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1.
Acta Oncol ; 57(8): 1017-1024, 2018 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-29350579

RESUMO

BACKGROUND: Cone beam computed tomography (CBCT) for radiotherapy image guidance suffers from respiratory motion artifacts. This limits soft tissue visualization and localization accuracy, particularly in abdominal sites. We report on a prospective study of respiratory motion-corrected (RMC)-CBCT to evaluate its efficacy in localizing abdominal organs and improving soft tissue visibility at end expiration. MATERIAL AND METHODS: In an IRB approved study, 11 patients with gastroesophageal junction (GEJ) cancer and five with pancreatic cancer underwent a respiration-correlated CT (4DCT), a respiration-gated CBCT (G-CBCT) near end expiration and a one-minute free-breathing CBCT scan on a single treatment day. Respiration was recorded with an external monitor. An RMC-CBCT and an uncorrected CBCT (NC-CBCT) were computed from the free-breathing scan, based on a respiratory model of deformations derived from the 4DCT. Localization discrepancy was computed as the 3D displacement of the GEJ region (GEJ patients), or gross tumor volume (GTV) and kidneys (pancreas patients) in the NC-CBCT and RMC-CBCT relative to their positions in the G-CBCT. Similarity of soft-tissue features was measured using a normalized cross correlation (NCC) function. RESULTS: Localization discrepancy from the end-expiration G-CBCT was reduced for RMC-CBCT compared to NC-CBCT in eight of eleven GEJ cases (mean ± standard deviation, respectively, 0.21 ± 0.11 and 0.43 ± 0.28 cm), in all five pancreatic GTVs (0.26 ± 0.21 and 0.42 ± 0.29 cm) and all ten kidneys (0.19 ± 0.13 and 0.51 ± 0.25 cm). Soft-tissue feature similarity around GEJ was higher with RMC-CBCT in nine of eleven cases (NCC =0.48 ± 0.20 and 0.43 ± 0.21), and eight of ten kidneys (0.44 ± 0.16 and 0.40 ± 0.17). CONCLUSIONS: In a prospective study of motion-corrected CBCT in GEJ and pancreas, RMC-CBCT yielded improved organ visibility and localization accuracy for gated treatment at end expiration in the majority of cases.


Assuntos
Tomografia Computadorizada de Feixe Cônico/métodos , Neoplasias Pancreáticas/radioterapia , Radioterapia Guiada por Imagem/métodos , Neoplasias Gástricas/radioterapia , Adulto , Idoso , Neoplasias Esofágicas/diagnóstico por imagem , Neoplasias Esofágicas/radioterapia , Junção Esofagogástrica/diagnóstico por imagem , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Movimento (Física) , Neoplasias Pancreáticas/diagnóstico por imagem , Estudos Prospectivos , Planejamento da Radioterapia Assistida por Computador , Respiração , Neoplasias Gástricas/diagnóstico por imagem
2.
J Appl Clin Med Phys ; 19(6): 11-25, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-30338913

RESUMO

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline (MPPG) represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiation requires specific training, skills, and techniques as described in each document. As the review of the previous version of AAPM Professional Policy (PP)-17 (Scope of Practice) progressed, the writing group focused on one of the main goals: to have this document accepted by regulatory and accrediting bodies. After much discussion, it was decided that this goal would be better served through a MPPG. To further advance this goal, the text was updated to reflect the rationale and processes by which the activities in the scope of practice were identified and categorized. Lastly, the AAPM Professional Council believes that this document has benefitted from public comment which is part of the MPPG process but not the AAPM Professional Policy approval process. The following terms are used in the AAPM's MPPGs: Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.


Assuntos
Física Médica/normas , Guias de Prática Clínica como Assunto/normas , Sociedades Científicas/normas , Humanos , Doses de Radiação
3.
J Appl Clin Med Phys ; 17(2): 473-486, 2016 03 08.
Artigo em Inglês | MEDLINE | ID: mdl-27074467

