The importance of tissue segmentation for dose calculations for kilovoltage radiation therapy

AMS-U-Net: automatic mass segmentation in digital breast tomosynthesis via U-Net

Purpose

The objective of this study was to develop a fully automatic mass segmentation method called AMS-U-Net for digital breast tomosynthesis (DBT), a popular breast cancer screening imaging modality. The aim was to address the challenges posed by the increasing number of slices in DBT, which leads to higher mass contouring workload and decreased treatment efficiency.

Approach

The study used 50 slices from different DBT volumes for evaluation. The AMS-U-Net approach consisted of four stages: image pre-processing, AMS-U-Net training, image segmentation, and post-processing. The model performance was evaluated by calculating the true positive ratio (TPR), false positive ratio (FPR), F-score, intersection over union (IoU), and 95% Hausdorff distance (pixels) as they are appropriate for datasets with class imbalance.

Results

The model achieved 0.911, 0.003, 0.911, 0.900, 5.82 for TPR, FPR, F-score, IoU, and 95% Hausdorff distance, respectively.

Conclusions

The AMS-U-Net model demonstrated impressive visual and quantitative results, achieving high accuracy in mass segmentation without the need for human interaction. This capability has the potential to significantly increase clinical efficiency and workflow in DBT for breast cancer screening.

Optimized Atlas-Based Auto-Segmentation of Bony Structures from Whole-Body Computed Tomography

PURPOSE

To develop and test a method for fully automated segmentation of bony structures from whole-body computed tomography (CT) and evaluate its performance compared with manual segmentation.

METHODS AND MATERIALS

We developed a workflow for automatic whole-body bone segmentation using atlas-based segmentation (ABS) method with a postprocessing module (ABSPP) in MIM MAESTRO software. Fifty-two CT scans comprised the training set to build the atlas library, and 29 CT scans comprised the test set. To validate the workflow, we compared Dice similarity coefficient (DSC), mean distance to agreement, and relative volume errors between ABSPP and ABS with no postprocessing (ABSNPP) with manual segmentation as the reference (gold standard).

RESULTS

The ABSPP method resulted in significantly improved segmentation accuracy (DSC range, 0.85-0.98) compared with the ABSNPP method (DSC range, 0.55-0.87; P < .001). Mean distance to agreement results also indicated high agreement between ABSPP and manual reference delineations (range, 0.11-1.56 mm), which was significantly improved compared with ABSNPP (range, 1.00-2.34 mm) for the majority of tested bony structures. Relative volume errors were also significantly lower for ABSPP compared with ABSNPP for most bony structures.

CONCLUSIONS

We developed a fully automated MIM workflow for bony structure segmentation from whole-body CT, which exhibited high accuracy compared with manual delineation. The integrated postprocessing module significantly improved workflow performance.

Roadmap for precision preclinical x-ray radiation studies

This Roadmap paper covers the field of precision preclinical x-ray radiation studies in animal models. It is mostly focused on models for cancer and normal tissue response to radiation, but also discusses other disease models. The recent technological evolution in imaging, irradiation, dosimetry and monitoring that have empowered these kinds of studies is discussed, and many developments in the near future are outlined. Finally, clinical translation and reverse translation are discussed.

Clinical treatment planning for kilovoltage radiotherapy using EGSnrc and Python

Kilovoltage radiotherapy dose calculations are generally performed with manual point dose calculations based on water dosimetry. Tissue heterogeneities, irregular surfaces, and introduction of lead cutouts for treatment are either not taken into account or crudely approximated in manual calculations. Full Monte Carlo (MC) simulations can account for these limitations but require a validated treatment unit model, accurately segmented patient tissues and a treatment planning interface (TPI) to facilitate the simulation setup and result analysis. EGSnrc was used in this work to create a model of Xstrahl kilovoltage unit extending the range of energies, applicators, and validation parameters previously published. The novel functionality of the Python-based framework developed in this work allowed beam modification using custom lead cutouts and shields, commonly present in kilovoltage treatments, as well as absolute dose normalization using the output of the unit. 3D user-friendly planning interface of the developed framework facilitated non-co-planar beam setups for CT phantom MC simulations in DOSXYZnrc. The MC models of 49 clinical beams showed good agreement with measured and reference data, to within 2% for percentage depth dose curves, 4% for beam profiles at various depths, 2% for backscatter factors, 0.5 mm of absorber material for half-value layers, and 3% for output factors. End-to-end testing of the framework using custom lead cutouts resulted in good agreement to within 3% of absolute dose distribution between simulations and EBT3 GafChromic film measurements. Gamma analysis demonstrated poor agreement at the field edges which was attributed to the limitations of simulating smooth cutout shapes. Dose simulated in a heterogeneous phantom agreed to within 7% with measured values converted using the ratio of mass energy absorption coefficients of appropriate tissues and air.

Significance of the spectral correction of photon counting detector response in material classification from spectral x-ray CT

Purpose: Photon counting imaging detectors (PCD) has paved the way for spectral x-ray computed tomography (spectral CT), which simultaneously measures a sample's linear attenuation coefficient (LAC) at multiple energies. However, cadmium telluride (CdTe)-based PCDs working under high flux suffer from detector effects, such as charge sharing and photon pileup. These effects result in the severe spectral distortions of the measured spectra and significant deviation of the extracted LACs from the reference attenuation curve. We analyze the influence of the spectral distortion correction on material classification performance. Approach: We employ a spectral correction algorithm to reduce the primary spectral distortions. We use a method for material classification that measures system-independent material properties, such as electron density, ρ e , and effective atomic number, Z eff . These parameters are extracted from the LACs using attenuation decomposition and are independent of the scanner specification. The classification performance with the raw and corrected data is tested on different numbers of energy bins and projections and different radiation dose levels. We use experimental data with a broad range of materials in the range of 6 ≤ Z eff ≤ 15 , acquired with a custom laboratory instrument for spectral CT. Results: We show that using the spectral correction leads to an accuracy increase of 1.6 and 3.8 times in estimating ρ e and Z eff , respectively, when the image reconstruction is performed from only 12 projections and the 15 energy bins approach is used. Conclusions: The correction algorithm accurately reconstructs the measured attenuation curve and thus gives better classification performance.

