to post-treatment microstructural changes as a candidate neuroimaging marker of ketamine's cellular mechanisms.
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http://dx.doi.org/10.1038/s41398-020-01122-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738670PMC
December 2020

Studying pre-treatment and ketamine-induced changes in white matter microstructure in the context of ketamine's antidepressant effects.

Transl Psychiatry 2020 12 15;10(1):432. Epub 2020 Dec 15.

Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Ketamine is increasingly being used as a therapeutic for treatment-resistant depression (TRD), yet the effects of ketamine on the human brain remain largely unknown. This pilot study employed diffusion magnetic resonance imaging (dMRI) to examine relationships between ketamine treatment and white matter (WM) microstructure, with the aim of increasing the current understanding of ketamine's neural mechanisms of action in humans. Longitudinal dMRI data were acquired from 13 individuals with TRD two hours prior to (pre-infusion), and four hours following (post-infusion), an intravenous ketamine infusion. Free-water imaging was employed to quantify cerebrospinal fluid-corrected mean fractional anisotropy (FA) in 15 WM bundles pre- and post-infusion. Analyses revealed that higher pre-infusion FA in the left cingulum bundle and the left superior longitudinal fasciculus was associated with greater depression symptom improvement 24 h post-ketamine. Moreover, four hours after intravenous administration of ketamine, FA rapidly increased in numerous WM bundles in the brain; this increase was significantly associated with 24 h symptom improvement in select bundles. Overall, the results of this preliminary study suggest that WM properties, as measured by dMRI, may have a potential impact on clinical improvement following ketamine. Ketamine administration additionally appears to be associated with rapid WM diffusivity changes, suggestive of rapid changes in WM microstructure. This study thus points to pre-treatment WM structure as a potential factor associated with ketamine's clinical efficacy, and to post-treatment microstructural changes as a candidate neuroimaging marker of ketamine's cellular mechanisms.
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http://dx.doi.org/10.1038/s41398-020-01122-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738670PMC
December 2020

Optimizing beam models for dosimetric accuracy over a wide range of treatments.

Phys Med 2019 Feb 24;58:47-53. Epub 2019 Jan 24.

Department of Radiation Oncology, University of California San Francisco, 1600 Divisadero Street, Suite H1031, San Francisco, CA 94115, United States.

This work presents a systematic approach for testing a dose calculation algorithm over a variety of conditions designed to span the possible range of clinical treatment plans. Using this method, a TrueBeam STx machine with high definition multi-leaf collimators (MLCs) was commissioned in the RayStation treatment planning system (TPS). The initial model parameters values were determined by comparing TPS calculations with standard measured depth dose and profile curves. The MLC leaf offset calibration was determined by comparing measured and calculated field edges utilizing a wide range of MLC retracted and over-travel positions. The radial fluence was adjusted using profiles through both the center and corners of the largest field size, and through measurements of small fields that were located at highly off-axis positions. The flattening filter source was adjusted to improve the TPS agreement for the output of MLC-defined fields with much larger jaw openings. The MLC leaf transmission and leaf end parameters were adjusted to optimize the TPS agreement for highly modulated intensity-modulated radiotherapy (IMRT) plans. The final model was validated for simple open fields, multiple field configurations, the TG 119 C-shape target test, and a battery of clinical IMRT and volumetric-modulated arc therapy (VMAT) plans. The commissioning process detected potential dosimetric errors of over 10% and resulted in a final model that provided in general 3% dosimetric accuracy. This study demonstrates the importance of using a variety of conditions to adjust a beam model and provides an effective framework for achieving high dosimetric accuracy.
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http://dx.doi.org/10.1016/j.ejmp.2019.01.011DOI Listing
February 2019

Evaluating the impact of extended field-of-view CT reconstructions on CT values and dosimetric accuracy for radiation therapy.

Med Phys 2019 Feb 14;46(2):892-901. Epub 2018 Dec 14.

Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA.

Purpose: Wide bore CT scanners use extended field-of-view (eFOV) reconstruction algorithms to attempt to recreate tissue truncated due to large patient habitus. Radiation therapy planning systems rely on accurate CT numbers in order to correctly plan and calculate radiation dose. This study looks at the impact of eFOV reconstructions on CT numbers and radiation dose calculations in real patient geometries.

Methods: A large modular phantom based on real patient geometries was created to surround a CIRS Model 062M phantom. The modular sections included a smooth patient surface, a skin fold in the patient surface, and the addition of arms for simulation of the patient in arms up or arms down position. This phantom was used to evaluate the accuracy of CT numbers for three extended FOV algorithms implemented on Siemens CT scanners: eFOV, HDFOV, and HDProFOV. Six different configurations of the phantoms were scanned and images were reconstructed for the three different extended FOV algorithms. The CIRS phantom inserts and overall phantom geometry were contoured in each image, and the Hounsfield units (HU) numbers were compared to an image of the phantom within the standard scan FOV (sFOV) without the modular sections. To evaluate the effect on dose calculations, six radiotherapy patients previously treated at our institution (three head and neck and three chest/pelvis) whose body circumferences extended past the 50 cm sFOV in the treatment planning CT were used. Images acquired on a Siemens Sensation Open scanner were reconstructed using sFOV, eFOV and HDFOV algorithms. A physician and dosimetrist identified the radiation target, critical organs, and external patient contour. A benchmark CT was created for each patient, consisting of an average of the 3 CT reconstructions with a density override applied to regions containing truncation artifacts. The benchmark CT was used to create an optimal radiation treatment plan. The plan was copied onto each CT reconstruction without density override and dose was recalculated.