RESUMO

The purpose of this study was to evaluate the accuracy and clinical feasibility of a motion monitoring method employing simultaneously acquired MV and kV images during volumetric-modulated arc therapy (VMAT). Short-arc digital tomosynthesis (SA-DTS) is used to improve the quality of the MV images that are then combined with orthogonally acquired kV images to assess 3D motion. An anthropomorphic phantom with implanted gold seeds was used to assess accuracy of the method under static, typical prostatic, and respiratory motion scenarios. Automatic registra-tion of kV images and single MV frames or MV SA-DTS reconstructed with arc lengths from 2° to 7° with the appropriate reference fiducial template images was performed using special purpose-built software. Clinical feasibility was evaluated by retrospectively analyzing images acquired over four or five sessions for each of three patients undergoing hypofractionated prostate radiotherapy. The standard deviation of the registration error in phantom using MV SA-DTS was similar to single MV images for the static and prostate motion scenarios (σ = 0.25 mm). Under respiratory motion conditions, the standard deviation of the registration error increased to 0.7mm and 1.7 mm for single MV and MV SA-DTS, respectively. Registration failures were observed with the respiratory scenario only and were due to motion-induced fiducial blurring. For the three patients studied, the mean and standard deviation of the difference between automatic registration using 4° MV SA-DTS and manual registration using single MV images results was 0.07±0.52mm. The MV SA-DTS results in patients were, on average, superior to single-frame MV by nearly 1 mm - significantly more than what was observed in phantom. The best MV SA-DTS results were observed with arc lengths of 3° to 4°. Registration failures in patients using MV SA-DTS were primarily due to blockage of the gold seeds by the MLC. The failure rate varied from 2% to 16%. Combined MV SA-DTS and kV imaging is feasible for intratreatment motion monitoring during VMAT of anatomic sites where limited motion is expected, and improves registration accuracy compared to single MV/kV frames. To create a clinically robust technique, further improvements to ensure visualization of fiducials at the desired control points without degradation of the treatment plan are needed.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Movimento (Física) , Imagens de Fantasmas , Neoplasias da Próstata/radioterapia , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia Guiada por Imagem/métodos , Radioterapia de Intensidade Modulada/métodos , Estudos de Viabilidade , Marcadores Fiduciais , Humanos , Masculino , Imagem Molecular/métodos , Dosagem Radioterapêutica , Estudos Retrospectivos , Software
4.
Med Phys ; 39(7): 4547-58, 2012 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-22830786

RESUMO

PURPOSE: Contouring a normal anatomical structure during radiation treatment planning requires significant time and effort. The authors present a fast and accurate semiautomatic contour delineation method to reduce the time and effort required of expert users. METHODS: Following an initial segmentation on one CT slice, the user marks the target organ and nontarget pixels with a few simple brush strokes. The algorithm calculates statistics from this information that, in turn, determines the parameters of an energy function containing both boundary and regional components. The method uses a conditional random field graphical model to define the energy function to be minimized for obtaining an estimated optimal segmentation, and a graph partition algorithm to efficiently solve the energy function minimization. Organ boundary statistics are estimated from the segmentation and propagated to subsequent images; regional statistics are estimated from the simple brush strokes that are either propagated or redrawn as needed on subsequent images. This greatly reduces the user input needed and speeds up segmentations. The proposed method can be further accelerated with graph-based interpolation of alternating slices in place of user-guided segmentation. CT images from phantom and patients were used to evaluate this method. The authors determined the sensitivity and specificity of organ segmentations using physician-drawn contours as ground truth, as well as the predicted-to-ground truth surface distances. Finally, three physicians evaluated the contours for subjective acceptability. Interobserver and intraobserver analysis was also performed and Bland-Altman plots were used to evaluate agreement. RESULTS: Liver and kidney segmentations in patient volumetric CT images show that boundary samples provided on a single CT slice can be reused through the entire 3D stack of images to obtain accurate segmentation. In liver, our method has better sensitivity and specificity (0.925 and 0.995) than region growing (0.897 and 0.995) and level set methods (0.912 and 0.985) as well as shorter mean predicted-to-ground truth distance (2.13 mm) compared to regional growing (4.58 mm) and level set methods (8.55 mm and 4.74 mm). Similar results are observed in kidney segmentation. Physician evaluation of ten liver cases showed that 83% of contours did not need any modification, while 6% of contours needed modifications as assessed by two or more evaluators. In interobserver and intraobserver analysis, Bland-Altman plots showed our method to have better repeatability than the manual method while the delineation time was 15% faster on average. CONCLUSIONS: Our method achieves high accuracy in liver and kidney segmentation and considerably reduces the time and labor required for contour delineation. Since it extracts purely statistical information from the samples interactively specified by expert users, the method avoids heuristic assumptions commonly used by other methods. In addition, the method can be expanded to 3D directly without modification because the underlying graphical framework and graph partition optimization method fit naturally with the image grid structure.