Dose calculations for pre-clinical radiobiology experiments conducted with single-field cabinet irradiators

PURPOSE

To provide percentage depth-dose (PDD) data along the central axis for dosimetry calculations in small-animal radiation biology experiments performed in cabinet irradiators. The PDDs are provided as a function of source-to-surface distance (SSD), field size and animal size.

METHODS

The X-ray tube designs for four biological cabinet irradiators, the RS2000, RT250, MultiRad350 and XRAD320, were simulated using the BEAMnrc Monte Carlo code to generate 160, 200, 250 and 320 kVp photon beams, respectively. The 320 kVp beam was simulated with two filtrations: a soft F1 aluminium filter and a hard F2 thoraeus filter made of aluminium, tin and copper. Beams were collimated into circular fields with diameters of 0.5 - 10 cm at SSDs of 10 - 60 cm. Monte Carlo dose calculations in 1 - 5-cm diameter homogeneous (soft tissue) small-animal phantoms as well as in heterogeneous phantoms with 3-mm diameter cylindrical lung and bone inserts (rib and cortical bone) were performed using DOSXYZnrc. The calculated depth doses in three test-cases were estimated by applying SSD, field size and animal size correction factors to a reference case (40 cm SSD, 1 cm field and 5 cm animal size) and these results were compared with the specifically simulated (i.e., expected) doses to assess the accuracy of this method. Dosimetry for two test-case scenarios of 160 and 250 kVp beams (representative of end-user beam qualities) was also performed, whereby the simulated PDDs at two different depths were compared with the results based on the interpolation from reference data.

RESULTS

The depth doses for three test-cases calculated at 200, 320 kVp F1 and 320 kVp F2, with half value layers (HVL) ranging from ∼0.6 mm to 3.6 mm Cu, agreed well with the expected doses, yielding dose differences of 1.2, 0.1 and 1.0%, respectively. The two end-user test-cases for 160 and 250 kVp beams with respective HVLs of ∼0.8 and 1.8 mm Cu yielded dose differences of 1.4 and 3.2% between the simulated and the interpolated PDDs. The dose increase at the bone-tissue proximal interface ranged from 1.2 to 2.5 times the dose in soft tissue for rib and 1.3 to 3.7 times for cortical bone. The dose drop-off at 1-cm depth beyond the bone ranged from 1.3 - 6.0% for rib and 3.2 - 11.7% for cortical bone. No drastic dose perturbations occurred in the presence of lung, with lung-tissue interface dose of >99% of soft tissue dose and <3% dose increase at 1-cm depth beyond lung.

CONCLUSIONS

The developed dose estimation method can be used to translate the measured dose at a point to dose at any depth in small-animal phantoms, making it feasible for pre-clinical calculation of dose distributions in animals irradiated with cabinet-style irradiators. The dosimetric impact of bone must be accurately quantified as dramatic dose perturbations at and beyond the bone interfaces can occur due to the relative importance of the photoelectric effect at kilovoltage energies. These results will help improve dosimetric accuracy in pre-clinical experiments. This article is protected by copyright. All rights reserved.

A Multimodality Image Guided Precision Radiation Research Platform: Integrating X-ray, Bioluminescence, and Fluorescence Tomography With Radiation Therapy

PURPOSE

Small animal irradiation is crucial to the investigation of radiobiological mechanisms. The paradigm of clinical radiation therapy is trending toward high-precision, stereotactic treatment. However, translating this scheme to small animal irradiation is challenging owing to the lack of high-quality image guidance. To overcome this obstacle, we developed a multimodality image guided precision radiation platform.

METHODS AND MATERIALS

The platform consists of 4 modules: x-ray computed tomography (CT), bioluminescence tomography (BLT), fluorescence molecular tomography (FMT), and radiation therapy. CT provides animal anatomy and material density for radiation dose calculation, as well as body contour for BLT and FMT reconstruction. BLT and FMT provide tumor localization to guide radiation beams and molecular activity to evaluate treatment outcome. Furthermore, we developed a Monte Carlo-based treatment planning system (TPS) for 3-dimensional dose calculation, calibrated it using radiochromic films sandwiched in a water-equivalent phantom, and validated it using in vivo dosimeters surgically implanted into euthanized mice (n = 4). Finally, we performed image guided irradiation on mice bearing orthotopic breast and prostate tumors and confirmed radiation delivery using γH2AX histology.

RESULTS

The Monte Carlo-based TPS was successfully calibrated by benchmarking simulation dose against film measurement. For in vivo dosimetry measured in the euthanized mice, the average difference between the TPS calculated dose and measured dose was 3.86% ± 1.12%. Following the TPS-generated treatment plan, we successfully delivered 20 Gy dose to an animal bearing an orthotopic prostate tumor using 4 BLT-guided radiation beams and 5 Gy dose to an animal bearing an orthotopic breast tumor using a single FMT-guided radiation beam. γH2AX histology presented significantly more DNA damage in irradiated tumors and thus validated the dose delivery accuracy.

CONCLUSIONS

Combined with Monte Carlo TPS, this multimodality CT/BLT/FMT image guided small animal radiation platform can specifically localize tumors, accurately calculate dose distribution, precisely guide radiation delivery, and molecularly evaluate treatment response. It provides an advanced toolset for radiobiology and translational cancer research.

