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BACKGROUND: Bolus materials have been used for decades in radiotherapy. Most frequently, these materials are utilized to bring dose closer to the skin surface to cover superficial targets optimally. While cavity filling, such as nasal cavities, is desirable, traditional commercial bolus is lacking, requiring other solutions. Recently, investigators have worked on utilizing 3D printing technology, including commercially available solutions, which can overcome some challenges with traditional bolus. PURPOSE: To utilize failure modes and effects analysis (FMEA) to successfully implement a comprehensive 3D printed bolus solution to replace commercial bolus in our clinic using a series of open-source (or free) software products. METHODS: 3D printed molds for bespoke bolus were created by exporting the DICOM structures of the bolus designed in the treatment planning system and manipulated to create a multipart mold for 3D printing. A silicone (Ecoflex 00-30) mixture is poured into the mold and cured to form the bolus. Molds for sheet bolus of five thicknesses were also created. A comprehensive FMEA was performed to guide workflow adjustments and QA steps. RESULTS: The process map identified 39 and 30 distinct steps for the bespoke and flat sheet bolus workflows, respectively. The corresponding FMEA highlighted 119 and 86 failure modes, with 69 shared between the processes. Misunderstanding of plan intent was a potential cause for most of the highest-scoring failure modes, indicating that physics and dosimetry involvement early in the process is paramount. CONCLUSION: FMEA informed the design and implementation of QA steps to guarantee a safe and high-quality comprehensive implementation of silicone bolus from 3D printed molds. This approach allows for greater adaptability not afforded by traditional bolus, as well as potential dissemination to other clinics due to the open-source nature of the workflow.
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PURPOSE: To assess the practicality of employing a commercial knowledge-based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone-beam computed tomography (iCBCT) datasets. METHODS AND MATERIALS: Intact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose-volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan-generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow. RESULTS: Model testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09 ± 02:06 (intact) and 07:12 ± 01:04 (bed). CONCLUSION: This study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach.
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Structural, electrical, and thermal properties of CdSnAs2, with analyses from temperature-dependent transport properties over a large temperature range, are reported. Phase-pure microcrystalline powders were synthesized that were subsequently densified to a high-density homogeneous polycrystalline specimen for this study. Temperature-dependent transport indicates n-type semiconducting behavior with a very high and nearly temperature independent mobility over the entire measured temperature range, attributed to the very small electron effective mass of this material. The Debye model was successfully applied to model the thermal conductivity and specific heat. This work contributes to the fundamental understanding of this material, providing further insight and allowing for investigations into altering this and related physical properties of these materials for technological applications.
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We report on the structural, chemical, electrical, and thermal properties of n-type polycrystalline NbFeSb synthesized by induction melting of the elements. Although several studies on p-type conduction of this half-Heusler composition have recently been reported, including reports of relatively high thermoelectric properties, very little has been reported on the transport properties of n-type compositions. We combine transport property investigations together with short- and long-range structural data obtained by Mössbauer spectroscopy of iron-57 and antimony-121 and by neutron total scattering, as well as first-principles calculations. In our investigation, we show that n-type conduction can occur from antiphase boundaries in this material. This work is intended to provide a greater understanding of the fundamental properties of NbFeSb as this material continues to be of interest for potential thermoelectric applications.
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Single crystals of clathrate-I Ba8Cu16As30 have been synthesized and their structure and electronic properties determined using synchrotron-based X-ray diffraction and first-principles calculations. The structure is confirmed to be Pm3Ì n (No. 223), with lattice parameter a = 10.4563(3) Å, and defined by a tetrahedrally bonded network of As and Cu that forms two distinct coordination polyhedra, with Ba residing inside these polyhedra. All crystallographic positions are fully occupied with no vacancies or superstructure with the Cu atoms, while occupying all framework sites in the network, exhibiting a preference for the 6c site. Agreement between the experimental and theoretically predicted structures was achieved after accounting for spin-orbit coupling. Our calculated Fermi surface, electron localization, and charge transfer, as well as a comparison with the results for elemental As46, provide insight into the fundamental properties of this clathrate-I material.