Assuntos
Inteligência Artificial , Reconhecimento Automatizado de Padrão/métodos , Intensificação de Imagem Radiográfica/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Interface Usuário-Computador , Interpretação Estatística de Dados , Humanos , Imagens de Fantasmas , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X/instrumentação
5.
Med Phys ; 39(6): 3070-9, 2012 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-22755692

RESUMO

PURPOSE: Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. METHODS: Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. RESULTS: Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. CONCLUSIONS: Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data.


Assuntos
Artefatos , Processamento de Imagem Assistida por Computador/métodos , Modelos Biológicos , Movimento , Respiração , Tomografia Computadorizada por Raios X/métodos , Humanos
6.
INFORMS J Appl Anal ; 52(1): 69-89, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35847768

RESUMO

Each year, approximately 18 million new cancer cases are diagnosed worldwide, and about half must be treated with radiotherapy. A successful treatment requires treatment planning with the customization of penetrating radiation beams to sterilize cancerous cells without harming nearby normal organs and tissues. This process currently involves extensive manual tuning of parameters by an expert planner, making it a time-consuming and labor-intensive process, with quality and immediacy of critical care dependent on the planner's expertise. To improve the speed, quality, and availability of this highly specialized care, Memorial Sloan Kettering Cancer Center developed and applied advanced optimization tools to this problem (e.g., using hierarchical constrained optimization, convex approximations, and Lagrangian methods). This resulted in both a greatly improved radiotherapy treatment planning process and the generation of reliable and consistent high-quality plans that reflect clinical priorities. These improved techniques have been the foundation of high-quality treatments and have positively impacted over 4,000 patients to date, including numerous patients in severe pain and in urgent need of treatment who might have otherwise required longer hospital stays or undergone unnecessary surgery to control the progression of their disease. We expect that the wide distribution of the system we developed will ultimately impact patient care more broadly, including in resource-constrained countries.

7.
Med Phys ; 37(6): 2901-9, 2010 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-20632601

RESUMO

PURPOSE: Respiratory motion adversely affects CBCT image quality and limits its localization accuracy for image-guided radiation treatment. Motion correction methods in CBCT have focused on the thorax because of its higher soft tissue contrast, whereas low-contrast tissue in abdomen remains a challenge. The authors report on a method to correct respiration-induced motion artifacts in 1 min CBCT scans that is applicable in both thorax and abdomen, using a motion model adapted to the patient from a respiration-correlated image set. METHODS: Model adaptation consists of nonrigid image registration that maps each image to a reference image in the respiration-correlated set, followed by a principal component analysis to reduce errors in the nonrigid registration. The model parametrizes the deformation field in terms of observed surrogate (diaphragm or implanted marker) position and motion (inhalation or exhalation) between the images. In the thorax, the model is obtained from the same CBCT images that are to be motion-corrected, whereas in the abdomen, the model uses respiration-correlated CT (RCCT) images acquired prior to the treatment session. The CBCT acquisition is a single 360 degrees rotation lasting 1 min, while simultaneously recording patient breathing. The approximately 600 projection images are sorted into six (in thorax) or ten (in abdomen) subsets and reconstructed to obtain a set of low-quality respiration-correlated RC-CBCT images. Application of the motion model deforms each of the RC-CBCT images to a chosen reference image in the set; combining all images yields a single high-quality CBCT image with reduced blurring and motion artifacts. Repeated application of the model with different reference images produces a series of motion-corrected CBCT images over the respiration cycle, for determining the motion extent of the tumor and nearby organs at risk. The authors also investigate a simpler correction method, which does not use PCA and correlates motion state with respiration phase, thus assuming repeatable breathing patterns. Comparison of contrast-to-noise ratios of pixel intensities within anatomical structures relative to surrounding background tissue provides a quantitative assessment of relative organ visibility. RESULTS: Evaluation in lung phantom, two patient cases in thorax and two in upper abdomen, shows that blurring and streaking artifacts are visibly reduced with motion correction. The boundaries of tumors in the thorax, liver, and kidneys are sharper and more discernible. Repeat application of the method in one thorax case, with reference images chosen at end expiration and end inspiration, indicates its feasibility for observing tumor motion extent. Phase-based motion correction without PCA reduces blurring less effectively; in addition, implanted markers appear broken up, indicating inconsistencies in the phase-based correction. In structures showing 1 cm or more motion excursion, PCA-based motion correction shows the highest contrast-to-noise ratios in the cases examined. CONCLUSIONS: Motion correction of CBCT is feasible and yields observable improvement in the thorax and abdomen. The PCA-based model is an important component: First, by reducing deformation errors caused by the nonrigid registration and second, by relating deformation to surrogate position rather than phase, thus accommodating breathing pattern changes between imaging sessions. The accuracy of the method requires confirmation in further patient studies.


