Patient-specific Dose Research Articles

DVHnet: A deep learning-based prediction of patient-specific dose volume histograms for radiotherapy planning.

To develop a deep learning method to predict patient-specific dose volume histograms (DVHs) for radiotherapy planning. Patient data included 180 cases with nasopharyngeal cancer, of which 153 cases were used for training and 27 for testing. A network (named "DVHnet") based on a convolutional neural network (CNN) was designed for directly predicting DVHs of organs at risk (OARs). Two-channel images with contoured structures were generated as the inputs for training the model. A one-dimensional array consisting of 256 continuous volume percentages on a DVH curve for each slice was calculated as the corresponding output. The combined DVH was then calculated. Sixteen OARs were modeled in the study. Prediction accuracy was evaluated against the corresponding DVH curve of ground truth (GT) plans. A global DVH analysis and critical dosimetry metrics for each OAR were calculated for quantitative evaluation. The performance of DVHnet also was evaluated against two baselines: DosemapNet (developed by our research group) and commercial RapidPlan software. The predicted mean difference in average dose of all OARs using DVHnet was 0.30±0.95Gy. And the predicted differences in D2% and D50 can be control within 2.32 and 0.69Gy. For most OARs, there were no obvious differences between the dosimetric metrics of the predicted and GT values for both DVHnet and DosemapNet (P≥0.05). Only the predicted D2% of the optic organs for DVHnet, and of brain stem PRV for DosemapNet displayed statistically significant differences. Except for the optic organs, DVHnet performs better than or comparably with RapidPlan. The mean difference in proportion of points of interest was 3.59%±7.78%. A deep learning network model was developed to automatically extract useful features for accurate prediction of patient-specific DVH curves directly. The performance of DVHnet was comparable to DosemapNet and RapidPlan.

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly used in breast cancer screening and diagnostics. Still, the severely limited 3rd dimension information in DBT has not been used, until now, to estimate the true breast density or the patient-specific dose. This study proposes a reconstruction algorithm for DBT based on deep learning specifically optimized for these tasks. The algorithm, which we name DBToR, is based on unrolling a proximal-dual optimization method. The proximal operators are replaced with convolutional neural networks and prior knowledge is included in the model. This extends previous work on a deep learning-based reconstruction model by providing both the primal and the dual blocks with breast thickness information, which is available in DBT. Training and testing of the model were performed using virtual patient phantoms from two different sources. Reconstruction performance, and accuracy in estimation of breast density and radiation dose, were estimated, showing high accuracy (density <±3%; dose <±20%) without bias, significantly improving on the current state-of-the-art. This work also lays the groundwork for developing a deep learning-based reconstruction algorithm for the task of image interpretation by radiologists.

Fluence-modulated proton CT optimized with patient-specific dose and variance objectives for proton dose calculation

Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achieved and demonstrated imaging dose reductions outside of the ROI of 74% on average, reducing the imaging dose from 1.2 to 0.3 mGy. Such dose savings are expected to be relevant compared to the therapeutic dose outside of the treatment field. Treatment doses were re-calculated on the FMpCT images and compared to treatment doses re-recalculated on uniform fluence pCT scans using a 1% criterion. Passing rates were above 98.3% for all patients. Passing rates comparing FMpCT treatment doses to the ground truth treatment dose were above 88.5% for all patients. Evaluation of the proton range with a 1 mm criterion resulted in passing rates above 97.5% (FMpCT/pCT) and 95.3% (FMpCT/ground truth). Jointly optimized fluence-modulated pCT images can be used for proton dose calculation maintaining the full dosimetric accuracy of pCT but reducing the required imaging dose considerably by three quarters. This may allow for daily imaging during particle therapy ensuring a safe and accurate delivery of the therapeutic dose and avoiding excess dose from imaging.

