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Featured researches published by Peiyun Lu.


European Radiology | 2012

A method for the automatic quantification of the completeness of pulmonary fissures: evaluation in a database of subjects with severe emphysema

Eva M. van Rikxoort; Jonathan G. Goldin; Maya Galperin-Aizenberg; Fereidoun Abtin; Hyun J. Kim; Peiyun Lu; Bram van Ginneken; Greg Shaw; Matthew S. Brown

AbstractObjectivesTo propose and evaluate a technique for automatic quantification of fissural completeness from chest computed tomography (CT) in a database of subjects with severe emphysema.MethodsNinety-six CT studies of patients with severe emphysema were included. The lungs, fissures and lobes were automatically segmented. The completeness of the fissures was calculated as the percentage of the lobar border defined by a fissure. The completeness score of the automatic method was compared with a visual consensus read by three radiologists using boxplots, rank sum tests and ROC analysis.ResultsThe consensus read found 49% (47/96), 15% (14/96) and 67% (64/96) of the right major, right minor and left major fissures to be complete. For all fissures visually assessed as being complete the automatic method resulted in significantly higher completeness scores (mean 92.78%) than for those assessed as being partial or absent (mean 77.16%; all p values <0.001). The areas under the curves for the automatic fissural completeness were 0.88, 0.91 and 0.83 for the right major, right minor and left major fissures respectively.ConclusionsAn automatic method is able to quantify fissural completeness in a cohort of subjects with severe emphysema consistent with a visual consensus read of three radiologists.Key Points• Lobar fissures are important for assessing the extent and distribution of lung disease • Modern CT allows automatic lobar segmentation and assessment of the fissures • This segmentation can also assess the completeness of the fissures. • Such assessment is important for decisions about novel therapies (eg for emphysema).


Medical Physics | 2013

The feasibility of a regional CTDIvol to estimate organ dose from tube current modulated CT exams

M Khatonabadi; Hyun J. Kim; Peiyun Lu; Kyle McMillan; Christopher H. Cagnon; J DeMarco; Michael F. McNitt-Gray

PURPOSE In AAPM Task Group 204, the size-specific dose estimate (SSDE) was developed by providing size adjustment factors which are applied to the Computed Tomography (CT) standardized dose metric, CTDI(vol). However, that work focused on fixed tube current scans and did not specifically address tube current modulation (TCM) scans, which are currently the majority of clinical scans performed. The purpose of this study was to extend the SSDE concept to account for TCM by investigating the feasibility of using anatomic and organ specific regions of scanner output to improve accuracy of dose estimates. METHODS Thirty-nine adult abdomen/pelvis and 32 chest scans from clinically indicated CT exams acquired on a multidetector CT using TCM were obtained with Institutional Review Board approval for generating voxelized models. Along with image data, raw projection data were obtained to extract TCM functions for use in Monte Carlo simulations. Patient size was calculated using the effective diameter described in TG 204. In addition, the scanner-reported CTDI(vo)l (CTDI(vol),global) was obtained for each patient, which is based on the average tube current across the entire scan. For the abdomen/pelvis scans, liver, spleen, and kidneys were manually segmented from the patient datasets; for the chest scans, lungs and for female models only, glandular breast tissue were segmented. For each patient organ doses were estimated using Monte Carlo Methods. To investigate the utility of regional measures of scanner output, regional and organ anatomic boundaries were identified from image data and used to calculate regional and organ-specific average tube current values. From these regional and organ-specific averages, CTDI(vol) values, referred to as regional and organ-specific CTDI(vol), were calculated for each patient. Using an approach similar to TG 204, all CTDI(vol) values were used to normalize simulated organ doses; and the ability of each normalized dose to correlate with patient size was investigated. RESULTS For all five organs, the correlations with patient size increased when organ doses were normalized by regional and organ-specific CTDI(vol) values. For example, when estimating dose to the liver, CTDI(vol),global yielded a R(2) value of 0.26, which improved to 0.77 and 0.86, when using the regional and organ-specific CTDI(vol) for abdomen and liver, respectively. For breast dose, the global CTDI(vol) yielded a R(2) value of 0.08, which improved to 0.58 and 0.83, when using the regional and organ-specific CTDI(vol) for chest and breasts, respectively. The R(2) values also increased once the thoracic models were separated for the analysis into females and males, indicating differences between genders in this region not explained by a simple measure of effective diameter. CONCLUSIONS This work demonstrated the utility of regional and organ-specific CTDI(vol) as normalization factors when using TCM. It was demonstrated that CTDI(vol),global is not an effective normalization factor in TCM exams where attenuation (and therefore tube current) varies considerably throughout the scan, such as abdomen/pelvis and even thorax. These exams can be more accurately assessed for dose using regional CTDI(vol) descriptors that account for local variations in scanner output present when TCM is employed.