Assuntos
Artefatos , Tomografia Computadorizada de Feixe Cônico/métodos , Intensificação de Imagem Radiográfica/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Radiografia Abdominal/métodos , Radiografia Torácica/métodos , Mecânica Respiratória , Algoritmos , Simulação por Computador , Humanos , Modelos Biológicos , Movimento/fisiologia , Reconhecimento Automatizado de Padrão/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
8.
Med Phys ; 37(3): 1237-45, 2010 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-20384261

RESUMO

Digital tomosynthesis (DTS) with a linear accelerator-mounted imaging system provides a means of reconstructing tomographic images from radiographic projections over a limited gantry arc, thus requiring only a few seconds to acquire. Its application in the thorax, however, often results in blurred images from respiration-induced motion. This work evaluates the feasibility of respiration-correlated (RC) DTS for soft-tissue visualization and patient positioning. Image data acquired with a gantry-mounted kilovoltage imaging system while recording respiration were retrospectively analyzed from patients receiving radiotherapy for non-small-cell lung carcinoma. Projection images spanning an approximately 30 degrees gantry arc were sorted into four respiration phase bins prior to DTS reconstruction, which uses a backprojection, followed by a procedure to suppress structures above and below the reconstruction plane of interest. The DTS images were reconstructed in planes at different depths through the patient and normal to a user-selected angle close to the center of the arc. The localization accuracy of RC-DTS was assessed via a comparison with CBCT. Evaluation of RC-DTS in eight tumors shows visible reduction in image blur caused by the respiratory motion. It also allows the visualization of tumor motion extent. The best image quality is achieved at the end-exhalation phase of the respiratory motion. Comparison of RC-DTS with respiration-correlated cone-beam CT in determining tumor position, motion extent and displacement between treatment sessions shows agreement in most cases within 2-3 mm, comparable in magnitude to the intraobserver repeatability of the measurement. These results suggest the method's applicability for soft-tissue image guidance in lung, but must be confirmed with further studies in larger numbers of patients.


Assuntos
Artefatos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/radioterapia , Radioterapia Assistida por Computador/métodos , Radioterapia Conformacional/métodos , Técnicas de Imagem de Sincronização Respiratória/métodos , Tomografia Computadorizada por Raios X/métodos , Humanos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Estatística como Assunto
9.
Adv Radiat Oncol ; 5(5): 1042-1050, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33083666

RESUMO

PURPOSE: We report on the clinical performance of a fully automated approach to treatment planning based on a Pareto optimal, constrained hierarchical optimization algorithm, named Expedited Constrained Hierarchical Optimization (ECHO). METHODS AND MATERIALS: From April 2017 to October 2018, ECHO produced 640 treated plans for 523 patients who underwent stereotactic body radiation therapy (RT) for paraspinal and other metastatic tumors. A total of 182 plans were for 24 Gy in a single fraction, 387 plans were for 27 Gy in 3 fractions, and the remainder were for other prescriptions or fractionations. Of the plans, 84.5% were for paraspinal tumors, with 69, 302, and 170 in the cervical, thoracic, and lumbosacral spine, respectively. For each case, after contouring, a template plan using 9 intensity modulated RT fields based on disease site and tumor location was sent to ECHO through an application program interface plug-in from the treatment planning system. ECHO returned a plan that satisfied all critical structure hard constraints with optimal target volume coverage and the lowest achievable normal tissue doses. Upon ECHO completion, the planner received an e-mail indicating the plan was ready for review. The plan was accepted if all clinical criteria were met. Otherwise, a limited number of parameters could be adjusted for another ECHO run. RESULTS: The median planning target volume size was 84.3 cm3 (range, 6.9-633.2). The median time to produce 1 ECHO plan was 63.5 minutes (range, 11-340 minutes) and was largely dependent on the field sizes. Of the cases, 79.7% required 1 run to produce a clinically accepted plan, 13.3% required 1 additional run with minimal parameter adjustments, and 7.0% required ≥2 additional runs with significant parameter modifications. All plans met or bettered the institutional clinical criteria. CONCLUSIONS: We successfully implemented automated stereotactic body RT paraspinal and other metastatic tumors planning. ECHO produced high-quality plans, improved planning efficiency and robustness, and enabled expedited treatment planning at our clinic.