Dosimetric investigation of 103Pd permanent breast seed implant brachytherapy based on Monte Carlo calculations

PurposePermanent breast seed implant using 103Pd is emerging as an effective adjuvant radiation technique for early stage breast cancer. However, clinical dose evaluations follow the water-based TG-43 approach with its considerable approximations. Toward clinical adoption of advanced TG-186 model-based dose evaluations, this study presents a comprehensive investigation for permanent breast seed implant considering both target and normal tissue doses. Methods and MaterialsDose calculations are performed with the free open-source Monte Carlo (MC) code, egs_brachy, using two types of virtual patient models: TG43sim (simulated TG-43 conditions) and MCref (heterogeneous tissue modeling from patient CT, seeds at implant angle) for 35 patients. The sensitivity of dose metrics to seed orientation and tissue segmentation are assessed. ResultsIn the target volume, D90 is 14.1 ± 5.8% lower with MCref than with TG43sim, on average. Conversely, normal tissue doses are generally higher with MCref than with TG43sim, for example, by 22 ± 13% for skin D1cm2, 82 ± 7% for ribs Dmax, and 71 ± 23% for heart D1cm3. Discrepancies between MCref and TG43sim doses vary over the patient cohort, as well as with the tissue and metric considered. Skin doses are particularly sensitive to seed orientation, with average difference of 4% (maximum 28%) in D1cm2 for seeds modeled vertically (egs_brachy default) compared with those aligned with implant angle. ConclusionsTG-43 dose evaluations generally underestimate doses to critical normal organs/tissues while overestimating target doses. There is considerable variation in MCref and TG43sim on a patient-by-patient basis, motivating clinical adoption of patient-specific MC dose calculations. The MCref framework presented herein provides a consistent modeling approach for clinical implementation of advanced TG-186 dose calculations.

PATIENT-SPECIFIC DOSE ESTIMATES IN DYNAMIC COMPUTED TOMOGRAPHY MYOCARDIAL PERFUSION EXAMINATION.

The study aimed to implement realistic source models of a computed tomography (CT) scanner and Monte Carlo simulations to actual patient data and to calculate patient-specific organ and effective dose estimates for patients undergoing dynamic CT myocardial perfusion examinations. Source models including bowtie filter, tube output and x-ray spectra were determined for a dual-source Siemens Somatom Definition Flash scanner. Twenty CT angiography patient datasets were merged with a scaled International Commission on Radiological Protection (ICRP) 110 voxel phantom. Dose simulations were conducted with ImpactMC software. Effective dose estimates varied from 5.0 to 14.6 mSv for the 80 kV spectrum and from 8.9 to 24.7 mSv for the 100 kV spectrum. Significant differences in organ doses and effective doses between patients emphasise the need to use actual patient data merged with matched anthropomorphic anatomy in the dose simulations to achieve a reasonable level of accuracy in the dose estimation procedure.

Анализ побочного сочетанного воздействия радиойодной и лучевой терапии у больных раком щитовидной железы