Validation of the analytical irradiator model and Monte Carlo dose engine in the small animal irradiation treatment planning system µ-RayStation 8B

Dose calculation in preclinical context with a clinical level of accuracy is a challenge due to the small animal scale and the medium photon energy range. In this work, we evaluate the effectiveness and accuracy of an analytical irradiator model combined with Monte Carlo (MC) calculations in the irradiated volume to calculate the dose delivered by a modern small animal irradiator. A model of the XRAD225Cx was created in µ-RayStation 8B, a preclinical treatment planning system, allowing arc and static beams for seven cylindrical collimators. Calculations with the µ-RayStation MC dose engine were compared with EBT3 measurements in water for all static beams and with a validated GATE model in water, heterogeneous media and a mouse CT. The GATE model is a complete MC representation of the XRAD225Cx. In water, µ-RayStation calculations, compared to GATE calculations and EBT3 measurements, agreed within a maximal error of 3.2% (mean absolute error of 0.6% and 0.8% respectively) and maximal distance-to-agreement (DTA) was 0.2 mm at 50% of the central dose. For a 5 mm static beam in heterogeneous media, the maximal absolute error between µ-RayStation and GATE calculations was below 1.3% in each medium and DTA was 0.1 mm at interfaces. For calculations on a mouse CT, µ-RayStation and GATE calculations agreed well for both static and arc beams. The 2D local gamma passing rate was  >98.9% for 1%/0.3 mm criteria and  >92.9% for 1%/0.2 mm criteria. Moreover, µ-RayStation reduces calculation time significantly comparing with GATE (speed-up factor between 120 and 680). These findings show that the analytical irradiator model presented in this work combined with the µ-RayStation MC dose engine accurately computes dose for the XRAD225Cx irradiator. The improvements in calculation time and availability of functionality and tools for managing, planning and evaluating the irradiation makes this platform very useful for pre-clinical irradiation research.

Fractionated head and neck irradiation impacts taste progenitors, differentiated taste cells, and Wnt/β-catenin signaling in adult mice

Head and neck cancer patients receiving conventional repeated, low dose radiotherapy (fractionated IR) suffer from taste dysfunction that can persist for months and often years after treatment. To understand the mechanisms underlying functional taste loss, we established a fractionated IR mouse model to characterize how taste buds are affected. Following fractionated IR, we found as in our previous study using single dose IR, taste progenitor proliferation was reduced and progenitor cell number declined, leading to interruption in the supply of new taste receptor cells to taste buds. However, in contrast to a single dose of IR, we did not encounter increased progenitor cell death in response to fractionated IR. Instead, fractionated IR induced death of cells within taste buds. Overall, taste buds were smaller and fewer following fractionated IR, and contained fewer differentiated cells. In response to fractionated IR, expression of Wnt pathway genes, Ctnnb1, Tcf7, Lef1 and Lgr5 were reduced concomitantly with reduced progenitor proliferation. However, recovery of Wnt signaling post-IR lagged behind proliferative recovery. Overall, our data suggest carefully timed, local activation of Wnt/β-catenin signaling may mitigate radiation injury and/or speed recovery of taste cell renewal following fractionated IR.

In vivo surface dosimetry with a scintillating fiber dosimeter in preclinical image-guided radiotherapy

PURPOSE

New preclinical image-guided irradiators and treatment planning systems represent a huge progress in radiobiology. Nevertheless, quality control of preclinical treatments is not as advanced as in clinical radiotherapy and in vivo dosimetry is less developed. In this study, we evaluate the use of a scintillating fiber dosimeter called DosiRat to verify the agreement between the doses planned with SmART-Plan and the measured doses during small animal irradiations.

METHODS

In vivo dosimetry was first evaluated with DosiRat through dose measurements performed at the surface of a 3 × 9 × 3 cm³ phantom. Measured and planned doses were compared for different irradiation conditions (prescription point, anterior, and posterior beams, 5 mm and 10 mm irradiation fields). In a second phase, measured and planned doses were compared for rat brain irradiations performed with anterior beams, with DosiRat positioned at the beam entrance. Comparisons were performed for different tube currents (1.3 and 13 mA), collimations (5, 10 and 25 mm diameter), and planned doses (0.1, 0.5, 2, and 10 Gy).

RESULTS

In the case of the phantom irradiations, planned and measured doses showed discrepancies smaller than the 5% accuracy of the TPS, except in cases in which the dosimeter was not centered in the irradiation field. The differences were larger for animal irradiations (from -3.3% to 8.8%) because of variations of the beam energy spectrum and the nonequivalence between materials at medium and low energy.

CONCLUSIONS

This study highlighted the complexity to implement one-dimension in vivo dosimetry in orthovoltage millimetric beams. Nevertheless, DosiRat is well adapted to in vivo dosimetry because of its small volume and its direct reading and allowed in vivo control of planned doses for anterior beams down to 5 mm diameter.

Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice

METHODS:

Dual energy CT (DECT) images of 9 female mice were used to extract the effective atomic number Zeff and the relative electron density ρe for each voxel in the images. To investigate the influence of the tissue compositions on the absorbed radiation dose for a typical kilovoltage photon beam, mass energy-absorption coefficients μen/ρ were calculated for 10 different tissues in each mouse.

RESULTS

Differences between human and murine tissue compositions can lead to errors around 7.5 % for soft tissues and 20.1 % for bone tissues in μen/ρ values for kilovoltage photon beams. When considering the spread within tissues, these errors can increase up to 17.5 % for soft tissues and 53.9 % for bone tissues within only a single standard deviation away from the mean tissue value.

CONCLUSION:

This study illustrates the need for murine reference tissue data. However, assigning only a single mean reference value to an entire tissue can still lead to large errors in dose calculations given the large spread within tissues of μen/ρ values found in this study. Therefore, new methods such as DECT and spectral CT imaging need to be explored, which can be important next steps in improving tissue assignment for dose calculations in small animal radiotherapy.