10.
J Appl Clin Med Phys ; 10(4): 132-141, 2009 Oct 07.
Artigo em Inglês | MEDLINE | ID: mdl-19918227

RESUMO

The Varian Real-time Position Management (RPM) system allows respiratory gating based on either the phase or displacement (amplitude) of the breathing waveform. A problem in clinical application is that phase-based gating, required for respiration-correlated (4D-CT) simulation, is not robust to irregular breathing patterns during treatment, and a widely used system version (1.6) does not provide an easy means to change from a phase-based gate into an equivalent displacement-based one. We report on the development and evaluation of a robust method to convert phase-gate thresholds, set by the physician, into equivalent displacement-gate thresholds to facilitate its clinical application to treatment. The software tool analyzes the respiration trace recorded during the 4D-CT simulation, and determines a relationship between displacement and phase through a functional fit. The displacement gate thresholds are determined from an average of two values of this function, corresponding to the start and end thresholds of the original phase gate. The software tool was evaluated in two ways: first, whether in-gate residual target motion and predicted treatment beam duty cycle are equivalent between displacement gating and phase gating during 4D-CT simulation (using retrospective phase recalculation); second, whether residual motion is improved with displacement gating during treatment relative to phase gating (using real-time phase calculation). Residual target motion was inferred from the respiration traces and quantified in terms of mean and standard deviation in-gate displacement measured relative to the value at the start of the recorded trace. For retrospectively-calculated breathing traces compared with real-time calculated breathing traces, we evaluate the inaccuracies of real-time phase calculation by measuring the phase gate position in each trace as well as the mean in-gate displacement and standard deviation of the displacement. Retrospectively-calculated data from ten patients were analyzed. The patient averaged in-gate mean +/- standard deviation displacement (representing residual motion) was reduced from 0.16 +/- 0.14 cm for phase gating under simulation conditions to 0.12 +/- 0.08 cm for displacement gating. Evaluation of respiration traces under treatment conditions (real-time phase calculation) showed that the average displacement gate threshold results in a lower in-gate mean and residual motion (variance) for all patients studied. The patient-averaged in-gate mean +/- standard deviation displacement was reduced from 0.26 +/- 0.18 cm for phase gating (under treatment conditions) to 0.15 +/- 0.09 cm for displacement gating. Real-time phase gating sometimes leads to gating on incorrect portions of the breathing cycle when the breathing trace is irregular. Displacement gating is less prone to such errors, as evidenced by the lower in-gate residual motion in a large majority of cases.


Assuntos
Imageamento Tridimensional/métodos , Radioterapia de Intensidade Modulada/métodos , Respiração , Técnicas de Imagem de Sincronização Respiratória , Software , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Simulação por Computador , Humanos , Estudos Prospectivos , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Estudos Retrospectivos
11.
Med Phys ; 46(7): 2944-2954, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31055858

RESUMO

PURPOSE: To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning. METHOD: The optimization algorithm is developed based on a hierarchical constrained optimization technique and is referred internally at our institution as expedited constrained hierarchical optimization (ECHO). Beamlet contributions to regions-of-interest are precomputed and captured in the influence matrix. Planning goals are of two classes: hard constraints that are strictly enforced from the first step (e.g., maximum dose to spinal cord), and desirable goals that are sequentially introduced in three constrained optimization problems (better planning target volume (PTV) coverage, lower organ at risk (OAR) doses, and smoother fluence map). After solving the optimization problems using external commercial optimization engines, the optimal fluence map is imported into an FDA-approved treatment planning system (TPS) for leaf sequencing and accurate full dose calculation. The dose-discrepancy between the optimization and TPS dose calculation is then calculated and incorporated into optimization by a novel dose correction loop technique using Lagrange multipliers. The correction loop incorporates the leaf sequencing and scattering effects into optimization to improve the plan quality and reduce the calculation time. The resultant optimal fluence map is again imported into TPS for leaf sequencing and final dose calculation for plan evaluation and delivery. The workflow is automated using application program interface (API) scripting, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug-in from the TPS. For each site, parameters and objective functions are chosen to represent clinical priorities. The first site chosen for clinical implementation was metastatic paraspinal lesions treated with stereotactic body radiotherapy (SBRT). As a first step, 75 ECHO paraspinal plans were generated retrospectively and compared with clinically treated plans generated by planners using VMAT (volumetric modulated arc therapy) with 4 to 6 partial arcs. Subsequently, clinical deployment began in April, 2017. RESULTS: In retrospective study, ECHO plans were found to be dosimetrically superior with respect to tumor coverage, plan conformity, and OAR sparing. For example, the average PTV D95%, cord and esophagus max doses, and Paddick Conformity Index were improved, respectively, by 1%, 6%, 14%, and 15%, at a negligible 3% cost of the average skin D10cc dose. CONCLUSION: Hierarchical constrained optimization is a powerful and flexible tool for automated IMRT treatment planning. The dosimetric correction step accurately accounts for detailed dosimetric multileaf collimator and scattering effects. The system produces high-quality, Pareto optimal plans and avoids the time-consuming trial-and-error planning process.