Radical surgery is the mainstay for differentiated thyroid cancer, radioiodine therapy followed by the surgery is the “gold standard” treatment modality indicated after the surgery. Radioiodine therapy becomes practically non-alternative treatment for patients with distant metastases. How-ever, orally administered radioiodine may be also absorbed into the bloodstream and can dam-age surrounding normal organs and tissues and cause side effect. To test radioiodine therapy safety side effects of the radionuclide on somatic cells should be accurately assessed. In addi-tion, external beam radiotherapy can also damage adjacent normal organs and tissues and thereby increases radioiodine therapy side effect. It is possible to evaluate patient-specific total radiation dose with the use of cytogenetic assay of chromosome aberrations level in peripheral blood lymphocytes because some types of chromosome aberrations are specific radiation mark-ers clearly indicating that the cells have been exposed to radiation. Radiation absorbed dose can be estimated by the number of the aberrations occurrence frequency, and the value of side radia-tion dose greatly depends on a patient personality. In this case peripheral blood lymphocytes are thought of as a model of somatic and bone marrow cells. The paper present results of application of cytogenetic assay for estimating side effects caused by exposure of adjacent organs and tis-sues to external beam radiotherapy and surrounding somatic cells to radioiodine therapy. Results of statistical analysis of external beam radiotherapy related side effect contribution to the total side effect are present in the paper. The joint group of 43 patients was involved in the study, all patients received radioiodine therapy and 5 of them received also external beam radiotherapy in addition to radioiodine therapy. All patents received radioiodine therapy in the Radionuclide Therapy Department, A. Tsyb MRRC in Obninsk. Cytogenetic assay was carried out in the Radia-tion Cytogenetics Laboratory, A. Tsyb MRRC. Results of the study and examination of regularities of radioiodine therapy and external beam radiotherapy related side effects development make it evident that patients received combining radioiodine therapy and external beam radiotherapy should present special group with the treatment plan different from that for the radioiodine thera-py exposed group. Exposure to external radiation may cause not only significant overestimation but also a false-positive underestimation of the number of radiation-specific markers because of lymphocytes inhibition following exposure to high total radiation dose. Inhibition effect may be a result of overestimating multiple radioiodine therapy administrations to achieve total I-131 activity (Σact) exceeds 1200 mCi. The absolute value of the total focal radiotherapy dose is probably ir-relevant. In general, patients assigned to both radioiodine therapy and external beam radiothera-py require personalized approach to treatment.

Development of patient-specific 3D models from histopathological samples for applications in radiation therapy.

The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p<0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.

Intravenous Fluid Management in Critically Ill Adults: A Review.

This article reviews the management of intravenous fluids and the evaluation of volume status in critically ill adults. Intravenous fluid administration is one of the most common interventions in the intensive care unit. Critically ill patients have dynamic fluid requirements, making the management of fluid therapy challenging. New literature suggests that balanced salt solutions may be preferred in some patient populations. The bedside critical care nurse must understand the properties of various intravenous fluids and their corresponding impact on human physiology. The nurse's clinical and laboratory assessments of each patient help define the goals of fluid therapy, which will in turn be used to determine the optimal patient-specific selection and dose of fluid for administration. Nurses serve a vital role in monitoring the safety and efficacy of intravenous fluid therapy. Although this intervention can be lifesaving, inappropriate use of fluids has the potential to yield detrimental effects. This article discusses fluid physiology and the goals of intravenous fluid therapy, compares the types of intravenous fluids (isotonic crystalloids, including 0.9% sodium chloride and balanced salt solutions; hypotonic and hypertonic crystalloids; and colloids) and their adverse effects and impact on hemodynamics, and describes the critical care nurse's essential role in selecting and monitoring intravenous fluid therapy.

Personalized Targeted Radioimmunotherapy with Anti-CD45 Iodine (131I) Apamistamab [Iomab-B] in Patients with Active Relapsed or Refractory Acute Myeloid Leukemia Results in Successful Donor Hematopoietic Cells Engraftment with the Timing of Engraftment Not Related to the Radiation Dose Delivered

Personalized Targeted Radioimmunotherapy with Anti-CD45 Iodine (131I) Apamistamab [Iomab-B] in Patients with Active Relapsed or Refractory Acute Myeloid Leukemia Results in Successful Donor Hematopoietic Cells Engraftment with the Timing of Engraftment Not Related to the Radiation Dose Delivered

Vincristine Sulfate Liposome Injection (VSLI) with Bendamustine and Rituximab As First-Line Therapy for Indolent B-Cell Lymphomas: A Phase 1 Study

Vincristine Sulfate Liposome Injection (VSLI) with Bendamustine and Rituximab As First-Line Therapy for Indolent B-Cell Lymphomas: A Phase 1 Study

PO-1431: Patient-specific dose calculations from a proton gantry mounted CBCT system: implementation in TOPAS

PO-1431: Patient-specific dose calculations from a proton gantry mounted CBCT system: implementation in TOPAS

