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Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies.

ABSTRACT: We present the complete construction methodology for an anatomically accurate mouse phantom made using materials which mimic the characteristics of tissue, lung, and bone for radiation dosimetry studies. Phantoms were constructed using 2?mm thick slices of tissue equivalent material which was precision machined to clear regions for insertion of lung and bone equivalent material where appropriate. Images obtained using a 3D computed tomography (CT) scan clearly indicate regions of tissue, lung, and bone that match their position within the original mouse CT scan. Additionally, radiographic films are used with the phantom to demonstrate dose mapping capabilities. The construction methodology presented here can be quickly and easily adapted to create a phantom of any specific small animal given a segmented CT scan of the animal. These physical phantoms are a useful tool to examine individual organ dose and dosimetry within mouse systems that are complicated by density inhomogeneity due to bone and lung regions.

SUBMITTER: Welch D

PROVIDER: S-EPMC4412154 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies.

Welch D D Harken A D AD Randers-Pehrson G G Brenner D J DJ

Physics in medicine and biology 20150410 9

We present the complete construction methodology for an anatomically accurate mouse phantom made using materials which mimic the characteristics of tissue, lung, and bone for radiation dosimetry studies. Phantoms were constructed using 2 mm thick slices of tissue equivalent material which was precision machined to clear regions for insertion of lung and bone equivalent material where appropriate. Images obtained using a 3D computed tomography (CT) scan clearly indicate regions of tissue, lung, a ...[more]

PMID: 25860401

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Project description:IntroductionAdditive manufacturing or 3-dimensional printing has become a widespread technology with many applications in medicine. We have conducted a systematic review of its application in radiation oncology with a particular emphasis on the creation of phantoms for image quality assessment and radiation dosimetry. Traditionally used phantoms for quality assurance in radiotherapy are often constraint by simplified geometry and homogenous nature to perform imaging analysis or pretreatment dosimetric verification. Such phantoms are limited due to their ability in only representing the average human body, not only in proportion and radiation properties but also do not accommodate pathological features. These limiting factors restrict the patient-specific quality assurance process to verify image-guided positioning accuracy and/or dose accuracy in "water-like" condition.Methods and resultsEnglish speaking manuscripts published since 2008 were searched in 5 databases (Google Scholar, Scopus, PubMed, IEEE Xplore, and Web of Science). A significant increase in publications over the 10 years was observed with imaging and dosimetry phantoms about the same total number (52 vs 50). Key features of additive manufacturing are the customization with creation of realistic pathology as well as the ability to vary density and as such contrast. Commonly used printing materials, such as polylactic acid, acrylonitrile butadiene styrene, high-impact polystyrene and many more, are utilized to achieve a wide range of achievable X-ray attenuation values from -1000 HU to 500 HU and higher. Not surprisingly, multimaterial printing using the polymer jetting technology is emerging as an important printing process with its ability to create heterogeneous phantoms for dosimetry in radiotherapy.ConclusionGiven the flexibility and increasing availability and low cost of additive manufacturing, it can be expected that its applications for radiation medicine will continue to increase.

Project description:Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR™ and then imported to the 3D modeling software package Rhinoceros™ for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations in skeletal size, individual organ masses and total fetal masses. The resulting series of fetal hybrid computational phantoms is applicable to organ-level and bone-level internal and external radiation dosimetry for human fetuses of various ages and weight percentiles.

Project description:ObjectiveOrgan radiation dose from a CT scan, calculated by CT dosimetry software, can be combined with cancer risk data to estimate cancer incidence resulting from CT exposure. We aim to determine to what extent the use of improved anatomical representation of the adult human body "phantom" in CT dosimetry software impacts estimates of radiation dose and cancer incidence, to inform comparison of past and future research.MethodsWe collected 20 adult cases for each of three CT protocols (abdomen/pelvis, chest and head) from each of five public hospitals (random sample) (January-April inclusive 2010) and three private clinics (self-report). Organ equivalent and effective dose were calculated using both ImPACT (mathematical phantom) and NCICT (voxelised phantom) software. Bland-Altman plots demonstrate agreement and Passing-Bablok regression reports systematic, proportional or random differences between results. We modelled the estimated lifetime attributable risk of cancer from a single exposure for each protocol, using age-sex specific risk-coefficients from the Biologic Effects of Ionizing Radiation VII report.ResultsFor the majority of organs used in epidemiological studies of cancer incidence, the NCICT software (voxelised) provided higher dose estimates. Across the lifespan NCICT resulted in cancer estimates 2.9%-6.6% and 14.8%-16.3% higher in males and females (abdomen/pelvis) and 7.6%-19.7% and 12.9%-26.5% higher in males and females respectively (chest protocol). For the head protocol overall cancer estimates were lower for NCICT, but with greatest disparity, >30% at times.ConclusionWhen the results of previous studies estimating CT dose and cancer incidence are compared to more recent, or future, studies the dosimetry software must be considered. Any change in radiation dose or cancer risk may be attributable to the software and phantom used, rather than-or in addition to-changes in scanning practice. Studies using dosimetry software to estimate radiation dose should describe software comprehensively to facilitate comparison with past and future research.