Assuntos
Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada , Automação , Modelos Teóricos , Fatores de Tempo
12.
Int J Radiat Oncol Biol Phys ; 71(1 Suppl): S103-7, 2008.
Artigo em Inglês | MEDLINE | ID: mdl-18406905

RESUMO

Compared with conventional three-dimensional (3D) conformal radiation therapy and intensity-modulated radiation therapy treatments, quality assurance (QA) for motion-adaptive radiation therapy involves various challenges because of the added temporal dimension. Here we discuss those challenges for three specific techniques related to motion-adaptive therapy: namely respiratory gating, breath holding, and four-dimensional computed tomography. Similar to the introduction of any other new technologies in clinical practice, typical QA measures should be taken for these techniques also, including initial testing of equipment and clinical procedures, as well as frequent QA examinations during the early stage of implementation. Here, rather than covering every QA aspect in depth, we focus on some major QA challenges. The biggest QA challenge for gating and breath holding is how to ensure treatment accuracy when internal target position is predicted using external surrogates. Recommended QA measures for each component of treatment, including simulation, planning, patient positioning, and treatment delivery and verification, are discussed. For four-dimensional computed tomography, some major QA challenges have also been discussed.


Assuntos
Movimento , Controle de Qualidade , Radioterapia Assistida por Computador/normas , Respiração , Tomografia Computadorizada por Raios X/métodos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/radioterapia , Calibragem , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/radioterapia , Imagens de Fantasmas/normas , Próteses e Implantes , Radioterapia Assistida por Computador/métodos
13.
Med Image Comput Comput Assist Interv ; 11071: 777-785, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30294726

RESUMO

We present an adversarial domain adaptation based deep learning approach for automatic tumor segmentation from T2-weighted MRI. Our approach is composed of two steps: (i) a tumor-aware unsupervised cross-domain adaptation (CT to MRI), followed by (ii) semi-supervised tumor segmentation using Unet trained with synthesized and limited number of original MRIs. We introduced a novel target specific loss, called tumor-aware loss, for unsupervised cross-domain adaptation that helps to preserve tumors on synthesized MRIs produced from CT images. In comparison, state-of-the art adversarial networks trained without our tumor-aware loss produced MRIs with ill-preserved or missing tumors. All networks were trained using labeled CT images from 377 patients with non-small cell lung cancer obtained from the Cancer Imaging Archive and unlabeled T2w MRIs from a completely unrelated cohort of 6 patients with pre-treatment and 36 on-treatment scans. Next, we combined 6 labeled pre-treatment MRI scans with the synthesized MRIs to boost tumor segmentation accuracy through semi-supervised learning. Semi-supervised training of cycle-GAN produced a segmentation accuracy of 0.66 computed using Dice Score Coefficient (DSC). Our method trained with only synthesized MRIs produced an accuracy of 0.74 while the same method trained in semi-supervised setting produced the best accuracy of 0.80 on test. Our results show that tumor-aware adversarial domain adaptation helps to achieve reasonably accurate cancer segmentation from limited MRI data by leveraging large CT datasets.