A Novel Prostate SBRT vs HDR Comparison: A Disease Perspective

To compare current SBRT and HDR prostate treatment regimens from a disease perspective using the latest published dose-response functions We developed and validated a comprehensive software platform enabling in-silico growth of realistic prostate tumor-like volumes of random shape and morphology within prostate. Published probabilities of disease occurrence in various prostate zonal anatomies, for various disease stages were taken into account when tumorlets were generated. The model used the patient-specific segmented anatomy and dose distributions delivered for 10 patients. 4500 tumorlets, ranging from 0.1 to 10 cm3 were generated. Each tumorlet was overlapped with the dose distribution and the corresponding radiobiological integral parameters (EUBED, gBEUD) were computed. Data from 25 international radiotherapy outcome datasets, stratified by risk and use of ADT, were used to generate dose-response curves, fractionation sensitivity and repopulation. These values then enabled our model to convert integral metrics parameters into a probability of cure (PoC). A large range of radiobiological parameters, α/b = [1.5, 7.7] Gy and α = [0.04, 0.3] Gy-1 were explored in comparing currently accepted regimens (e.g. 7.25Gy x 5 and 13.5Gy x 2). SBRT plans were created using both RTOG 0938 and NRG GU005 criteria. A version of the plan was escalated from 36.25 to 40Gy. The two methods of integrating radio-biological dose effect (EUBED and gBEUD) handle dose inhomogeneity differently. SBRT plans display less dose inhomogeneity and consequently both formalisms produce very similar results. For HDR plans, which have more dose heterogeneity, the two formalisms produce slightly different results but for both, the PoC tends to decrease with the increased disease volume. Similar SBRT and HDR outcomes were observed for a very low α/b (1.5) and only low and intermediate risk disease. For higher α/b values, for all the dose-response curves examined, predictions showed that HDR provided a 5-30% increase in PoC, increasing with increased α/b and risk strata. The NRG plans, requiring higher dose coverage (98% vs 95%), produce, for the same prescription dose, a 1-5% PoC increase. The NRG 40Gy plans restore some of the PoC, when compared to HDR, particularly at large tumor volumes. We are presenting a novel perspective in comparing two treatment modalities or regimens. Our results show that using prescription dose alone in a BED-style equivalence, particularly when accounting for large degrees of variability in planning styles and delivery, has a limited value. The method we are proposing, looking at probabilities of cure at disease level –tumorlets- rather than physical peripheral prescription dose at gland level, has the potential to create a true equivalence between established and time-tested treatments (HDR) and newer modalities (SBRT), while accounting for all existent planning style variability.

Deterministic linear Boltzmann transport equation solver for patient-specific CT dose estimation: Comparison against a Monte Carlo benchmark for realistic scanner configurations and patient models.

Epidemiological evidence suggests an increased risk of cancer related to computed tomography (CT) scans, with children exposed to greater risk. The purpose of this work is to test the reliability of a linear Boltzmann transport equation (LBTE) solver for rapid and patient-specific CT dose estimation. This includes building a flexible LBTE framework for modeling modern clinical CT scanners and to validate the resulting dose maps across a range of realistic scanner configurations and patient models. In this study, computational tools were developed for modeling CT scanners, including a bowtie filter, overrange collimation, and tube current modulation. The LBTE solver requires discretization in the spatial, angular, and spectral dimensions, which may affect the accuracy of scanner modeling. To investigate these effects, this study evaluated the LBTE dose accuracy for different discretization parameters, scanner configurations, and patient models (male, female, adults, pediatric). The method used to validate the LBTE dose maps was the Monte Carlo code Geant4, which provided ground truth dose maps. LBTE simulations were implemented on a GeForce GTX 1080 graphic unit, while Geant4 was implemented on a distributed cluster of CPUs. The agreement between Geant4 and the LBTE solver quantifies the accuracy of the LBTE, which was similar across the different protocols and phantoms. The results suggest that 18 views per rotation provides sufficient accuracy, as no significant improvement in the accuracy was observed by increasing the number of projection views. Considering this discretization, the LBTE solver average simulation time was approximately 30s. However, in the LBTE solver the phantom model was implemented with a lower voxel resolution with respect to Geant4, as it is limited by the memory of the GPU. Despite this discretization, the results showed a good agreement between the LBTE and Geant4, with root mean square error of the dose in organs of approximately 3.5% for most of the studied configurations. The LBTE solver is proposed as an alternative to Monte Carlo for patient-specific organ dose estimation. This study demonstrated accurate organ dose estimates for the rapid LBTE solver when considering realistic aspects of CT scanners and a range of phantom models. Future plans will combine the LBTE framework with deep learning autosegmentation algorithms to provide near real-time patient-specific organ dose estimation.