ADVANCES IN KNOWLEDGE:

This is the first study that investigates the implications of using human tissue compositions for dose calculations in mice for kilovoltage photon beams.

Toward automated and personalized organ dose determination in CT examinations - A comparison of two tissue characterization models for Monte Carlo organ dose calculation with a Therapy Planning System

PURPOSE

Computed tomography (CT) is a versatile tool in diagnostic radiology with rapidly increasing number of examinations per year globally. Routine adaption of the exposure level for patient anatomy and examination protocol cause the patients' exposures to become diversified and harder to predict by simple methods. To facilitate individualized organ dose estimates, we explore the possibility to automate organ dose calculations using a radiotherapy treatment planning system (TPS). In particular, the mapping of CT number to elemental composition for Monte Carlo (MC) dose calculations is investigated.

METHODS

Organ dose calculations were done for a female thorax examination test case with a TPS (Raystation™, Raysearch Laboratories AB, Stockholm, Sweden) utilizing a MC dose engine with a CT source model presented in a previous study. The TPS's inherent tissue characterization model for mapping of CT number to elemental composition of the tissues was calibrated using a phantom with known elemental compositions and validated through comparison of MC calculated dose with dose measured with Thermo Luminescence Dosimeters (TLD) in an anthropomorphic phantom. Given the segmentation tools of the TPS, organ segmentation strategies suitable for automation were analyzed for high contrast organs, utilizing CT number thresholding and model-based segmentation, and for low contrast organs utilizing water replacements in larger tissue volumes. Organ doses calculated with a selection of organ segmentation methods in combination with mapping of CT numbers to elemental composition (RT model), normally used in radiotherapy, were compared to a tissue characterization model with organ segmentation and elemental compositions defined by replacement materials [International Commission on Radiological Protection (ICRP) model], frequently favored in imaging dosimetry.

RESULTS

The results of the validation with the anthropomorphic phantom yielded mean deviations from the dose to water calculated with the RT and ICRP model as measured with TLD of 1.1% and 1.5% with maximum deviations of 6.1% and 8.7% respectively over all locations in the phantom. A strategy for automated organ segmentation was evaluated for two different risk organ groups, that is, low contrast soft organs and high contrast organs. The relative deviation between organ doses calculated with the RT model and with the ICRP model varied between 0% and 20% for the thorax/upper abdomen risk organs.

CONCLUSIONS

After calibration, the RT model in the TPS provides accurate MC dose results as compared to measurements with TLD and the ICRP model. Dosimetric feasible segmentation of the risk organs for a female thorax demonstrates a possibility for automation using the segmentation tool available in a TPS for high contrast organs. Low contrast soft organs can be represented by water volumes, but organ dose to the esophagus and thyroid must be determined using standardized organ shapes. The uncertainties of the organ doses are small compared to the overall uncertainty, at least an order of magnitude larger, in the estimates of lifetime attributable risk (LAR) based on organ doses. Large-scale and automated individual organ dose calculations could provide an improvement in cancer incidence estimates from epidemiological studies.

MicroCT imaging dose to mouse organs using a validated Monte Carlo model of the small animal radiation research platform (SARRP)

The goal of this work was to establish imaging dose to mouse organs with a validated Monte Carlo (MC) model of the image-guided Small Animal Radiation Research Platform (SARRP) and to investigate the effect of scatter from the internal walls on animal therapy dose determination. A MC model of the SARRP was built in the BEAMnrc code and validated with a series of homogeneous and heterogeneous phantom measurements. A segmented microCT scan of a mouse was used in DOSXYZnrc to determine mouse organ microCT imaging doses to 15-35 g mice for the SARRP pancake (mouse lying on couch) and standard (mouse standing on couch) imaging geometries for 40-80 kVp tube voltages. Imaging dose for off-center positioning shifts and maintaining image noise across tube voltages were also calculated. Half-value layer (HVL) measurements for the 220 kVp therapy beam in the presence of the SARRP shielding cabinet were modeled in BEAMnrc and compared to the 100 cm source-to-detector distance (SDD) in the scatter free, narrow-beam geometry recommended by the American Association of Physicists in Medicine Task Group 61 (AAPM TG-61). For a 60 kVp, 0.8 mA, and 60 s scan protocol, maximum mean organ imaging doses to boney and non-boney structures were 10.5 cGy and 3.5 cGy, respectively, for an average size 20 g mouse. Current-exposure combinations above 323, 203, 147, 116, and 95 mAs for 40-80 kVp tube voltages, respectively, will increase body doses above 10 cGy. MicroCT mean body dose was 18% lower in pancake compared to standard imaging geometry. An 11% difference in measured HVL at a 50 cm SDD was found compared to MC simulated HVL for the AAPM TG-61 recommended scatter free geometry at a 100 cm SDD. This change in HVL resulted in a 0.5% change in absorbed dose to water calculations for the treatment beam.

G4DARI: Geant4/GATE based Monte Carlo simulation interface for dosimetry calculation in radiotherapy

Monte Carlo (MC) simulation is widely recognized as an important technique to study the physics of particle interactions in nuclear medicine and radiation therapy. There are different codes dedicated to dosimetry applications and widely used today in research or in clinical application, such as MCNP, EGSnrc and Geant4. However, such codes made the physics easier but the programming remains a tedious task even for physicists familiar with computer programming. In this paper we report the development of a new interface GEANT4 Dose And Radiation Interactions (G4DARI) based on GEANT4 for absorbed dose calculation and for particle tracking in humans, small animals and complex phantoms. The calculation of the absorbed dose is performed based on 3D CT human or animal images in DICOM format, from images of phantoms or from solid volumes which can be made from any pure or composite material to be specified by its molecular formula. G4DARI offers menus to the user and tabs to be filled with values or chemical formulas. The interface is described and as application, we show results obtained in a lung tumor in a digital mouse irradiated with seven energy beams, and in a patient with glioblastoma irradiated with five photon beams. In conclusion, G4DARI can be easily used by any researcher without the need to be familiar with computer programming, and it will be freely available as an application package.