Results: Tissue extending past the sFOV impacts the HU numbers for tissues inside and outside the sFOV when using extended FOV reconstructions. On average, the HU for all CIRS density inserts in the arms up (arms down) position varied by 43 HU (67 HU), 39 HU (73 HU), and 18 HU (51 HU) for the eFOV, HDFOV, and HDProFOV scans, respectively. In the patient dose calculations, patients with a smooth patient contour had the least deviation from the benchmark in the HDFOV (0.1-0.5%) compared to eFOV (0.4-1.8%) reconstructions. In cases with large amounts of tissue and irregular skin folds, the eFOV deviated the least from the benchmark (range 0.2-0.6% dose difference) compared to HDFOV (range 1.3-1.8% dose difference).

Conclusions: All reconstruction algorithms demonstrated good CT number accuracy in the center of the image. Larger artifacts are seen near and extending outside the scan FOV, however, dose calculations performed using typical beam arrangements using the extended FOV reconstructions were still mostly within 2.5% of best estimated reference values.
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http://dx.doi.org/10.1002/mp.13299DOI Listing
February 2019

Evaluating the impact of extended field-of-view CT reconstructions on CT values and dosimetric accuracy for radiation therapy.

Med Phys 2019 Feb 14;46(2):892-901. Epub 2018 Dec 14.

Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA.

Purpose: Wide bore CT scanners use extended field-of-view (eFOV) reconstruction algorithms to attempt to recreate tissue truncated due to large patient habitus. Radiation therapy planning systems rely on accurate CT numbers in order to correctly plan and calculate radiation dose. This study looks at the impact of eFOV reconstructions on CT numbers and radiation dose calculations in real patient geometries.

Methods: A large modular phantom based on real patient geometries was created to surround a CIRS Model 062M phantom. The modular sections included a smooth patient surface, a skin fold in the patient surface, and the addition of arms for simulation of the patient in arms up or arms down position. This phantom was used to evaluate the accuracy of CT numbers for three extended FOV algorithms implemented on Siemens CT scanners: eFOV, HDFOV, and HDProFOV. Six different configurations of the phantoms were scanned and images were reconstructed for the three different extended FOV algorithms. The CIRS phantom inserts and overall phantom geometry were contoured in each image, and the Hounsfield units (HU) numbers were compared to an image of the phantom within the standard scan FOV (sFOV) without the modular sections. To evaluate the effect on dose calculations, six radiotherapy patients previously treated at our institution (three head and neck and three chest/pelvis) whose body circumferences extended past the 50 cm sFOV in the treatment planning CT were used. Images acquired on a Siemens Sensation Open scanner were reconstructed using sFOV, eFOV and HDFOV algorithms. A physician and dosimetrist identified the radiation target, critical organs, and external patient contour. A benchmark CT was created for each patient, consisting of an average of the 3 CT reconstructions with a density override applied to regions containing truncation artifacts. The benchmark CT was used to create an optimal radiation treatment plan. The plan was copied onto each CT reconstruction without density override and dose was recalculated.

Results: Tissue extending past the sFOV impacts the HU numbers for tissues inside and outside the sFOV when using extended FOV reconstructions. On average, the HU for all CIRS density inserts in the arms up (arms down) position varied by 43 HU (67 HU), 39 HU (73 HU), and 18 HU (51 HU) for the eFOV, HDFOV, and HDProFOV scans, respectively. In the patient dose calculations, patients with a smooth patient contour had the least deviation from the benchmark in the HDFOV (0.1-0.5%) compared to eFOV (0.4-1.8%) reconstructions. In cases with large amounts of tissue and irregular skin folds, the eFOV deviated the least from the benchmark (range 0.2-0.6% dose difference) compared to HDFOV (range 1.3-1.8% dose difference).

Conclusions: All reconstruction algorithms demonstrated good CT number accuracy in the center of the image. Larger artifacts are seen near and extending outside the scan FOV, however, dose calculations performed using typical beam arrangements using the extended FOV reconstructions were still mostly within 2.5% of best estimated reference values.
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http://dx.doi.org/10.1002/mp.13299DOI Listing
February 2019

A continuous arc delivery optimization algorithm for CyberKnife m6.

Med Phys 2018 Jun 1. Epub 2018 Jun 1.

Department of Radiation Oncology, University of California, San Francisco, CA, USA.

Purpose: This study aims to reduce the delivery time of CyberKnife m6 treatments by allowing for noncoplanar continuous arc delivery. To achieve this, a novel noncoplanar continuous arc delivery optimization algorithm was developed for the CyberKnife m6 treatment system (CyberArc-m6).