A Preliminary Simulation Study of Dose-Guided Adaptive Radiotherapy Based on Halcyon MV Cone-Beam CT Images With Retrospective Data From a Phase II Clinical Trial.

Background and purpose: To evaluate the feasibility of dose-guided adaptive radiotherapy (ART) based on deformable image registration (DIR) using fractional megavoltage cone-beam CT (MVCBCT) images from Halcyon system that uses identical beams for treatment and imaging and to retrospectively investigate the influence of anatomic changes on target coverage and organ-at-risk (OAR) sparing across various tumor sites.Materials and Methods: Four hundred twenty-two MVCBCT images from 16 patients (three head and neck, seven thoracic, three abdominal, and three pelvic cases) treated in a phase II clinical trial for Halcyon were selected. DIR between the planning CT and daily MVCBCT image was implemented by Velocity software to create pseudo CT. To investigate the accuracy of dose calculation on pseudo CT, three evaluation patients with rescanned CT and adaptive plans were selected. Dose distribution of adaptive plans calculated on pseudo CT was compared with that calculated on the rescanned planning CT on the three evaluation patients. To investigate the impact of inter-fractional anatomic changes on target dose coverage and dose to OARs of the 16 patients, fractional dose was calculated and accumulated incrementally based on deformable registration between planning CT and daily MVCBCT images.Results: Passing rates using 3 mm/3%/10% threshold local gamma analysis were 93.04, 96.00, and 91.68%, respectively, for the three evaluation patients between the reconstructed dose on pseudo CT (MVCBCT) and rescanned CT, where accumulated dose deviations of over 97% voxels were smaller than 0.5 Gy. Planning target volume (PTV) D95% and D90% (the minimum dose received by at least 95/90% of the volume) of the accumulated dose could be as low as 93.8 and 94.5% of the planned dose, respectively. OAR overdose of various degrees were observed in the 16 patients relative to the planned dose. In most cases, OARs' dose volume histogram (DVH) lines of accumulated and planned dose were very close to each other if not overlapping. Among cases with visible deviations, the differences were bilateral without apparent patterns specific to tumor sites or organs.Conclusion: As a confidence building measure, this simulation study suggested the possibility of ART for Halcyon based on DIR between planning CT and MVCBCT. Preliminary clinical data suggested the benefit of patient-specific dose reconstruction and ART to avoid unacceptable target underdosage and OAR overdosage.

PATIENT-SPECIFIC ORGAN DOSES FROM PEDIATRIC HEAD CT EXAMINATIONS.