ESTRO ACROP: Technology for precision small animal radiotherapy research: Optimal use and challenges

Many radiotherapy research centers have recently installed novel research platforms enabling the investigation of the radiation response of tumors and normal tissues in small animal models, possibly in combination with other treatment modalities. Many more research institutes are expected to follow in the coming years. These novel platforms are capable of mimicking human radiotherapy more closely than older technology. To facilitate the optimal use of these novel integrated precision irradiators and various small animal imaging devices, and to maximize the impact of the associated research, the ESTRO committee on coordinating guidelines ACROP (Advisory Committee in Radiation Oncology Practice) has commissioned a report to review the state of the art of the technology used in this new field of research, and to issue recommendations. This report discusses the combination of precision irradiation systems, small animal imaging (CT, MRI, PET, SPECT, bioluminescence) systems, image registration, treatment planning, and data processing. It also provides guidelines for reporting on studies.

A new tissue segmentation method to calculate 3D dose in small animal radiation therapy

Background

In pre-clinical animal experiments, radiation delivery is usually delivered with kV photon beams, in contrast to the MV beams used in clinical irradiation, because of the small size of the animals. At this medium energy range, however, the contribution of the photoelectric effect to absorbed dose is significant. Accurate dose calculation therefore requires a more detailed tissue definition because both density (ρ) and elemental composition (Z_eff) affect the dose distribution. Moreover, when applied to cone beam CT (CBCT) acquisitions, the stoichiometric calibration of HU becomes inefficient as it is designed for highly collimated fan beam CT acquisitions. In this study, we propose an automatic tissue segmentation method of CBCT imaging that assigns both density (ρ) and elemental composition (Z_eff) in small animal dose calculation.

Methods

The method is based on the relationship found between CBCT number and ρ*Z_eff product computed from known materials. Monte Carlo calculations were performed to evaluate the impact of ρZ_eff variation on the absorbed dose in tissues. These results led to the creation of a tissue database composed of artificial tissues interpolated from tissue values published by the ICRU. The ρZ_eff method was validated by measuring transmitted doses through tissue substitute cylinders and a mouse with EBT3 film. Measurements were compared to the results of the Monte Carlo calculations.

Results

The study of the impact of ρZ_eff variation over the range of materials, from ρZ_eff = 2 g.cm^− 3 (lung) to 27 g.cm^− 3 (cortical bone) led to the creation of 125 artificial tissues. For tissue substitute cylinders, the use of ρZ_eff method led to maximal and average relative differences between the Monte Carlo results and the EBT3 measurements of 3.6% and 1.6%. Equivalent comparison for the mouse gave maximal and average relative differences of 4.4% and 1.2%, inside the 80% isodose area. Gamma analysis led to a 94.9% success rate in the 10% isodose area with 4% and 0.3 mm criteria in dose and distance.

Conclusions

Our new tissue segmentation method was developed for 40kVp CBCT images. Both density and elemental composition are assigned to each voxel by using a relationship between HU and the product ρZ_eff. The method, validated by comparing measurements and calculations, enables more accurate small animal dose distribution calculated on low energy CBCT images.

The impact of dual energy CT imaging on dose calculations for pre-clinical studies

BACKGROUND

To investigate the feasibility of using dual-energy CT (DECT) for tissue segmentation and kilovolt (kV) dose calculations in pre-clinical studies and assess potential dose calculation accuracy gain.

METHODS

Two phantoms and an ex-vivo mouse were scanned in a small animal irradiator with two distinct energies. Tissue segmentation was performed with the single-energy CT (SECT) and DECT methods. A number of different material maps was used. Dose calculations were performed to verify the impact of segmentations on the dose accuracy.

RESULTS

DECT showed better overall results in comparison to SECT. Higher number of DECT segmentation media resulted in smaller dose differences in comparison to the reference. Increasing the number of materials in the SECT method yielded more instability. Both modalities showed a limit to which adding more materials with similar characteristics ceased providing better segmentation results, and resulted in more noise in the material maps and the dose distributions. The effect was aggravated with a decrease in beam energy. For the ex-vivo specimen, the choice of only one high dense bone for the SECT method resulted in large volumes of tissue receiving high doses. For the DECT method, the choice of more than one kind of bone resulted in lower dose values for the different tissues occupying the same volume. For the organs at risk surrounded by bone, the doses were lower when using the SECT method in comparison to DECT, due to the high absorption of the bone. SECT material segmentation may lead to an underestimation of the dose to OAR in the proximity of bone.

CONCLUSIONS

The DECT method enabled the selection of a higher number of materials thereby increasing the accuracy in dose calculations. In phantom studies, SECT performed best with three materials and DECT with seven for the phantom case. For irradiations in preclinical studies with kV photon energies, the use of DECT segmentation combined with the choice of a low-density bone is recommended.