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Materials with very low thermal conductivities continue to be of interest for a variety of applications. We synthesized CuSbS2 employing a mechanical alloying technique in order to investigate its physical properties. The trigonal pyramid arrangement of the S atoms around the Sb atoms allows for lone-pair electron formation that results in very low thermal conductivity. In addition to thermal properties, the structural, electrical, and optical properties, as well as compositional stability measurements, are also discussed. CuSbS1.8Te0.2 was similarly synthesized and characterized in order to compare its structural and transport properties with that of CuSbS2, in addition to investigating the effect of Te alloying on these properties.
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PURPOSE: The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning auto-segmentation (DLAS) tool on enhanced iterative cone beam computed tomography (iCBCT) acquisitions for intact prostate and prostate bed treatments. METHODS AND MATERIALS: DLAS models were trained using 116 iCBCT data sets with manually delineated organs at risk (bladder, femoral heads, and rectum) and target volumes (intact prostate and prostate bed) adhering to institution-specific contouring guidelines. An additional 25 intact prostate and prostate bed iCBCT data sets were used for model testing. Segmentation accuracy relative to a reference structure set was quantified using various geometric comparison metrics and qualitatively evaluated by trained physicists and physicians. These results were compared with those obtained for an additional DLAS-based model trained on planning computed tomography (pCT) data sets and for a deformable image registration (DIR)-based automatic contour propagation method. RESULTS: In most instances, statistically significant differences in the Dice similarity coefficient (DSC), 95% directed Hausdorff distance, and mean surface distance metrics were observed between the models, as the iCBCT-trained DLAS model outperformed the pCT-trained DLAS model and DIR-based method for all organs at risk and the intact prostate target volume. Mean DSC values for the proposed method were ≥0.90 for these volumes of interest. The iCBCT-trained DLAS model demonstrated a relatively suboptimal performance for the prostate bed segmentation, as the mean DSC value was <0.75 for this target contour. Overall, 90% of bladder, 93% of femoral head, 67% of rectum, and 92% of intact prostate contours generated by the proposed method were deemed clinically acceptable based on qualitative scoring, and approximately 63% of prostate bed contours required moderate or major manual editing to adhere to institutional contouring guidelines. CONCLUSIONS: The proposed method presents the potential for improved segmentation accuracy and efficiency compared with the DIR-based automatic contour propagation method as commonly applied in CBCT-based dose evaluation and calculation studies.
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Tomografia Computadorizada de Feixe Cônico , Aprendizado Profundo , Neoplasias da Próstata , Humanos , Masculino , Tomografia Computadorizada de Feixe Cônico/métodos , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/radioterapia , Pelve/diagnóstico por imagem , Aceleradores de Partículas , Planejamento da Radioterapia Assistida por Computador/métodos , Órgãos em RiscoRESUMO
PURPOSE: To assess the clinical acceptability of a commercial deep-learning-based auto-segmentation (DLAS) prostate model that was retrained using institutional data for delineation of the clinical target volume (CTV) and organs-at-risk (OARs) for postprostatectomy patients, accounting for clinical and imaging protocol variations. METHODS AND MATERIALS: CTV and OARs of 109 prostate-bed patients were used to evaluate the performance of the vendor-trained model and custom retrained DLAS models using different training quantities. Two new models for OAR structures were retrained (n = 30, 60 data sets), while separate models were trained for a new CTV structure (n = 30, 60, 90 data sets), with the remaining data sets used for testing (n = 49, 19). The dice similarity coefficient (DSC), Hausdorff distance, and mean surface distance were evaluated. Six radiation oncologists performed a qualitative evaluation scoring both preference and clinical utility for blinded structure sets. Physician consensus data sets identified from the qualitative evaluation were used toward a separate CTV model. RESULTS: Both the 30- and 60-case retrained OAR models had median DSC values between 0.91 to 0.97, improving significantly over the vendor-trained model for all OARs except the penile bulb. The brand new 60-case CTV model had a median DSC of 0.70 improving significantly over the 30-case model. DLAS (60-case model) and manual contours were blinded and evaluated by physicians with contours deemed acceptable or precise for 87% and 94% of cases for DLAS and manual delineations, respectively. DLAS-generated CTVs were scored precise or acceptable in 54% of cases, compared with the manual delineation value of 73%. The 30-case physician consensus CTV model did not show a significant difference compared with the randomly selected models. CONCLUSIONS: Custom retraining using institutional data leads to performance improvement in the clinical utility and accuracy of DLAS for postprostatectomy patients. A small number of data sets are sufficient for building an institutional site-specific DLAS OAR model, as well as for training new structures. Data indicates the workload for identifying training data sets could be shared among groups for the male pelvic region, making it accessible to clinics of all sizes.