Methods And Materials: CyberArc-m6 uses a five-step overarching strategy, in which an initial set of beam geometries is determined, the robotic delivery path is calculated, direct aperture optimization is conducted, intermediate MLC configurations are extracted, and the final beam weights are computed for the continuous arc radiation source model. This algorithm was implemented on five prostate and three brain patients, previously planned using a conventional step-and-shoot CyberKnife m6 delivery technique. The dosimetric quality of the CyberArc-m6 plans was assessed using locally confined mutual information (LCMI), conformity index (CI), heterogeneity index (HI), and a variety of common clinical dosimetric objectives.

Results: Using conservative optimization tuning parameters, CyberArc-m6 plans were able to achieve an average CI difference of 0.036 ± 0.025, an average HI difference of 0.046 ± 0.038, and an average LCMI of 0.920 ± 0.030 compared with the original CyberKnife m6 plans. Including a 5 s per minute image alignment time and a 5-min setup time, conservative CyberArc-m6 plans achieved an average treatment delivery speed up of 1.545x ± 0.305x compared with step-and-shoot plans.

Conclusions: The CyberArc-m6 algorithm was able to achieve dosimetrically similar plans compared to their step-and-shoot CyberKnife m6 counterparts, while simultaneously reducing treatment delivery times.
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http://dx.doi.org/10.1002/mp.13022DOI Listing
June 2018

A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants.

BMC Genomics 2018 Apr 16;19(1):257. Epub 2018 Apr 16.

The New Zealand Institute for Plant & Food Research Ltd (PFR), Private Bag 92169, Auckland, 1142, New Zealand.

Background: Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models.

Results: A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models.

Conclusions: Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and correction of gene models enabling improvement of computational prediction. This utility was especially relevant for certain types of gene families such as the EXPANSIN like genes. Finally, this high quality gene set will supply the kiwifruit and general plant community with a new tool for genomics and other comparative analysis.
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http://dx.doi.org/10.1186/s12864-018-4656-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902842PMC
April 2018

Commissioning and Evaluation of an Electronic Portal Imaging Device-Based In-Vivo Dosimetry Software.

Cureus 2018 Feb 2;10(2):e2139. Epub 2018 Feb 2.

Radiation Oncology, University of California San Francisco.

This study reports on our experience with the in-vivo dose verification software, EPIgray® (DOSIsoft, Cachan, France). After the initial commissioning process, clinical experiments on phantom treatments were evaluated to assess the level of accuracy of the electronic portal imaging device (EPID) based in-vivo dose verification. EPIgray was commissioned based on the company's instructions. This involved ion chamber measurements and portal imaging of solid water blocks of various thicknesses between 5 and 35 cm. Field sizes varied between 2 x 2 cm and 20 x 20 cm. The determined conversion factors were adjusted through an additional iterative process using treatment planning system calculations. Subsequently, evaluation was performed using treatment plans of single and opposed beams, as well as intensity modulated radiotherapy (IMRT) plans, based on recommendations from the task group report TG-119 to test for dose reconstruction accuracy. All tests were performed using blocks of solid water slabs as a phantom. For single square fields, the dose at isocenter was reconstructed within 3% accuracy in EPIgray compared to the treatment planning system dose. Similarly, the relative deviation of the total dose was accurately reconstructed within 3% for all IMRT plans with points placed inside a high-dose region near the isocenter. Predictions became less accurate than < 5% when the evaluation point was outside the treatment target. Dose at points 5 cm or more away from the isocenter or within an avoidance structure was reconstructed less reliably. EPIgray formalism accuracy is adequate for an efficient error detection system with verifications performed in high-dose volumes. It provides immediate intra-fractional feedback on the delivery of treatment plans without affecting the treatment beam. Besides the EPID, no additional hardware is required. The software evaluates local point dose measurements to verify treatment plan delivery and patient positioning within 5% accuracy, depending on the placement of evaluation points.
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http://dx.doi.org/10.7759/cureus.2139DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5880591PMC
February 2018

Deep nets vs expert designed features in medical physics: An IMRT QA case study.

Med Phys 2018 Jun 18;45(6):2672-2680. Epub 2018 Apr 18.

Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA.

Purpose: The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA).

Method: A total of 498 IMRT plans across all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. Measurements were performed using a commercial 2D diode array, and passing rates for 3%/3 mm local dose/distance-to-agreement (DTA) were recorded. Separately, fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). The CNNs were trained to predict IMRT QA gamma passing rates using TensorFlow and Keras. A set of model architectures, inspired by the convolutional blocks of the VGG-16 ImageNet model, were constructed and implemented. Synthetic data, created by rotating and translating the fluence maps during training, was created to boost the performance of the CNNs. Dropout, batch normalization, and data augmentation were utilized to help train the model. The performance of the CNNs was compared to a generalized Poisson regression model, previously developed for this application, which used 78 expert designed features.

Results: Deep Neural Networks without domain knowledge achieved comparable performance to a baseline system designed by domain experts in the prediction of 3%/3 mm Local gamma passing rates. An ensemble of neural nets resulted in a mean absolute error (MAE) of 0.70 ± 0.05 and the domain expert model resulted in a 0.74 ± 0.06.

