Patient-specific organ and effective dose estimates in pediatric oncology computed tomography

Gao, Yiming; Quinn, Brian; Pandit‐Taskar, Neeta; Behr, Gerald; Mahmood, Usman; Long, Daniel J.; Xu, Xiaobin; Germain, Jean St.; Dauer, Lawrence T.

doi:10.1016/j.ejmp.2017.12.013

Cited by 32 publications

(21 citation statements)

References 35 publications

(71 reference statements)

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“…Table 5 provides a comparison with other local and international pediatric DRL studies, between the 75th percentile of the CTDI vol and DLP analysis. The findings of CTDI vol were similar to German, United States, Korea and European studies for CT Brain and CT thorax [8,[15][16][17][18]. However, DLP values for CT brain were significantly higher than others study except for reference level from Jordan [19].…”

Section: Resultssupporting

confidence: 83%

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Diagnostic Reference Level of Radiation Dose and Image Quality among Paediatric CT Examinations in A Tertiary Hospital in Malaysia

et al. 2020

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Pediatrics are more vulnerable to radiation and are prone to dose compared to adults, requiring more attention to computed tomography (CT) optimization. Hence, diagnostic reference levels (DRLs) have been implemented as part of optimization process in order to monitor CT dose and diagnostic quality. The noise index has recently been endorsed to be included as a part of CT optimization in the DRLs report. In this study, we have therefore set local DRLs for pediatric CT examination with a noise index as an indicator of image quality. One thousand one hundred and ninety-two (1192) paediatric patients undergoing CT brain, CT thorax and CT chest-abdomen-pelvis (CAP) examinations were analyzed retrospectively and categorized into four age groups; group 1 (0–1 year), group 2 (1–5 years), group 3 (5–10 years) and group 4 (10–15 years). For each group, data such as the volume-weighted CT dose index (CTDIvol), dose-length product (DLP) and the effective dose (E) were calculated and DRLs for each age group set at 50th percentile were determined. Both CT dose and image noise values between age groups have differed significantly with p-value < 0.05. The highest CTDIvol and DLP values in all age groups with the lowest noise index value reported in the 10–15 age group were found in CT brain examination. In conclusion, there was a significant variation in doses and noise intensity among children of different ages, and the need to change specific parameters to fit the clinical requirement.

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Section: Resultssupporting

confidence: 83%

“…The 75th percentile (third quartile) CTDI vol and DLP values in this study were compared with the DRL data from studies in other countries. The DLP results in CT brain were slightly higher than the studies in USA and Switzerland [15,17]. The higher DLP in CT brain could mainly be due to the over-ranging beam when scanning was performed.…”

Section: Discussioncontrasting

confidence: 57%

Diagnostic Reference Level of Radiation Dose and Image Quality among Paediatric CT Examinations in A Tertiary Hospital in Malaysia

et al. 2020

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“…Obtaining the complete tube current modulation profile was not possible owing to the lack of sufficient information (proprietary data undisclosed by the manufacturer). We, therefore, extracted the longitudinal tube current modulation from the DICOM header file of patient's CT images and did not consider angular tube current modulation . The absorbed doses to predefined target organs were calculated using a previously validated C++ computer code .…”

Section: Methodsmentioning

confidence: 99%

“…We, therefore, extracted the longitudinal tube current modulation from the DICOM header file of patient's CT images and did not consider angular tube current modulation. 16 The absorbed doses to predefined target organs were calculated using a previously validated C++ computer code. 26,27 The simulations of each helical CT scan were repeated six times with x-ray tube starting at angles differing by 60°since the actual tube starting angles in the actual examinations were unknown.…”

Section: C Dosimetry Calculationsmentioning

confidence: 99%

“…Similar to the above‐mentioned method, this technique also suffers from time‐consuming manual organ segmentation required for dosimetry calculations. Gao et al estimated organ doses for a large number of pediatric patients using patient‐specific information implemented into VirtualDose™ CT dose calculation software. The Radimetrics™ commercial dose tracking software (Bayer HealthCare, Berlin, Germany) calculates patient‐specific absorbed doses by matching CT images of each patient with Cristy & Eckerman stylized computational phantoms, taking into account the physical and anatomical characteristics of the patient.…”

Section: Introductionmentioning

confidence: 99%

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Construction of patient‐specific computational models for organ dose estimation in radiological imaging

2019

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Purpose Diagnostic imaging procedures require optimization depending on the medical task at hand, the apparatus being used, and patient physical and anatomical characteristics. The assessment of the radiation dose and associated risks plays a key role in safety and quality management for radiation protection purposes. In this work, we aim at developing a methodology for personalized organ‐level dose assessment in x‐ray computed tomography (CT) imaging. Methods Regional voxel models representing reference patient‐specific computational phantoms were generated through image segmentation of CT images for four patients. The best‐fitting anthropomorphic phantoms were selected from a previously developed comprehensive phantom library according to patient's anthropometric parameters, then registered to the anatomical masks (skeleton, lung, and body contour) of patients to produce a patient‐specific whole‐body phantom. Well‐established image registration metrics including Jaccard's coefficients for each organ, organ mass, body perimeter, organ‐surface distance, and effective diameter are compared between the reference patient model, registered model, and anchor phantoms. A previously validated Monte Carlo code is utilized to calculate the absorbed dose in target organs along with the effective dose delivered to patients. The calculated absorbed doses from the reference patient models are then compared with the produced personalized model, anchor phantom, and those reported by commercial dose monitoring systems. Results The evaluated organ‐surface distance and body effective diameter metrics show a mean absolute difference between patient regional voxel models, serving as reference, and patient‐specific models around 4.4% and 4.5%, respectively. Organ‐level radiation doses of patient‐specific models are in good agreement with those of the corresponding patient regional voxel models with a mean absolute difference of 9.1%. The mean absolute difference of organ doses for the best‐fitting model extracted from the phantom library and Radimetrics™ commercial dose tracking software are 15.5% and 41.1%, respectively. Conclusion The results suggest that the proposed methodology improves the accuracy of organ‐level dose estimation in CT, especially for extreme cases [high body mass index (BMI) and large skeleton]. Patient‐specific radiation dose calculation and risk assessment can be performed using the proposed methodology for both monitoring of cumulative radiation exposure of patients and epidemiological studies. Further validation using a larger database is warranted.

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Radiation exposure dose outside the irradiation field due to differences in pediatric head computed tomography scanning methods

Higuchi¹,

Fujimura

2021

Radiol Phys Technol

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Patient-specific organ and effective dose estimates in pediatric oncology computed tomography

Cited by 32 publications

References 35 publications

Diagnostic Reference Level of Radiation Dose and Image Quality among Paediatric CT Examinations in A Tertiary Hospital in Malaysia

Diagnostic Reference Level of Radiation Dose and Image Quality among Paediatric CT Examinations in A Tertiary Hospital in Malaysia

Construction of patient‐specific computational models for organ dose estimation in radiological imaging

Radiation exposure dose outside the irradiation field due to differences in pediatric head computed tomography scanning methods

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