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Inteligência Artificial , Aprendizado Profundo , Humanos , Masculino , Planejamento da Radioterapia Assistida por Computador/métodos , Órgãos em Risco , ProstatectomiaRESUMO
BACKGROUND: Cone-beam computed tomography (CBCT) allows for patient setup and positioning, and potentially dose verification or adaptive replanning prior to each treatment delivery. Poor CBCT image quality due to scatter artifacts and patient motion has been a major limiting factor. A new image reconstruction algorithm was recently clinically implemented for improving image quality through iterative reconstruction (iCBCT). PURPOSE: This study aims to characterize iCBCT image quality, establish image value (HU)-to-relative electron density (RED) calibration curves for dose calculation, and assess the dosimetric accuracy for different anatomical sites. MATERIAL AND METHODS: Both conventional CBCT and iCBCT scans were acquired from a Varian TrueBeam On-Board Imager system. A Catphan 604 phantom was scanned to compare image quality between the traditional Feldkamp-Davis-Kress (FDK) and novel iterative reconstruction techniques. Computerized Imaging Reference Systems (CIRS) electron density phantom was used to construct site-specific HU-RED curves corresponding to various scan settings. The CIRS Dynamic Thorax phantom, Rando pelvis phantom, and BrainLab head phantom were used for assessing dosimetric accuracy calculated on iCBCT images, compared to that on traditional FDK-based CBCT images. All phantoms were scanned on a computed tomography (CT) to obtain baseline HU values for comparison. RESULTS: Test results obtained from Catphan showed statistically significant improvement with iCBCT, compared to FDK CBCT. Average HU differences from the baseline CT values were improved to within ±30 HU for iCBCT, compared to FDK CBCT for phantom studies. Dose calculated on iCBCT for both phantoms and patient cases directly using baseline HU-RED calibration from CT showed 0.5%-2.0% accuracy from the baseline dose calculated on CT, which is comparable to doses calculated using site-specific HU-RED calibration curves. CONCLUSION: iCBCT provides improved image quality, improved HU accuracy compared to CT baseline, and has potential to provide online dose verification as part of the adaptive radiotherapy workflow directly using the baseline HU-RED calibration curve from CT.
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Tomografia Computadorizada de Feixe Cônico , Planejamento da Radioterapia Assistida por Computador , Humanos , Planejamento da Radioterapia Assistida por Computador/métodos , Tomografia Computadorizada de Feixe Cônico/métodos , Tomografia Computadorizada por Raios X , Radiometria , Pelve , Imagens de Fantasmas , Processamento de Imagem Assistida por Computador/métodos , AlgoritmosRESUMO
Purpose: Post-operative prostate cancer patients are treated with full bladder instruction and the use of an endorectal balloon (ERB). We reassessed the efficacy of this practice based on daily image guidance and dose delivery using high-quality iterative reconstructed cone-beam CT (iCBCT). Methods: Fractional dose delivery was calculated on daily iCBCT for 314 fractions from 14 post-operative prostate patients (8 with and 6 without ERB) treated with volumetric modulated radiotherapy (VMAT). All patients were positioned using novel iCBCT during image guidance. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. The dose-volume parameters of the contoured organs at risk (OAR) and CTV coverage were assessed for the clinical impact of daily bladder volume variations and the use of ERB. Minimum bladder volume was studied, and a straightforward bladder instruction was explored for easy clinical adoption. Results: A "minimum bladder" contour, the overlap between the original bladder contour and a 15 mm anterior and superior expansion from prostate bed PTV, was confirmed to be effective in identifying cases that might fail a bladder constraint of V65% <60%. The average difference between the maximum and minimum bladder volumes for each patient was 277.1 mL. The daily bladder volumes varied from 62.4 to 590.7 mL and ranged from 29 to 286% of the corresponding planning bladder volume. The bladder constraint of V65% <60% was met in almost all fractions (98%). CTVs (D90%, D95%, and D98%) remained well-covered regardless of the absolute bladder volume daily variation or the presence of the endorectal balloon. Patients with an endorectal balloon showed smaller variation but a higher average maximum rectal wall dose (D0.03mL: 104.3% of the prescription) compared to patients without (103.3%). Conclusions: A "minimum bladder" contour was determined that can be easily generated and followed to ensure sufficient bladder sparing. Further analysis and validation are needed to confirm the utility of the minimal bladder contour. Accurate dose delivery can be achieved for prostate bed target coverage and OAR sparing with or without the use of ERB.