The aim of this work was to estimate patient's organ absorbed doses from pediatric helical head computed tomography (CT) examinations using the Size-Specific Dose Estimate (SSDE) methodology and to determine organ dose to SSDE conversion coefficients for clinical routine. Patient-specific organ and tissue absorbed doses from 139 Head CT scans performed in pediatric patients from 0 to 15years old in a Public Hospital in Tunja, Colombia were estimated. The calculations were made through Monte Carlo simulations, based on patient-specific information, dosimetric CT quantities (CTDIvol, DLP) and age-specific computational human phantoms matched to patients on the basis of gender and size. SSDE showed to be a good quantity for estimate patient-specific organ doses from pediatric head CT examinations when appropriate phantom's attenuation-based size metrics are chosen to match for any patient size. Strong correlations between absorbed dose and SSDE were found for skin (R2=0.99), brain (R2=0.98) and eyes (R2=0.97), respectively. Besides, a good correlation between SSDE and absorbed dose to the red bone marrow (tissue extended outside the scan coverage) was observed (R2=0.94). SSDE-to-organ-dose conversion coefficients obtained in this study provide a practical way to estimate patient-specific organ head CT doses.

Patient-specific anatomical models for radioiodine dosimetry in treatment of hyperthyroidism: is it necessary?

To investigate the necessity of patient-specific dosimetry calculations using individualized models for hyperthyroid patients treated with radioactive iodine (RAI). This treatment modality was considered to be safe and effective; however, a recent publication indicated associations between greater organ-absorbed doses of RAI and risk of cancer death. Ten patient-specific models which ranged in size were used (from 152.5 to 184cm in height and from 44 to 88kg in mass). The time-integrated activity coefficients (TIAC) were evaluated from the 2017 Leggett's model assuming 24h radioactive iodine uptakes (RAIU) of 30, 50, 70, and 90% and two intake routes for normal uptake (ingestion and injection). A set of 131 I S factors (mGy MBq-1 h-1 ) from the patient-specific phantoms including 12 source regions were provided in this study. These S factors were used together with the new TIACs to present dose coefficients. The MC-based patient-specific S factors were compared with the ICRP standard data and the variation ranges (%) of (-65, +210) and (-57, +193) were reported for self and cross S factors, respectively. However, for self S factors, those intervals were reduced to (-8.3, +4.6) when mass correction was applied. Moreover, variations on organ dose coefficients were evaluated and the thyroid contributions were also assessed for 24h RAIU of 30, 50, 70, and 90%. Considering that the thyroid contribution to adjacent normal organs is high and the variations on cross dose coefficients are also considerable, variations (%) on normal organ doses were estimated to be up to (-63, +132), with a planned thyroid absorbed dose of 150Gy. Given the large variations on organ doses, the standard data are not an appropriate substitute for patient-specific data. Particularly, when accurate patient-specific dose estimation is a serious concern in RAI treatment (RAIT) for nuclear medicine practitioners. However, acquiring computed tomography (CT) images for patient-specific modeling will impose additional radiation dose to patients. It was concluded that CT imaging limited to the region from skull base to mid thorax (i.e., for organs with RAIT doses of >~50mGy with a dose of 150Gy prescribed to the thyroid) may be suggested and is clinically relevant because the normal organ dose increments are not greater than 10%.

Point dose verification of Cranial Stereotactic Radiosurgery using micro Ionization Chamber and EBT3 film for 6MV FF and FFF beams in Varian TrueBeam® LINAC