Conclusions: Convolutional neural networks (CNNs) with transfer learning can predict IMRT QA passing rates by automatically designing features from the fluence maps without human expert supervision. Predictions from CNNs are comparable to a system carefully designed by physicist experts.
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http://dx.doi.org/10.1002/mp.12890DOI Listing
June 2018

Correcting TG 119 confidence limits.

Med Phys 2018 Mar 19;45(3):1001-1008. Epub 2018 Feb 19.

Department of Radiation Oncology, University of California, San Francisco, CA, 94115, USA.

Purpose: Task Group 119 (TG-119) has been adopted for evaluating the adequacy of intensity-modulated radiation therapy (IMRT) commissioning and for establishing patient-specific IMRT quality assurance (QA) passing criteria in clinical practice. TG-119 establishes 95% confidence limits (CLs), which help clinics identify systematic IMRT QA errors and identify outliers. In TG-119, the 95% CLs are established by fitting the Gamma Γ analysis passing rate results to an assumed distribution, then calculating the limit in which 95% of the data fall. CLs for a given dataset will depend greatly on the type of distribution used, and those determined by following the TG-119 guidelines are only valid if the underlying data follows a Gaussian distribution. Gaussian distributions assume symmetry about the mean, which would imply the possibility of negative Γ analysis failing rates. This study demonstrates that the gamma distribution is a more reasonable assumption for establishing CLs than the Gaussian distribution used in TG-119. Thus, the gamma distribution is suggested as a replacement to the conventional Gaussian statistical model used in TG-119.

Materials And Methods: The moments estimator (ME) for the gamma family is used to obtain the CLs of the failing rates for all Γ analysis criteria. To demonstrate the congruence of the gamma distribution, the root mean squared error and the CL values for the MEs of the gamma and the Gaussian families were compared.

Results: In this study, the empirical 95% CLs generated using 302 plans represent the ground truth, which resulted in a 91.83% passing rate using 3%/3 mm error local criteria. The gamma distribution underestimates the 95% CL by 0.09%, while the Gaussian distribution overestimates the 95% CL by 4.12%.

Conclusions: Although IMRT QA equipment may vary between clinics, the mathematical formalism presented in this study applies to any combination of planning and delivery systems. This study has demonstrated that a gamma distribution should be favored over a Gaussian distribution when establishing CLs for IMRT QA.
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http://dx.doi.org/10.1002/mp.12759DOI Listing
March 2018

Qigong and Tai-Chi for Mood Regulation.

Focus (Am Psychiatr Publ) 2018 Jan 24;16(1):40-47. Epub 2018 Jan 24.

Dr. Yeung and Ms. Cheung are with the Depression Clinical and Research Program, Massachusetts General Hospital, Boston. Dr. Yeung is also with the South Cove Community Health Center, Boston. Dr. Chan is with the Department of Social Work and Social Administration and the Centre on Behavioral Health, University of Hong Kong, Pokfulam, Hong Kong. Dr. Zou is with the Department of Physical Education and Health Education, Springfield College, Springfield, Massachusetts, and the Department of Sports Science, Jishou University, Jishou, China.

Qigong and Tai-Chi are traditional self-healing, self-cultivation exercises originating in ancient China. These exercises are characterized by coordinated body posture and movements, deep rhythmic breathing, meditation, and mental focus based on traditional Chinese medicine theories. Although the exact mechanisms of Qigong's and Tai-Chi's effects on physical and mental well-being are unknown, these practices may be viewed as meditative movements and share many of the healing elements observed in mindfulness meditation. Clinical studies including randomized controlled trials and meta-analyses have shown that both Qigong and Tai-Chi have beneficial effects on psychological well-being and reduce symptoms of anxiety and depression. Qigong and Tai-Chi frequently involve anchoring attention to interoceptive sensations related to breath or other parts of the body, which has been shown to enhance nonreactivity to aversive thoughts and impulses. Preliminary studies suggest that the slow movements in Qigong and Tai-Chi with slowing of breath frequency could alter the autonomic system and restore homeostasis, attenuating stress related to hypothalamus-pituitary-adrenal axis reactivity and modulating the balance of the autonomic nervous system toward parasympathetic dominance. Qigong's and Tai-Chi's effects on emotion regulation could occur through changes in multiple prefrontal regions, the limbic system, and the striatum or in the expression of genes linked to inflammatory responses and stress-related pathways.
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http://dx.doi.org/10.1176/appi.focus.20170042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6519567PMC
January 2018

Improved rectal dosimetry with the use of SpaceOAR during high-dose-rate brachytherapy.

Brachytherapy 2018 Mar - Apr;17(2):259-264. Epub 2017 Dec 2.

Department of Radiation Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA. Electronic address:

Purpose: Hydrogel spacers have been suggested to limit rectal radiation dose with improvements in clinical outcomes in patients undergoing external beam radiation treatment for prostate cancer. No studies to date have assessed the utility and dosimetric effect of SpaceOAR (Augmenix, Inc, Waltham, MA), the only Food and Drug Administration-approved hydrogel rectal spacer, for high-dose-rate (HDR) brachytherapy.