Multi-institutional MicroCT image comparison of image-guided small animal irradiators

To recommend imaging protocols and establish tolerance levels for microCT image quality assurance (QA) performed on conformal image-guided small animal irradiators. A fully automated QA software SAPA (small animal phantom analyzer) for image analysis of the commercial Shelley micro-CT MCTP 610 phantom was developed, in which quantitative analyses of CT number linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, spatial resolution by means of modulation transfer function (MTF), and CT contrast were performed. Phantom microCT scans from eleven institutions acquired with four image-guided small animal irradiator units (including the commercial PXi X-RAD SmART and Xstrahl SARRP systems) with varying parameters used for routine small animal imaging were analyzed. Multi-institutional data sets were compared using SAPA, based on which tolerance levels for each QA test were established and imaging protocols for QA were recommended. By analyzing microCT data from 11 institutions, we established image QA tolerance levels for all image quality tests. CT number linearity set to R ²  >  0.990 was acceptable in microCT data acquired at all but three institutions. Acceptable SNR  >  36 and noise levels  <55 HU were obtained at five of the eleven institutions, where failing scans were acquired with current-exposure time of less than 120 mAs. Acceptable spatial resolution (>1.5 lp mm^-1 for MTF  =  0.2) was obtained at all but four institutions due to their large image voxel size used (>0.275 mm). Ten of the eleven institutions passed the set QA tolerance for geometric accuracy (<1.5%) and nine of the eleven institutions passed the QA tolerance for contrast (>2000 HU for 30 mgI ml^-1). We recommend performing imaging QA with 70 kVp, 1.5 mA, 120 s imaging time, 0.20 mm voxel size, and a frame rate of 5 fps for the PXi X-RAD SmART. For the Xstrahl SARRP, we recommend using 60 kVp, 1.0 mA, 240 s imaging time, 0.20 mm voxel size, and 6 fps. These imaging protocols should result in high quality images that pass the set tolerance levels on all systems. Average SAPA computation time for complete QA analysis for a 0.20 mm voxel, 400 slice Shelley phantom microCT data set was less than 20 s. We present image quality assurance recommendations for image-guided small animal radiotherapy systems that can aid researchers in maintaining high image quality, allowing for spatially precise conformal dose delivery to small animals.

Scattered Dose Calculations and Measurements in a Life-Like Mouse Phantom

Anatomically accurate phantoms are useful tools for radiation dosimetry studies. In this work, we demonstrate the construction of a new generation of life-like mouse phantoms in which the methods have been generalized to be applicable to the fabrication of any small animal. The mouse phantoms, with built-in density inhomogeneity, exhibit different scattering behavior dependent on where the radiation is delivered. Computer models of the mouse phantoms and a small animal irradiation platform were devised in Monte Carlo N-Particle code (MCNP). A baseline test replicating the irradiation system in a computational model shows minimal differences from experimental results from 50 Gy down to 0.1 Gy. We observe excellent agreement between scattered dose measurements and simulation results from X-ray irradiations focused at either the lung or the abdomen within our phantoms. This study demonstrates the utility of our mouse phantoms as measurement tools with the goal of using our phantoms to verify complex computational models.

Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

OBJECTIVE

The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system.

METHODS

The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Z_eff) and relative electron densities (ρ_e) for phantom inserts with known elemental compositions and relative electron densities.

RESULTS

The optimal energy combination was determined to be 50 and 90 kVp. For this combination, Z_eff and ρ_e can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60 cGy.

CONCLUSION

Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Z_eff and ρ_e. When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Z_eff and ρ_e errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system.

A kernel-based dose calculation algorithm for kV photon beams with explicit handling of energy and material dependencies

Objective:

Mimicking state-of-the-art patient radiotherapy with high-precision irradiators for small animals is expected to advance the understanding of dose–effect relationships and radiobiology in general. We work on the implementation of intensity-modulated radiotherapy-like irradiation schemes for small animals. As a first step, we present a fast analytical dose calculation algorithm for keV photon beams.

Methods:

We follow a superposition–convolution approach adapted to kV X-rays, based on previous work for microbeam therapy. We assume local energy deposition at the photon interaction point due to the short electron ranges in tissue. This allows us to separate the dose calculation into locally absorbed primary dose and the scatter contribution, calculated in a point kernel approach. We validate our dose model against Geant4 Monte Carlo (MC) simulations and compare the results to Muriplan (XStrahl Ltd, Camberley, UK).

Results:

For field sizes of (1 mm)² to (1 cm)² in water, the depth dose curves show a mean disagreement of 1.7% to MC simulations, with the largest deviations in the entrance region (4%) and at large depths (5% at 7 cm). Larger discrepancies are observed at water-to-bone boundaries, in bone and at the beam edges in slab phantoms and a mouse brain. Calculation times are in the order of 5 s for a single beam.

Conclusion:

The algorithm shows good agreement with MC simulations in an initial validation. It has the potential to become an alternative to full MC dose calculation.

Advances in knowledge:

The presented algorithm demonstrates the potential of kernel-based dose calculation for kV photon beams. It will be valuable in intensity-modulated radiotherapy and inverse treatment planning for high precision small-animal radiotherapy.

[Small animal image-guided radiotherapy: A new era for preclinical studies]

Preclinical external beam radiotherapy irradiations used to be delivered with a static broad beam. To promote the transfer from animal to man, the preclinical treatment techniques dedicated to the animal have been optimized to be similar to those delivered to patients in clinical practice. In this context, preclinical irradiators have been developed. Due to the small sizes of the animals, and the irradiation beams, the scaling to the small animal dimensions involves specific problems. Reducing the size and energy of the irradiation beams require very high technical performance, especially for the mechanical stability of the irradiator and the spatial resolution of the imaging system. In addition, the determination of the reference absorbed dose rate must be conducted with a specific methodology and suitable detectors. To date, three systems are used for preclinical studies in France. The aim of this article is to present these new irradiators dedicated to small animals from a physicist point of view, including the commissioning and the quality control.