Abstract Introduction: Achieving high positional and dosimetric accuracy in small fields is very challenging due to the imbalance of charged particle equilibrium (CPE), occlusion of the primary radiation source, and overlapping penumbra regions. These factors make the choice of the detector for Stereotactic Radiosurgery (SRS) patient-specific quality assurance (PSQA) difficult. The aim of the study is to compare the suitability of EBT3 Gafchromic film against CC01 pinpoint chamber for the purpose of SRS and stereotactic Radiotherapy (SRT) dose verification. Material and Method: EBT3 Gafchromic film was calibrated against Treatment Planning System (TPS) doses (1 Gy – 35 Gy). CC01 pinpoint chamber and EBT3 film was used to verify Patient-Specific point doses of 21 intracranial lesions each planned with Static, Dynamic Conformal Arc (DCA), and Volumetric Arc Therapy (VMAT) using Varian TrueBeam Accelerator 6MV Flattening Filter (FF) and 6MV Flattening Filter Free (FFF) beams. The lesion sizes varied from 0.4 cc to 2.9 cc. The lesions were categorized into &lt;1cc, 1cc-2cc and 2cc-3cc. Results: High variations in measured doses from TPS calculated dose were observed with small lesion volumes irrespective of the dosimeter. As the sizes decreased high uncertainty was observed in ion chamber results. CC01 was observed under-responding to film in small lesion sizes (&lt;1cc), where nearly 50% of results under-responded in comparison with Film results. Film results were more or less consistent for static and DCA plans. Static and DCA plans were consistent passing more than 73% of the plans of the smallest lesion size category. VMAT showed very poor PSQA agreement for all three volumes (32.1% for &lt;1cc, 14.3% for 2cc-3cc and 39.3% for 2cc-3cc). No significant difference was observed between 6MVFF and 6MVFFF beams from the chi-squared test. Conclusion: EBT3 Film was observed to be a more suitable detector for small lesion sizes less than 1cc, compared to CC01. As the volume increases, the response of CC01 and EBT3 film have no significant difference in performing PSQA for intracranial SRS/SRT. VMAT techniques for intra cranial SRS shows deviation from TPS planned dose for both EBT3 film and CC01 and should not be preferred choice of verification tools.

Whole-body voxel-based internal dosimetry using deep learning

PurposeIn the era of precision medicine, patient-specific dose calculation using Monte Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of radiation hazards and correlation with patient outcome. Hence, we propose a novel method to perform whole-body personalized organ-level dosimetry taking into account the heterogeneity of activity distribution, non-uniformity of surrounding medium, and patient-specific anatomy using deep learning algorithms.MethodsWe extended the voxel-scale MIRD approach from single S-value kernel to specific S-value kernels corresponding to patient-specific anatomy to construct 3D dose maps using hybrid emission/transmission image sets. In this context, we employed a Deep Neural Network (DNN) to predict the distribution of deposited energy, representing specific S-values, from a single source in the center of a 3D kernel composed of human body geometry. The training dataset consists of density maps obtained from CT images and the reference voxelwise S-values generated using Monte Carlo simulations. Accordingly, specific S-value kernels are inferred from the trained model and whole-body dose maps constructed in a manner analogous to the voxel-based MIRD formalism, i.e., convolving specific voxel S-values with the activity map. The dose map predicted using the DNN was compared with the reference generated using MC simulations and two MIRD-based methods, including Single and Multiple S-Values (SSV and MSV) and Olinda/EXM software package.ResultsThe predicted specific voxel S-value kernels exhibited good agreement with the MC-based kernels serving as reference with a mean relative absolute error (MRAE) of 4.5 ± 1.8 (%). Bland and Altman analysis showed the lowest dose bias (2.6%) and smallest variance (CI: − 6.6, + 1.3) for DNN. The MRAE of estimated absorbed dose between DNN, MSV, and SSV with respect to the MC simulation reference were 2.6%, 3%, and 49%, respectively. In organ-level dosimetry, the MRAE between the proposed method and MSV, SSV, and Olinda/EXM were 5.1%, 21.8%, and 23.5%, respectively.ConclusionThe proposed DNN-based WB internal dosimetry exhibited comparable performance to the direct Monte Carlo approach while overcoming the limitations of conventional dosimetry techniques in nuclear medicine.

Feasibility study of patient-specific dose verification in proton therapy utilizing positron emission tomography (PET) and generative adversarial network (GAN).