14.
Semin Radiat Oncol ; 17(4): 268-77, 2007 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-17903704

RESUMO

Technological developments in image-guided radiotherapy systems have introduced new considerations to the treatment-planning process. These include more rational assessment and reduction of treatment margins; adaptation of treatment plans according to information gathered as treatment progresses; and facilitation of treatments involving the delivery of large, highly focused doses of radiation to tumors. We examine the performance of different treatment-room image-guidance systems in terms of target position accuracy; such information is important for determining treatment margins and deciding on an appropriate correction strategy. Some clinical situations may warrant a modification to a patient's treatment plan part way through a course of treatment, such as tumor shrinkage in response to treatment and daily organ variation. We discuss the challenges and review proposed strategies for treatment-plan adaptation. Image guidance in combination with 3-dimensional conformal and intensity-modulated radiotherapy has provided the tools for clinical trials of single-dose and hypofractionated treatment as an alternative to standard fractionation. We discuss the clinical realization of this treatment paradigm in various disease sites.


Assuntos
Diagnóstico por Imagem , Neoplasias/radioterapia , Planejamento da Radioterapia Assistida por Computador/métodos , Fracionamento da Dose de Radiação , Feminino , Neoplasias de Cabeça e Pescoço/radioterapia , Humanos , Neoplasias Hepáticas/radioterapia , Neoplasias Pulmonares/radioterapia , Masculino , Neoplasias da Próstata/radioterapia , Dosagem Radioterapêutica , Tomografia Computadorizada por Raios X
15.
Int J Radiat Oncol Biol Phys ; 67(5): 1548-58, 2007 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-17394950

RESUMO

PURPOSE: To evaluate the use of megavoltage cone-beam computed tomography (MV CBCT) to measure interfractional variation in lung tumor position. METHODS AND MATERIALS: Eight non-small-cell lung cancer patients participated in the study, 4 with respiratory gating and 4 without. All patients underwent MV CBCT scanning at weekly intervals. Contoured planning CT and MV CBCT images were spatially registered based on vertebral anatomy, and displacements of the tumor centroid determined. Setup error was assessed by comparing weekly portal orthogonal radiographs with digitally reconstructed radiographs generated from planning CT images. Hypothesis testing was performed to test the statistical significance of the volume difference, centroid displacement, and setup uncertainty. RESULTS: The vertebral bodies and soft tissue portions of tumor within lung were visible on the MV CBCT scans. Statistically significant systematic volume decrease over the course of treatment was observed for 1 patient. The average centroid displacement between simulation CT and MV CBCT scans were 2.5 mm, -2.0 mm, and -1.5 mm with standard deviations of 2.7 mm, 2.7 mm, and 2.6 mm in the right-left, anterior-posterior and superior-inferior directions. The mean setup errors were smaller than the centroid shifts, while the standard deviations were comparable. In most cases, the gross tumor volume (GTV) defined on the MV CBCT was located on average at least 5 mm inside a 10 mm expansion of the GTV defined on the planning CT scan. CONCLUSIONS: The MV CBCT technique can be used to image lung tumors and may prove valuable for image-guided radiotherapy. Our conclusions must be verified in view of the small patient number.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/radioterapia , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/radioterapia , Movimento , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Estudos de Viabilidade , Humanos , Variações Dependentes do Observador , Aceleradores de Partículas , Planejamento da Radioterapia Assistida por Computador/métodos
16.
Med Phys ; 34(12): 4772-81, 2007 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-18196805

RESUMO

The modeling of respiratory motion is important for a more accurate understanding and accounting of its effect on dose to cancers in the thorax and abdomen by radiotherapy. We have developed a model of respiration-induced organ motion in the thorax without the commonly adopted assumption of repeatable breath cycles. The model describes the motion of a volume of interest within the patient based on a reference three-dimensional (3D) image (at end expiration) and the diaphragm positions at different time points. The input data are respiration-correlated CT (RCCT) images of patients treated for non-small- cell lung cancer, consisting of 3D images, including the diaphragm positions, at ten phases of the respiratory cycle. A deformable image registration algorithm calculates the deformation field that maps each 3D image to the reference 3D image. A principal component analysis is performed to parameterize the 3D deformation field in terms of the diaphragm motion. We show that the first two principal components are adequate to accurately and completely describe the organ motion in the data of four patients. Artifacts in the RCCT images that commonly occur at the mid-respiration states are reduced in the model-generated images. Further validation of the model is demonstrated in the successful application of the parameterized 3D deformation field to RCCT data of the same patient but acquired several days later. We have developed a method for predicting respiration-induced organ motion in patients that has potential for improving the accuracy of dose calculation in radiotherapy. Possible limitations of the model are cases where the correlation between lung tumor and diaphragm position is less reliable such as superiorly situated tumors and interfraction changes in tumor-diaphragm correlation. The limited number of clinical cases examined suggests, but does not confirm, the model's applicability to a wide range of patients.