MRI-Only Based Radiotherapy Treatment Planning for the Rat Brain on a Small Animal Radiation Research Platform (SARRP)

Computed tomography (CT) is the standard imaging modality in radiation therapy treatment planning (RTP). However, magnetic resonance (MR) imaging provides superior soft tissue contrast, increasing the precision of target volume selection. We present MR-only based RTP for a rat brain on a small animal radiation research platform (SARRP) using probabilistic voxel classification with multiple MR sequences. Six rat heads were imaged, each with one CT and five MR sequences. The MR sequences were: T1-weighted, T2-weighted, zero-echo time (ZTE), and two ultra-short echo time sequences with 20 μs (UTE1) and 2 ms (UTE2) echo times. CT data were manually segmented into air, soft tissue, and bone to obtain the RTP reference. Bias field corrected MR images were automatically segmented into the same tissue classes using a fuzzy c-means segmentation algorithm with multiple images as input. Similarities between segmented CT and automatic segmented MR (ASMR) images were evaluated using Dice coefficient. Three ASMR images with high similarity index were used for further RTP. Three beam arrangements were investigated. Dose distributions were compared by analysing dose volume histograms. The highest Dice coefficients were obtained for the ZTE-UTE2 combination and for the T1-UTE1-T2 combination when ZTE was unavailable. Both combinations, along with UTE1-UTE2, often used to generate ASMR images, were used for further RTP. Using 1 beam, MR based RTP underestimated the dose to be delivered to the target (range: 1.4%-7.6%). When more complex beam configurations were used, the calculated dose using the ZTE-UTE2 combination was the most accurate, with 0.7% deviation from CT, compared to 0.8% for T1-UTE1-T2 and 1.7% for UTE1-UTE2. The presented MR-only based workflow for RTP on a SARRP enables both accurate organ delineation and dose calculations using multiple MR sequences. This method can be useful in longitudinal studies where CT's cumulative radiation dose might contribute to the total dose.

Monte Carlo comparison of x-ray and proton CT for range calculations of proton therapy beams

Proton computed tomography (CT) has been described as a solution for imaging the proton stopping power of patient tissues, therefore reducing the uncertainty of the conversion of x-ray CT images to relative stopping power (RSP) maps and its associated margins. This study aimed to investigate this assertion under the assumption of ideal detection systems. We have developed a Monte Carlo framework to assess proton CT performances for the main steps of a proton therapy treatment planning, i.e. proton or x-ray CT imaging, conversion to RSP maps based on the calibration of a tissue phantom, and proton dose simulations. Irradiations of a computational phantom with pencil beams were simulated on various anatomical sites and the proton range was assessed on the reference, the proton CT-based and the x-ray CT-based material maps. Errors on the tissue's RSP reconstructed from proton CT were found to be significantly smaller and less dependent on the tissue distribution. The imaging dose was also found to be much more uniform and conformal to the primary beam. The mean absolute deviation for range calculations based on x-ray CT varies from 0.18 to 2.01 mm depending on the localization, while it is smaller than 0.1 mm for proton CT. Under the assumption of a perfect detection system, proton range predictions based on proton CT are therefore both more accurate and more uniform than those based on x-ray CT.

Modeling a superficial radiotherapy X-ray source for relative dose calculations

The purpose of this study was to empirically characterize and validate a kilovoltage (kV) X‐ray beam source model of a superficial X‐ray unit for relative dose calculations in water and assess the accuracy of the British Journal of Radiology Supplement 25 (BJR 25) percentage depth dose (PDD) data. We measured central axis PDDs and dose profiles using an Xstrahl 150 X‐ray system. We also compared the measured and calculated PDDs to those in the BJR 25. The Xstrahl source was modeled as an effective point source with varying spatial fluence and spectra. In‐air ionization chamber measurements were made along the x‐ and y‐axes of the X‐ray beam to derive the spatial fluence and half‐value layer (HVL) measurements were made to derive the spatially varying spectra. This beam characterization and resulting source model was used as input for our in‐house dose calculation software (kVDoseCalc) to compute radiation dose at points of interest (POIs). The PDDs and dose profiles were measured using 2, 5, and 15 cm cone sizes at 80, 120, 140, and 150 kVp energies in a scanning water phantom using IBA Farmer‐type ionization chambers of volumes 0.65 and 0.13 cc, respectively. The percent difference in the computed PDDs compared with our measurements range from −4.8% to 4.8%, with an overall mean percent difference and standard deviation of 1.5% and 0.7%, respectively. The percent difference between our PDD measurements and those from BJR 25 range from −14.0% to 15.7%, with an overall mean percent difference and standard deviation of 4.9% and 2.1%, respectively — showing that the measurements are in much better agreement with kVDoseCalc than BJR 25. The range in percent difference between kVDoseCalc and measurement for profiles was −5.9% to 5.9%, with an overall mean percent difference and standard deviation of 1.4% and 1.4%, respectively. The results demonstrate that our empirically based X‐ray source modeling approach for superficial X‐ray therapy can be used to accurately compute relative dose in a homogeneous water‐equivalent medium. They also show limitations in the accuracy of the BJR 25 PDD data.

PACS number: 87.55.kh

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

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.

Modality comparison for small animal radiotherapy: a simulation study

PURPOSE

Small animal radiation therapy has advanced significantly in recent years. Whereas in the past dose was delivered using a single beam and a lead shield for sparing of healthy tissue, conformal doses can be now delivered using more complex dedicated small animal radiotherapy systems with image guidance. The goal of this paper is to investigate dose distributions for three small animal radiation treatment modalities.

METHODS

This paper presents a comparison of dose distributions generated by the three approaches-a single-field irradiator with a 200 kV beam and no image guidance, a small animal image-guided conformal system based on a modified microCT scanner with a 120 kV beam developed at Stanford University, and a dedicated conformal system, SARRP, using a 220 kV beam developed at Johns Hopkins University. The authors present a comparison of treatment plans for the three modalities using two cases: a mouse with a subcutaneous tumor and a mouse with a spontaneous lung tumor. A 5 Gy target dose was calculated using the EGSnrc Monte Carlo codes.