Medical Physics | 2012

A comparison of methods to estimate organ doses in CT when utilizing approximations to the tube current modulation function

M Khatonabadi; Di Zhang; Kelsey B. Mathieu; Hyun J. Kim; Peiyun Lu; Dianna D. Cody; J DeMarco; Christopher H. Cagnon; Michael F. McNitt-Gray

PURPOSE Most methods to estimate patient dose from computed tomography (CT) exams have been developed based on fixed tube current scans. However, in current clinical practice, many CT exams are performed using tube current modulation (TCM). Detailed information about the TCM function is difficult to obtain and therefore not easily integrated into patient dose estimate methods. The purpose of this study was to investigate the accuracy of organ dose estimates obtained using methods that approximate the TCM function using more readily available data compared to estimates obtained using the detailed description of the TCM function. METHODS Twenty adult female models generated from actual patient thoracic CT exams and 20 pediatric female models generated from whole body PET∕CT exams were obtained with IRB (Institutional Review Board) approval. Detailed TCM function for each patient was obtained from projection data. Monte Carlo based models of each scanner and patient model were developed that incorporated the detailed TCM function for each patient model. Lungs and glandular breast tissue were identified in each patient model so that organ doses could be estimated from simulations. Three sets of simulations were performed: one using the original detailed TCM function (x, y, and z modulations), one using an approximation to the TCM function (only the z-axis or longitudinal modulation extracted from the image data), and the third was a fixed tube current simulation using a single tube current value which was equal to the average tube current over the entire exam. Differences from the reference (detailed TCM) method were calculated based on organ dose estimates. Pearsons correlation coefficients were calculated between methods after testing for normality. Equivalence test was performed to compare the equivalence limit between each method (longitudinal approximated TCM and fixed tube current method) and the detailed TCM method. Minimum equivalence limit was reported for each organ. RESULTS Doses estimated using the longitudinal approximated TCM resulted in small differences from doses obtained using the detailed TCM function. The calculated root-mean-square errors (RMSE) for adult female chest simulations were 9% and 3% for breasts and lungs, respectively; for pediatric female chest and whole body simulations RMSE were 9% and 7% for breasts and 3% and 1% for lungs, respectively. Pearsons correlation coefficients were consistently high for the longitudinal approximated TCM method, ranging from 0.947 to 0.999, compared to the fixed tube current value ranging from 0.8099 to 0.9916. In addition, an equivalence test illustrated that across all models the longitudinal approximated TCM is equivalent to the detailed TCM function within up to 3% for lungs and breasts. CONCLUSIONS While the best estimate of organ dose requires the detailed description of the TCM function for each patient, extracting these values can be difficult. The presented results show that an approximation using available data extracted from the DICOM header provides organ dose estimates with RMSE of less than 10%. On the other hand, the use of the overall average tube current as a single tube current value was shown to result in poor and inconsistent estimates of organ doses.


Medical Physics | 2015

Attenuation‐based size metric for estimating organ dose to patients undergoing tube current modulated CT exams

Maryam Bostani; Kyle McMillan; Peiyun Lu; Hyun J. Kim; Christopher H. Cagnon; J DeMarco; Michael F. McNitt-Gray

PURPOSE Task Group 204 introduced effective diameter (ED) as the patient size metric used to correlate size-specific-dose-estimates. However, this size metric fails to account for patient attenuation properties and has been suggested to be replaced by an attenuation-based size metric, water equivalent diameter (DW). The purpose of this study is to investigate different size metrics, effective diameter, and water equivalent diameter, in combination with regional descriptions of scanner output to establish the most appropriate size metric to be used as a predictor for organ dose in tube current modulated CT exams. METHODS 101 thoracic and 82 abdomen/pelvis scans from clinically indicated CT exams were collected retrospectively from a multidetector row CT (Sensation 64, Siemens Healthcare) with Institutional Review Board approval to generate voxelized patient models. Fully irradiated organs (lung and breasts in thoracic scans and liver, kidneys, and spleen in abdominal scans) were segmented and used as tally regions in Monte Carlo simulations for reporting organ dose. Along with image data, raw projection data were collected to obtain tube current information for simulating tube current modulation scans using Monte Carlo methods. Additionally, previously described patient size metrics [ED, DW, and approximated water equivalent diameter (DWa)] were calculated for each patient and reported in three different ways: a single value averaged over the entire scan, a single value averaged over the region of interest, and a single value from a location in the middle of the scan volume. Organ doses were normalized by an appropriate mAs weighted CTDIvol to reflect regional variation of tube current. Linear regression analysis was used to evaluate the correlations between normalized organ doses and each size metric. RESULTS For the abdominal organs, the correlations between normalized organ dose and size metric were overall slightly higher for all three differently (global, regional, and middle slice) reported DW and DWa than they were for ED, but the differences were not statistically significant. However, for lung dose, computed correlations using water equivalent diameter calculated in the middle of the image data (DW,middle) and averaged over the low attenuating region of lung (DW,regional) were statistically significantly higher than correlations of normalized lung dose with ED. CONCLUSIONS To conclude, effective diameter and water equivalent diameter are very similar in abdominal regions; however, their difference becomes noticeable in lungs. Water equivalent diameter, specifically reported as a regional average and middle of scan volume, was shown to be better predictors of lung dose. Therefore, an attenuation-based size metric (water equivalent diameter) is recommended because it is more robust across different anatomic regions. Additionally, it was observed that the regional size metric reported as a single value averaged over a region of interest and the size metric calculated from a single slice/image chosen from the middle of the scan volume are highly correlated for these specific patient models and scan types.