Methods: Eighteen consecutive patients scheduled for HDR brachytherapy in the treatment of prostate cancer underwent transperineal ultrasound-guided placement of 10 cc of SpaceOAR hydrogel following catheter implantation. Treatment plans were generated using an inverse planning simulated annealing algorithm. Rectal dosimetry for these 18 patients was compared with the 36 preceding patients treated with HDR brachytherapy without SpaceOAR.

Results: Fifty-four plans were analyzed. There was no difference in age, pretreatment prostate-specific antigen, Gleason score, clinical stage, prostate volume, or contoured rectal volume between those who received SpaceOAR and those who did not. Patients who received SpaceOAR hydrogel had significantly lower dose to the rectum as measured by percent of contoured organ at risk (median, V < 0.005% vs. 0.010%, p = 0.003; V < 0.005% vs. 0.14%, p < 0.0005; V 0.09% vs. 0.88%, p < 0.0005; V = 1.16% vs. 3.08%, p < 0.0005); similar results were seen for rectal volume in cubic centimeters. One patient who received SpaceOAR developed a perineal abscess 1 month after treatment.

Conclusions: Transperineal insertion of SpaceOAR hydrogel at the time of HDR brachytherapy is feasible and decreases rectal radiation dose. Further investigation is needed to assess the clinical impact of this dosimetric improvement and potential toxicity reduction.
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http://dx.doi.org/10.1016/j.brachy.2017.10.014DOI Listing
January 2019

Development and validation of a rapid and robust method to determine visceral adipose tissue volume using computed tomography images.

PLoS One 2017 31;12(8):e0183515. Epub 2017 Aug 31.

Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America.

Background: Visceral adiposity is a risk factor for many chronic diseases. Existing methods to quantify visceral adipose tissue volume using computed tomographic (CT) images often use a single slice, are manual, and are time consuming, making them impractical for large population studies. We developed and validated a method to accurately, rapidly, and robustly measure visceral adipose tissue volume using CT images.

Methods: In-house software, Medical Executable for the Efficient and Robust Quantification of Adipose Tissue (MEERQAT), was developed to calculate visceral adipose tissue volume using a series of CT images within a manually identified region of interest. To distinguish visceral and subcutaneous adipose tissue, ellipses are drawn through the rectus abdominis and transverse abdominis using manual and automatic processes. Visceral and subcutaneous adipose tissue volumes are calculated by counting the numbers of voxels corresponding to adipose tissue in the region of interest. MEERQAT's ellipse interpolation method was validated by comparing visceral adipose volume from 10 patients' CT scans with corresponding results from manually delineated scans. Accuracy of visceral adipose quantification was tested using a phantom consisting of animal fat and tissues. Robustness of the method was tested by determining intra-observer and inter-observer coefficients of variation (CV).

Results: The mean difference in visceral adipose tissue volume between manual and elliptical delineation methods was -0.54 ± 4.81%. In the phantom, our measurement differed from the known adipose volume by ≤ 7.5% for all scanning parameters. Mean inter-observer CV for visceral adipose tissue volume was 0.085, and mean intra-observer CV for visceral adipose tissue volume was 0.059.

Conclusions: We have developed and validated a robust method of accurately and quickly determining visceral adipose tissue volume in any defined region of interest using CT imaging.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0183515PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5578607PMC
October 2017

Characterization of the effect of a new commercial transmission detector on radiation therapy beams.

Pract Radiat Oncol 2017 Nov - Dec;7(6):e559-e567. Epub 2017 Apr 9.

Department of Radiation Oncology, University of California San Francisco, San Francisco, California. Electronic address:

Purpose: To evaluate the influence of a new commercial transmission detector on radiation therapy beams.

Methods And Materials: A transmission detector designed for online treatment monitoring was characterized on a TrueBeam STx linear accelerator with 6-MV, 6-flattening filter free, 10-MV, and 10-flattening filter free beams. Measurements of percentage depth doses, in-plane and cross-plane off-axis profiles at different depths, transmission factors, and skin dose were acquired with 3 × 3, 5 × 5, 10 × 10, 20 × 20, and 40 × 40 cm field sizes at 100 cm and 80 cm source-to-surface distance (SSD). A CC04 chamber was used for all profile and transmission factor measurements. Skin dose was assessed at 100, 90, and 80 cm SSD using a variety of detectors (Roos and Markus parallel-plate chambers and optically stimulated luminescent dosimeters [OSLDs]). Skin dose was also assessed for various patient sample plans with OSLDs.

Results: The percentage depth doses showed small differences between the unperturbed and perturbed beams for 100 cm SSD (≤4 mm depth of maximum dose difference, <1.2% average profile difference) for all field sizes. At 80 cm SSD, the differences were larger (≤8 mm depth of maximum dose difference, <3% average profile difference). The differences were larger for the flattened beams and larger field sizes. The off-axis profiles showed similar trends. Field penumbras looked similar with and without the transmission detector. Comparisons in the profile central 80% showed a maximum average (maximum) profile difference between all field sizes of 1.0% (2.6%) and 1.4% (6.3%) for 100 and 80 cm SSD, respectively. The average measured skin dose increase at 100 cm (80 cm) SSD for a 10 × 10 cm field size was <4% (<35%) for all energies. For a 40 × 40 cm field size, this increased to <31% (≤63%). For the sample patient plans, the average skin dose difference was 0.53% (range, -6.6% to 10.4%).