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PURPOSE: A successful proton beam therapy (PBT) center relies heavily on the proper function and maintenance of a proton beam therapy machine. However, when a PBT machine is non-operational, a proton facility is hindered with delays that can potentially lead to inferior treatment outcome due to treatment interruption. This article reports a viable solution for a photon back-up plan in a proton down event. METHODS AND MATERIALS: The implementation of a workflow for which proton plans are converted to photon plans so that patients can be treated using photons has been a successful strategy to reduce delays and mitigate its effect on patient care. This workflow was established through collaboration of physicians, physicists, dosimetrists, therapists, nurses, and schedulers. RESULTS AND CONCLUSIONS: A tiered system established by disease site, number of fractions, and individualized circumstances is used to prioritize patients. Proton-photon backup planning strategy and physics check details were described. This article provides an overview of workflow of conversion of PBT to photon when the PBT machine is down. Specific needs of patients undergoing proton beam therapy are addressed.
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Terapia com Prótons , Humanos , Fótons/uso terapêutico , Terapia com Prótons/métodos , Prótons , Planejamento da Radioterapia Assistida por Computador/métodos , Fluxo de TrabalhoRESUMO
The synthesis, electronic structure and temperature dependent transport properties of polycrystalline Cu1+xMn2-xInTe4 (x = 0, 0.2, 0.3) are reported for the first time. These quaternary chalcogenides were synthesized by direct reaction of the elements, followed by solid state annealing and hot press densification. The thermal conductivity is low for all specimens and intrinsic to the material system. Furthermore, the off-stoichiometry specimens illustrate the sensitivity of the transport properties to stoichiometry, with a greater than two-orders-of magnitude increase in carrier concentration with increased Cu content. First principles calculations of the electronic structure are also reported, and are in agreement with the experimental data. This fundamental investigation shows the potential towards further optimization of the electrical properties that, in addition to the intrinsically low thermal conductivity, provides a basis for further research into the viability of this material system for potential energy-related applications.
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Thermoelectricity allows direct conversion between heat and electricity, providing alternatives for green energy technologies. Despite these advantages, for most materials the energy conversion efficiency is limited by the tendency for the electrical and thermal conductivity to be proportional to each other and the Seebeck coefficient to be small. Here we report counter examples, where the heavy fermion compounds YbTM 2Zn20 (TM = Co, Rh, Ir) exhibit enhanced thermoelectric performance including a large power factor (PF = 74 µW/cm-K2; TM = Ir) and a high figure of merit (ZT = 0.07; TM = Ir) at 35 K. The combination of the strongly hybridized electronic state originating from the Yb f-electrons and the novel structural features (large unit cell and possible soft phonon modes) leads to high power factors and small thermal conductivity values. This demonstrates that with further optimization these systems could provide a platform for the next generation of low temperature thermoelectric materials.
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Temperature-dependent transport properties of the recently discovered layered bismuth-rich tellurobromides BinTeBr (n = 2, 3) are investigated for the first time. Dense homogeneous polycrystalline specimens prepared for different electrical and thermal measurements were synthesized by a ball milling-based process. While the calculated electronic structure classifies Bi2TeBr as a semimetal with a small electron pocket, its transport properties demonstrate a semiconductorlike behavior. Additional bismuth bilayers in the Bi3TeBr crystal structure strengthens the interlayer chemical bonding thus leading to metallic conduction. The thermal conductivity of the semiconducting compositions is low, and the electrical properties are sensitive to doping with a factor of four reduction in resistivity observed at room temperature for only 3% Pb doping. Investigation of the thermoelectric properties suggests that optimization for thermoelectrics may depend on particular elemental substitution. The results presented are intended to expand on the research into tellurohalides in order to further advance the fundamental investigation of these materials, as well as investigate their potential for thermoelectric applications.