Medical Physics | 2017

Estimating Organ Doses from Tube Current Modulated CT Examinations using a Generalized Linear Model

Maryam Bostani; Kyle McMillan; Peiyun Lu; Grace Kim; Dianna D. Cody; Gary Arbique; S. Bruce Greenberg; J DeMarco; Christopher H. Cagnon; Michael F. McNitt-Gray

Purpose Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan‐specific variables as needed. Methods The collection of a total of 332 patient CT scans at four different institutions was approved by each institutions IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patients image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z‐axis‐only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDIvol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT. Results The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs. Conclusions The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population.


Proceedings of SPIE | 2012

Automated segmentation of tumors on bone scans using anatomy-specific thresholding

Gregory H. Chu; Pechin Lo; Hyun J. Kim; Peiyun Lu; Bharath Ramakrishna; David W. Gjertson; Cheryce Poon; Martin Auerbach; Jonathan G. Goldin; Matthew S. Brown

Quantification of overall tumor area on bone scans may be a potential biomarker for treatment response assessment and has, to date, not been investigated. Segmentation of bone metastases on bone scans is a fundamental step for this response marker. In this paper, we propose a fully automated computerized method for the segmentation of bone metastases on bone scans, taking into account characteristics of different anatomic regions. A scan is first segmented into anatomic regions via an atlas-based segmentation procedure, which involves non-rigidly registering a labeled atlas scan to the patient scan. Next, an intensity normalization method is applied to account for varying levels of radiotracer dosing levels and scan timing. Lastly, lesions are segmented via anatomic regionspecific intensity thresholding. Thresholds are chosen by receiver operating characteristic (ROC) curve analysis against manual contouring by board certified nuclear medicine physicians. A leave-one-out cross validation of our method on a set of 39 bone scans with metastases marked by 2 board-certified nuclear medicine physicians yielded a median sensitivity of 95.5%, and specificity of 93.9%. Our method was compared with a global intensity thresholding method. The results show a comparable sensitivity and significantly improved overall specificity, with a p-value of 0.0069.


Journal of therapeutic ultrasound | 2015

Efficacy of MR-guided focused ultrasound ablation for localized adenomyosis in comparison to leiomyoma

Heidi Coy; Nelly Tan; Daniel Margolis; Peiyun Lu; Grace Kim; Matthew S. Brown; David Lu; Jonathan G. Goldin; Steven S. Raman

Symptomatic localized adenomyosis is generally treated conservatively, or with more radical treatments such as hysterectomy. An effective non-invasive therapy is needed, especially for those who wish to preserve their fertility. MR-guided Focused Ultrasound ablation (MRgFUS) has been shown as an effective treatment for symptomatic uterine leiomyomas with a large non-perfused volume (NPV) immediately after treatment. Our specific aim was to compare the change in NPV in subjects with localized adenomyomas treated with MRgFUS, with the change in NPV in subjects treated with MRgFUS for symptomatic uterine leiomyomas to determine if similar results were achieved in the localized adenomyoma cohort.


Academic Radiology | 2015

Comparison of the Quantitative CT Imaging Biomarkers of Idiopathic Pulmonary Fibrosis at Baseline and Early Change with an Interval of 7 Months

Hyun J. Kim; Matthew S. Brown; Daniel Chong; David W. Gjertson; Peiyun Lu; Hak J. Kim; Heidi Coy; Jonathan G. Goldin


European Respiratory Journal | 2011

Association of texture-based quantitative fibrotic patterns and pulmonary function test in a new validation set

Hyun J. Kim; Matthew S. Brown; Fereidoun Abtin; Peiyun Lu; Daniel Chong; Jonathan G. Goldin


International Journal of Clinical Trials | 2018

High-throughput image labeling and quality control for clinical trials using machine learning

Robert J. Harris; Pangyu Teng; Mahesh B. Nagarajan; Liza Shrestha; Xiang Lu; Bharath Ramakrishna; Peiyun Lu; Theo Sanford; Heather Clem; Megan McRoberts; Jonathan G. Goldin; Matthew S. Brown

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Hyun J. Kim

University of California

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Grace Kim

University of California

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J DeMarco

Cedars-Sinai Medical Center

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Daniel Chong

University of California

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