Conclusions: The transmission detector has minimal effect on clinically relevant radiation therapy beams for intensity modulated radiation therapy and volumetric arc therapy (field sizes 10 × 10 cm and less). For larger field sizes, some perturbations are observable that would need to be assessed for clinical impact.
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http://dx.doi.org/10.1016/j.prro.2017.04.001DOI Listing
July 2018

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife.

Phys Med Biol 2017 Jun 26;62(14):5777-5789. Epub 2017 Jun 26.

Department of Radiation Oncology, University of California, San Francisco, CA, United States of America.

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.
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http://dx.doi.org/10.1088/1361-6560/aa6f92DOI Listing
June 2017

Positive beliefs about mental illness: Associations with sex, age, diagnosis, and clinical outcomes.

J Affect Disord 2016 Nov 14;204:197-204. Epub 2016 Jun 14.

Department of Psychiatry, McLean Hospital, Belmont, MA 02478, United States; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, United States.

Background: Beliefs about mental illness affect how individuals cope with their symptoms. Positive beliefs about mental illness (PBMI) refer to perceptions of positive attributes individuals may identify in their illness, such as beneficial consequences, enhanced creativity or cognition, or growth through adversity.

Methods: The present study developed and tested a brief measure of PBMI in 332 adults presenting for partial hospitalization with a variety of acute psychiatric conditions.

Results: Results indicated that older individuals and women had lower levels of PBMI than others, while individuals with bipolar disorder had higher levels of PBMI than others. PBMI significantly increased over the course of brief standard treatment. Baseline levels of PBMI, as well as changes in PBMI over the course of treatment, were associated with clinical outcomes including, but not limited to, depression and well-being. A diagnosis of bipolar disorder moderated the relationship between PBMI and only one clinical outcome, emotional lability. Increases in PBMI during treatment were associated with reduced emotional lability only in participants without bipolar disorder.

Limitations: Our findings are limited by the naturalistic study design. In addition, the lack of ethnoracial diversity in our sample limits the generalization of results.

Conclusions: Our results suggest that PBMI are a distinct set of beliefs that meaningfully relate to demographic characteristics, diagnostic characteristics, and clinical outcomes. Future research should examine the mechanisms through which PBMI and outcomes are related, as well as determine whether interventions designed to address PBMI (and perhaps tailored for different diagnostic groups) have clinical utility.
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http://dx.doi.org/10.1016/j.jad.2016.06.038DOI Listing
November 2016

Statistical assessment of proton treatment plans under setup and range uncertainties.

Int J Radiat Oncol Biol Phys 2013 Aug 18;86(5):1007-13. Epub 2013 May 18.

Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Purpose: To evaluate a method for quantifying the effect of setup errors and range uncertainties on dose distribution and dose-volume histogram using statistical parameters; and to assess existing planning practice in selected treatment sites under setup and range uncertainties.

Methods And Materials: Twenty passively scattered proton lung cancer plans, 10 prostate, and 1 brain cancer scanning-beam proton plan(s) were analyzed. To account for the dose under uncertainties, we performed a comprehensive simulation in which the dose was recalculated 600 times per given plan under the influence of random and systematic setup errors and proton range errors. On the basis of simulation results, we determined the probability of dose variations and calculated the expected values and standard deviations of dose-volume histograms. The uncertainties in dose were spatially visualized on the planning CT as a probability map of failure to target coverage or overdose of critical structures.

Results: The expected value of target coverage under the uncertainties was consistently lower than that of the nominal value determined from the clinical target volume coverage without setup error or range uncertainty, with a mean difference of -1.1% (-0.9% for breath-hold), -0.3%, and -2.2% for lung, prostate, and a brain cases, respectively. The organs with most sensitive dose under uncertainties were esophagus and spinal cord for lung, rectum for prostate, and brain stem for brain cancer.

Conclusions: A clinically feasible robustness plan analysis tool based on direct dose calculation and statistical simulation has been developed. Both the expectation value and standard deviation are useful to evaluate the impact of uncertainties. The existing proton beam planning method used in this institution seems to be adequate in terms of target coverage. However, structures that are small in volume or located near the target area showed greater sensitivity to uncertainties.
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http://dx.doi.org/10.1016/j.ijrobp.2013.04.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755369PMC
August 2013

A novel dose-based positioning method for CT image-guided proton therapy.

Med Phys 2013 May;40(5):051714

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 94, Houston, Texas 77030, USA.

Purpose: Proton dose distributions can potentially be altered by anatomical changes in the beam path despite perfect target alignment using traditional image guidance methods. In this simulation study, the authors explored the use of dosimetric factors instead of only anatomy to set up patients for proton therapy using in-room volumetric computed tomographic (CT) images.

Methods: To simulate patient anatomy in a free-breathing treatment condition, weekly time-averaged four-dimensional CT data near the end of treatment for 15 lung cancer patients were used in this study for a dose-based isocenter shift method to correct dosimetric deviations without replanning. The isocenter shift was obtained using the traditional anatomy-based image guidance method as the starting position. Subsequent isocenter shifts were established based on dosimetric criteria using a fast dose approximation method. For each isocenter shift, doses were calculated every 2 mm up to ± 8 mm in each direction. The optimal dose alignment was obtained by imposing a target coverage constraint that at least 99% of the target would receive at least 95% of the prescribed dose and by minimizing the mean dose to the ipsilateral lung.