Project description:Calculation of radiation dosimetry in targeted nuclear medicine therapies is traditionally resource-intensive, requiring multiple posttherapy SPECT acquisitions. An alternative approach is to take advantage of existing pharmacokinetic data from these smaller cohorts to enable dose computation from a single posttreatment scan in a manner that may be applied to a much broader patient population. Methods: In this work, a technical description of simplified dose estimation is presented and applied to the assessment of 177Lu-prostate-specific membrane antigen (PSMA)-617 therapy for metastatic prostate cancer. By normalizing existing time-activity curves to a single measurement time, it is possible to calculate a mean and range of time-integrated activity values that relate to absorbed radiation dose. To assist with accurate pharmacokinetic modeling of the training cohort, a method for contour-guided image registration was developed. Results: Tissue-specific dose conversion factors for common posttreatment imaging times are reported along with a characterization of added uncertainty in comparison to a traditional serial imaging protocol. Single-time-point dose factors for tumor were determined to be 11.0, 12.1, 13.6, and 15.2 Gy per MBq/mL at image times of 24, 48, 72, and 96 h, respectively. For normal tissues, parotid gland factors were 6.7, 9.4, 13.3, and 19.3 Gy per MBq/mL at those times, and kidneys were 7.1, 10.3, 15.0, and 22.0 Gy per MBq/mL. Tumor dose estimates were most accurate using delayed scanning at times beyond 72 h. Dose to healthy tissues is best characterized by scanning patients in the first 2 d of treatment because of the larger degree of tracer clearance in this early phase. Conclusion: This work demonstrates a means for efficient dose estimation in 177Lu-PSMA-617 therapy. By providing methods to simplify and potentially automate radiation dosimetry, we hope to accelerate the understanding of radiobiology and development of dose-response models in this unique therapeutic context.

Project description:PURPOSE:To apply a previously designed framework for predicting radiation pneumonitis by using pretreatment lung function heterogeneity metrics, anatomic dosimetry, and functional lung dosimetry derived from 2 imaging modalities within the same cohort. METHODS AND MATERIALS:Treatment planning computed tomography (CT) scans were co-registered with pretreatment [99mTc] macro-aggregated albumin perfusion single-photon positron emission tomography (SPECT)/CT scans and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT scans of 28 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ?2 (Common Terminology Criteria for Adverse Events, v. 4). Anatomic dosimetric parameters (mean lung dose [MLD], volume receiving ?20 Gy [V20]) were collected from treatment planning scans. Baseline functional lung heterogeneity parameters and functional lung dose-volume parameters were calculated from pretreatment SPECT/CT and FDG PET/CT scans. Functional heterogeneity parameters calculated over the tumor-subtracted lung included skewness, kurtosis, and coefficient of variation from perfusion SPECT and FDG PET and the global lung parenchymal glycolysis and mean standardized uptake value from FDG PET. Functional dose-volume parameters calculated in regions of highly functional lung, defined on perfusion (p) or SUV (s) images, included mean lung dose (pMLD, sMLD) and V20 (pV20, sV20). Fraction of integral lung function receiving ?20 Gy (pF20, sF20) was also calculated. Equivalent doses in 2 Gy per fraction (EQD2) were calculated to account for differences in treatment regimens and dose fractionation (EQD2Lung). RESULTS:Two anatomic dosimetric parameters (MLD, V20) and 4 functional dosimetric parameters (pMLD, pV20, pF20, sF20) were significant predictors of grade ?2 pneumonitis (area under the curve >0.84; P < .05). Dose-independent functional lung heterogeneity metrics were not associated with pneumonitis incidence. At thresholds of 100% sensitivity and 65% to 91% specificity, corresponding to maximum prediction accuracy for pneumonitis, these parameters had the following cutoff values: MLD = 13.6 Gy EQD2Lung, V20 = 25%, pMLD = 13.2 Gy EQD2Lung, pV20 = 15%, pF20 = 17%, and sF20 = 25%. Significant parameters MLD, V20, pF20, and sF20 were not cross-correlated to significant parameters pMLD and pV20, indicating that they may offer independently predictive information (Spearman ? < 0.7). CONCLUSIONS:We reported differences in anatomic and functional lung dosimetry between patients with and without pneumonitis in this limited patient cohort. Adding selected independent functional lung parameters may risk stratify patients for pneumonitis. Validation studies are ongoing in a prospective functional lung avoidance trial at our institution.

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Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies.

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Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies.

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