RESULTS

All treatment modalities generated similar dose distributions for the subcutaneous tumor case, with the highest mean dose to the ipsilateral lung and bones in the single-field plan (0.4 and 0.4 Gy) compared to the microCT (0.1 and 0.2 Gy) and SARRP (0.1 and 0.3 Gy) plans. The lung case demonstrated that due to the nine-beam arrangements in the conformal plans, the mean doses to the ipsilateral lung, spinal cord, and bones were significantly lower in the microCT plan (2.0, 0.4, and 1.9 Gy) and the SARRP plan (1.5, 0.5, and 1.8 Gy) than in single-field irradiator plan (4.5, 3.8, and 3.3 Gy). Similarly, the mean doses to the contralateral lung and the heart were lowest in the microCT plan (1.5 and 2.0 Gy), followed by the SARRP plan (1.7 and 2.2 Gy), and they were highest in the single-field plan (2.5 and 2.4 Gy). For both cases, dose uniformity was greatest in the single-field irradiator plan followed by the SARRP plan due to the sensitivity of the lower energy microCT beam to target heterogeneities and image noise.

CONCLUSIONS

The two treatment planning examples demonstrate that modern small animal radiotherapy techniques employing image guidance, variable collimation, and multiple beam angles deliver superior dose distributions to small animal tumors as compared to conventional treatments using a single-field irradiator. For deep-seated mouse tumors, however, higher-energy conformal radiotherapy could result in higher doses to critical organs compared to lower-energy conformal radiotherapy. Treatment planning optimization for small animal radiotherapy should therefore be developed to take full advantage of the novel conformal systems.

Monte Carlo model of the scanning beam digital x-ray (SBDX) source

The scanning-beam digital x-ray (SBDX) system has been developed for fluoroscopic imaging using an inverse x-ray imaging geometry. The SBDX system consists of a large-area x-ray source with a multihole collimator and a small detector. The goal of this study was to build a Monte Carlo (MC) model of the SBDX source as a useful tool for optimization of the SBDX imaging system in terms of its hardware components and imaging parameters. The MC model of the source was built in the EGSnrc/BEAMnrc code and validated using the DOSXYZnrc code and Gafchromic film measurements for 80, 100, and 120 kV x-ray source voltages. The MC simulated depth dose curves agreed with measurements to within 5%, and beam profiles at three selected depths generally agreed within 5%. Exposure rates and half-value layers for three voltages were also calculated from the MC simulations. Patient skin-dose per unit detector-dose was quantified as a function of patient size for all three x-ray source voltages. The skin-dose to detector-dose ratio ranged from 5-10 for a 20 cm thick patient to 1 × 10(3)-1 × 10(5) for a 50 cm patient for the 120 and 80 kV beams, respectively. Simulations of imaging dose for a prostate patient using common imaging parameters revealed that skin-dose per frame was as low as 0.2 mGy.

Surface dose reduction from bone interface in kilovoltage X-ray radiation therapy: a Monte Carlo study of photon spectra

This study evaluated the dosimetric impact of surface dose reduction due to the loss of backscatter from the bone interface in kilovoltage (kV) X‐ray radiation therapy. Monte Carlo simulation was carried out using the EGSnrc code. An inhomogeneous phantom containing a thin water layer (0.5–5 mm) on top of a bone (thickness=1 cm) was irradiated by a clinical 105 kVp photon beam produced by a Gulmay D3225 X‐ray machine. Field sizes of 2, 5, and 10 cm diameter and source‐to‐surface distance of 20 cm were used. Surface doses for different phantom configurations were calculated using the DOSXYZnrc code. Photon energy spectra at the phantom surface and bone were determined according to the phase‐space files at the particle scoring planes which included the multiple crossers. For comparison, all Monte Carlo simulations were repeated in a phantom with the bone replaced by water. Surface dose reduction was found when a bone was underneath the water layer. When the water thickness was equal to 1 mm for the circular field of 5 cm diameter, a surface dose reduction of 6.3% was found. The dose reduction decreased to 4.7% and 3.4% when the water thickness increased to 3 and 5 mm, respectively. This shows that the impact of the surface dose uncertainty decreased while the water thickness over the bone increased. This result was supported by the decrease in relative intensity of the lower energy photons in the energy spectrum when the water layer was with and over the bone, compared to without the bone. We concluded that surface dose reduction of 7.8%–1.1% was found when the water thickness increased from 0.5–5 mm for circular fields with diameters ranging from 2–10 cm. This decrease of surface dose results in an overestimation of prescribed dose at the patient's surface, and might be a concern when using kV photon beam to treat skin tumors in sites such as forehead, chest wall, and kneecap.

PACS number: 87.55.K‐; 87.55.ne; 87.57.uq

Design and development of a new micro-beam treatment planning system: effectiveness of algorithms of optimization and dose calculations and potential of micro-beam treatment

A new treatment planning system (TPS) was designed and developed for a new treatment system, which consisted of a micro-beam-enabled linac with robotics and a real-time tracking system. We also evaluated the effectiveness of the implemented algorithms of optimization and dose calculations in the TPS for the new treatment system. In the TPS, the optimization procedure consisted of the pseudo Beam's-Eye-View method for finding the optimized beam directions and the steepest-descent method for determination of beam intensities. We used the superposition-/convolution-based (SC-based) algorithm and Monte Carlo-based (MC-based) algorithm to calculate dose distributions using CT image data sets. In the SC-based algorithm, dose density scaling was applied for the calculation of inhomogeneous corrections. The MC-based algorithm was implemented with Geant4 toolkit and a phase-based approach using a network-parallel computing. From the evaluation of the TPS, the system can optimize the direction and intensity of individual beams. The accuracy of the dose calculated by the SC-based algorithm was less than 1% on average with the calculation time of 15 s for one beam. However, the MC-based algorithm needed 72 min for one beam using the phase-based approach, even though the MC-based algorithm with the parallel computing could decrease multiple beam calculations and had 18.4 times faster calculation speed using the parallel computing. The SC-based algorithm could be practically acceptable for the dose calculation in terms of the accuracy and computation time. Additionally, we have found a dosimetric advantage of proton Bragg peak-like dose distribution in micro-beam treatment.