Results: The authors found that 7 of 15 plans did not meet the target coverage constraint when using only the anatomy-based alignment. After the authors applied dose-based alignment, all met the target coverage constraint. For all but one case in which the target dose was met using both anatomy-based and dose-based alignment, the latter method was able to improve normal tissue sparing.

Conclusions: The authors demonstrated that a dose-based adjustment to the isocenter can improve target coverage and/or reduce dose to nearby normal tissue.
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http://dx.doi.org/10.1118/1.4801910DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3651206PMC
May 2013

Fast range-corrected proton dose approximation method using prior dose distribution.

Phys Med Biol 2012 Jun 16;57(11):3555-69. Epub 2012 May 16.

The University of Texas at Houston Graduate School of Biomedical Sciences, Houston, TX 77030, USA.

For robust plan optimization and evaluation purposes, one needs a computationally efficient way to calculate dose distributions and dose-volume histograms (DVHs) under various changes in the variables associated with beam delivery and images. In this study, we report an approximate method for rapid calculation of dose when setup errors and anatomical changes occur during proton therapy. This fast dose approximation method calculates new dose distributions under various circumstances based on the prior knowledge of dose distribution from a reference setting. In order to validate the method, we calculated and compared the dose distributions from our approximation method to the dose distributions calculated from a clinically commissioned treatment planning system which was used as the ground truth. The overall accuracy of the proposed method was tested against varying degrees of setup error and anatomical deformation for selected patient cases. The setup error was simulated by rigid shifts of the patient; while the anatomical deformation was introduced using weekly acquired repeat CT data sets. We evaluated the agreement between the dose approximation method and full dose recalculation using a 3D gamma index and the root-mean-square (RMS) and maximum deviation of the cumulative dose volume histograms (cDVHs). The average passing rate of 3D gamma analysis under 3% dose and 3 mm distance-to-agreement criteria were 96% and 89% for setup errors and severe anatomy changes, respectively. The average of RMS and maximum deviation of the cDVHs under the setup error was 0.5% and 1.5%, respectively for all structures considered. Similarly, the average of RMS and maximum deviations under the weekly anatomical change were 0.6% and 2.7%, respectively. Our results show that the fast dose approximation method was able to account for the density variation of the patient due to the setup and anatomical changes with acceptable accuracy while significantly improving the computation time.
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http://dx.doi.org/10.1088/0031-9155/57/11/3555DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3388743PMC
June 2012

Dose perturbations and image artifacts caused by carbon-coated ceramic and stainless steel fiducials used in proton therapy for prostate cancer.

Phys Med Biol 2010 Dec 12;55(23):7135-47. Epub 2010 Nov 12.

The University of Texas at Houston Graduate School of Biomedical Sciences, Houston, TX 77030, USA.

Image-guided radiation therapy using implanted fiducial markers is a common solution for prostate localization to improve targeting accuracy. However, fiducials that are typically used for conventional photon radiotherapy cause large dose perturbations in patients who receive proton radiotherapy. A proposed solution has been to use fiducials of lower atomic number (Z) materials to minimize this effect in tissue, but the effects of these fiducials on dose distributions have not been quantified. The objective of this study was to analyze the magnitude of the dose perturbations caused by select lower-Z fiducials (a carbon-coated zirconium dioxide fiducial and a plastic-coated stainless steel fiducial) and compare them to perturbations caused by conventional gold fiducials. Sets of phantoms were used to assess select components of the effects on dose. First, the fiducials were assessed for radiographic visibility using both conventional computed tomography (CT) and an on-board kilovoltage imaging device at our proton therapy center. CT streak artifacts from the fiducials were also measured in a separate phantom. Second, dose perturbations were measured downstream of the fiducials using radiochromic film. The magnitude of dose perturbation was characterized as a function of marker material, implantation depth and orientation with respect to the beam axis. The radiographic visibility of the markers was deemed to be acceptable for clinical use. The dose measurements showed that the perpendicularly oriented zirconium dioxide and stainless steel fiducials located near the center of modulation of the proton beam perturbed the dose by less than 10%, but that the same fiducials in a parallel orientation near the end of the range of the beam could perturb the dose by as much as 38%. This suggests that carbon-coated and stainless steel fiducials could be used in proton therapy if they are located far from the end of the range of the beam and if they are oriented perpendicular to the beam axis.
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http://dx.doi.org/10.1088/0031-9155/55/23/S13DOI Listing
December 2010

Investigation of geometric distortions on magnetic resonance and cone beam computed tomography images used for planning and verification of high-dose rate brachytherapy cervical cancer treatment.

Brachytherapy 2010 Jul-Sep;9(3):266-73. Epub 2010 Feb 9.

Department of Radiation Oncology, University of California San Francisco, San Francisco, CA 94143, USA.