Online dose verification based on proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between dose and the activity distributions, a machine learning-based approach was developed to establish their relationship. Simulations were carried out using a pencil beam scanning system and a computed tomography (CT) image-based phantom. A DiscoGAN model was developed to perform dose verification for both central and off-center lines. Besides the activity as input, HU information from CT images and stopping power (SP) prior were incorporated as auxiliary features for the model. The performance was quantitatively studied in terms of mean absolute error (MAE) and mean relative error (MRE), under different signal-to-noise ratios (SNRs). In addition to a dataset comprising monoenergetic beams, two additional datasets were generated to evaluate the model's generalization capability: five reconstructed PET images based on an in-beam PET system and a dataset comprising spread-out Bragg peaks (SOBPs). The feasibility of dose verification was successfully demonstrated for all three datasets. For the monoenergetic case (i.e., raw activity of positron emitters), the MRE is found to be <1% for the central lines and 5% for the off-center lines, respectively. The range uncertainty is found to be less than 1mm. The prediction based on five PET images, which take into account the detection of 511-keV photons and image reconstruction, yields slightly inferior performance. For the SOBP case, the MRE of the center lines is found to be <3% and the range uncertainty is <1mm. The inclusion of anatomical information (HU and SP) improves both accuracy and generalization of the DiscoGAN model. The combination of proton-induced positron emitters, in-beam PET, and machine learning may become a useful tool allowing for patient-specific online dose verification in proton therapy.

Numerical simulation of the effect of inhalation parameters, gender, age and disease severity on the lung deposition of dry powder aerosol drugs emitted by Turbuhaler®, Breezhaler® and Genuair® in COPD patients

The effect of breathing parameters on the airway deposition of the inhaled aerosols with known size was intensively studied in the literature. However, in the case of dry powder aerosol drugs both the quantity and quality of the particles emitted by the inhaler and inhaled by the patients is a complex function of the patient's breathing parameters, which in turn depend also on the disease severity and current status of the patient. The aim of this study was to evaluate the impact of breathing parameters, gender, age, symptoms and exacerbation history related disease severity (GOLD groups) of chronic obstructive pulmonary disease (COPD) patients on the lung dose of four different drugs emitted by three DPIs (dry powder inhalers). Breathing profiles of 47 COPD patients were recorded while they inhaled through Turbuhaler®, Breezhaler® and Genuair® inhalers. Patient specific emitted doses and particle size distributions were determined for Symbicort® Turbuhaler®, Onbrez® Breezhaler®, Seebri® Breezhaler® and Bretaris® Genuair® aerosol drugs. Airway deposition was quantified by a validated whole respiratory tract particle deposition model. Correlation analysis of the lung doses with breathing parameters through the devices and with standard spirometric parameters was performed. The effects of gender, age and degree of disease severity (GOLD groups) on the lung doses were also studied by statistical analysis. Mean values and distributions of the deposited lung doses proved to be both drug and device specific, yielding 24.2 (±7.8), 22.6 (±3.6), 34.2 (±4.8) and 23.9 (±5.4) % values for Symbicort®, Onbrez®, Seebri® and Bretaris®, respectively. Drugs with flow rate sensitive emitted dose and emitted particle size distribution exhibited higher intersubject variability of the lung doses. The degree of correlation of lung doses with breathing parameters through the devices was also drug specific. Correlation with flow rate was the strongest for Symbicort® Turbuhaler®. Longer breath-hold increased the lung dose of all the studied drugs. Correlations of lung dose with standard spirometric parameters was generally weaker than its correlation with the parameters measured when inhaling through the devices. Men had higher lung deposition than women, younger patients had higher deposition than older ones and patients with less severe disease higher doses than those with more severe COPD, but the differences were statistically significant only upon gender and only in case of Symbicort® and Seebri®. Patients with better inhalation parameters are likely to have higher lung deposition when inhaling a drug with emitted dose and particle size distribution sensitive to the inhalation flow rate. At the same time, patients with lower lung capacity show better deposition results when inhaling from inhalers emitting a more constant amount of drug and particles with more stable aerodynamic characteristics. A more powerful inhalation significantly increases the lung dose for the drug emitted by Turbuhaler®, while long breath-hold is likely to yield significantly higher deposition for drugs emitted by Breezhaler® and Genuair®. Lung doses of two different drugs dispensed in the same inhaler can be significantly different.