Purpose: To measure the amount of geometric distortions present in the three-dimensional imaging modalities--cone beam computed tomography (CBCT) and magnetic resonance imaging (MRI)--used at University of California, San Francisco, CA, for gynecologic high dose rate brachytherapy.

Methods And Materials: An MRI- and CT-compatible water phantom with two different sets of support structures was designed and built for this study. The support structures were used to precisely position catheters that were filled with either an MRI contrast agent or a string of radio-opaque markers. The first support structure without anatomy was built to test system-based distortions. A second structure included two types of gynecologic applicators as well as several anatomical structures, including bones and rectum to test object-induced distortions. Images were acquired with CT (for reference), kilovoltage CBCT, and MRI (1.5 T with T1- and T2-weighted images). The difference in catheter positions between the images and the CT images was analyzed.

Results: For CBCT, the mean of the absolute deviations was below 1mm in all directions. The inherent uncertainty in the measurement of distortion was less than 0.5mm. MRI presented mean absolute system-based distortions between 0.6 and 1.1mm in the central region of the image and between 0.7 and 2.3mm in the outer region. Images with the applicator and anatomy in place created mean absolute distortions of 0.4, 0.8, and 0.8mm or less for CBCT, MR-T1, and MR-T2 images, respectively.

Conclusions: The distortions measured in the presence of applicators are small enough to validate the use of CBCT and 1.5 T MRI for GYN brachytherapy treatment planning and verification.
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http://dx.doi.org/10.1016/j.brachy.2009.09.004DOI Listing
December 2010

Dose recalculation and the Dose-Guided Radiation Therapy (DGRT) process using megavoltage cone-beam CT.

Int J Radiat Oncol Biol Phys 2009 Jun 3;74(2):583-92. Epub 2009 Apr 3.

Department of Radiation Oncology, University of California San Francisco, Comprehensive Cancer Center, 94115, USA.

Purpose: At the University of California San Francisco, daily or weekly three-dimensional images of patients in treatment position are acquired for image-guided radiation therapy. These images can be used for calculating the actual dose delivered to the patient during treatment. In this article, we present the process of performing dose recalculation on megavoltage cone-beam computed tomography images and discuss possible strategies for dose-guided radiation therapy (DGRT).

Materials And Methods: A dedicated workstation has been developed to incorporate the necessary elements of DGRT. Patient image correction (cupping, missing data artifacts), calibration, completion, recontouring, and dose recalculation are all implemented in the workstation. Tools for dose comparison are also included. Examples of image correction and dose analysis using 6 head-and-neck and 2 prostate patient datasets are presented to show possible tracking of interfraction dosimetric endpoint variation over the course of treatment.

Results: Analysis of the head-and-neck datasets shows that interfraction treatment doses vary compared with the planning dose for the organs at risk, with the mean parotid dose and spinal cord D(1) increasing by as much as 52% and 10%, respectively. Variation of the coverage to the target volumes was small, with an average D(5) dose difference of 1%. The prostate patient datasets revealed accurate dose coverage to the targeted prostate and varying interfraction dose distributions to the organs at risk.

Conclusions: An effective workflow for the clinical implementation of DGRT has been established. With these techniques in place, future clinical developments in adaptive radiation therapy through daily or weekly dosimetric measurements of treatment day images are possible.
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http://dx.doi.org/10.1016/j.ijrobp.2008.12.034DOI Listing
June 2009

Correction of megavoltage cone-beam CT images of the pelvic region based on phantom measurements for dose calculation purposes.

J Appl Clin Med Phys 2009 Jan 27;10(1):33-42. Epub 2009 Jan 27.

Department of Radiation Oncology, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, U.S.A.

Megavoltage cone-beam CT (MVCBCT) is an imaging technology that provides a 3D representation of the patient in treatment position. Because it is a form of x-ray tomography, MVCBCT images give information about the attenuation coefficients of the imaged tissues, and thus could be used for dose calculation. However, the cupping and missing data artifacts seen on MVCBCT images can cause inaccuracies in dose calculations. To eliminate these inaccuracies, a correction method specific to pelvis imaging and based on phantom measurements has been devised. Pelvis-shaped water phantoms of three different sizes were designed and imaged with MVCBCT. Three sets of correction factors were created from the artifacts observed in these MVCBCT images by dividing the measured CT number by the predefined CT number for water. Linear interpolation is performed between the sets of correction factors to take into account the varying size of different patients. To compensate for the missing anatomy due to the limited field of view of the MVCBCT system, the MVCBCT image is complemented with the kilovoltage CT (kVCT) image acquired for treatment planning.When the correction method is applied to an anthropomorphic pelvis phantom, the standard deviation between dose calculations performed with kVCT and MVCBCT images is 0.6%, with 98% of the dose points agreeing within +/- 3%.With uncorrected MVCBCT images this percentage falls to 75%. An example of dose calculation performed with a corrected clinicalMVCBCT image of a prostate cancer patient shows that changes in anatomy of normal tissues result in variation of the dose distribution received by these tissues.This correction method enablesMVCBCT images to be used for the verification of the daily dose distribution for patients treated in the pelvis region.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720499PMC
http://dx.doi.org/10.1120/jacmp.v10i1.2852DOI Listing
January 2009