Assuntos
Modelos Biológicos , Movimento , Pacientes , Planejamento da Radioterapia Assistida por Computador/métodos , Respiração , Neoplasias Abdominais/diagnóstico por imagem , Neoplasias Abdominais/fisiopatologia , Neoplasias Abdominais/radioterapia , Expiração , Humanos , Imageamento Tridimensional , Inalação , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/fisiopatologia , Neoplasias Pulmonares/radioterapia , Neoplasias Torácicas/diagnóstico por imagem , Neoplasias Torácicas/fisiopatologia , Neoplasias Torácicas/radioterapia , Tomografia Computadorizada por Raios X
17.
IEEE Trans Med Imaging ; 26(10): 1379-90, 2007 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-17948728

RESUMO

Two major factors preventing the routine clinical use of finite-element analysis for image registration are: 1) the substantial labor required to construct a finite-element model for an individual patient's anatomy and 2) the difficulty of determining an appropriate set of finite-element boundary conditions. This paper addresses these issues by presenting algorithms that automatically generate a high quality hexahedral finite-element mesh and automatically calculate boundary conditions for an imaged patient. Medial shape models called m-reps are used to facilitate these tasks and reduce the effort required to apply finite-element analysis to image registration. Encouraging results are presented for the registration of CT image pairs which exhibit deformation caused by pressure from an endorectal imaging probe and deformation due to swelling.


Assuntos
Algoritmos , Inteligência Artificial , Reconhecimento Automatizado de Padrão/métodos , Neoplasias da Próstata/diagnóstico por imagem , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Técnica de Subtração , Tomografia Computadorizada por Raios X/métodos , Simulação por Computador , Elasticidade , Análise de Elementos Finitos , Humanos , Imageamento Tridimensional/métodos , Masculino , Modelos Biológicos , Neoplasias da Próstata/fisiopatologia , Intensificação de Imagem Radiográfica/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
18.
Lung Cancer ; 51(1): 41-51, 2006 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-16198022

RESUMO

We evaluated the ability of a commercial respiratory gating system to assure the reproducibility of internal anatomy in respiration synchronized CT (RS-CT) scans. This passive system uses an infrared sensitive camera to track the motion of reflective markers mounted on the abdomen. Eighteen patients, nine with lung tumors and nine with liver tumors, were selected for evaluation of the Varian Real-Time Position Monitor respiratory gating system. Liver tumors were chosen as surrogate for lower lobe tumors. Each patient underwent at least two identical RS-CT scans, at end-inspiration (EI) or end-expiration (EE), to assess intra-fraction reproducibility. Twelve patients also underwent a free breathing scan and an opposed-respiration phase synchronized scan (EI if the two first were an EE and vice versa). On each CT, a physician contoured the liver, the kidneys, the spleen, and the diaphragms for the liver patients; and similarly, the lungs, the gross tumor volume (GTV), the trachea, the heart and the diaphragms for the lung patients. After registering the different CT images using bony anatomy, the changes of each structure between the respective data sets were quantified in terms of its volume, the displacement of its center of mass (COM), and an "index" coefficient of reproducibility. An analysis of the CT scans obtained at EI and EE phases yielded an average superior-inferior (SI) difference of the diaphragm position of 14.4 mm (range: 45.9-0.9). A similar analysis of CT scans acquired at the same breathing phase yielded 0.7 mm (range: 3.1-0, p=0.0001). Similar conclusions were derived in analysis of COM positions of the following structures: lungs, heart, lung's GTV, liver, spleen and kidneys. Evaluation of volume changes for lungs, liver, and spleen confirmed reproducibility of RS-CT while the "index" coefficient confirmed reproducibility of RS-CT of all organs. A commercial gating system using external markers for RS-CT significantly improves the positional reproducibility of thoracic and upper abdominal structures. This reproducible decrease in organ motion will allow a reduction of the margin of expansion facilitating increase in target dose beyond that allowed by conventional radiation treatments.


Assuntos
Fígado/fisiopatologia , Neoplasias Pulmonares/fisiopatologia , Pulmão/fisiopatologia , Respiração , Adulto , Idoso , Idoso de 80 Anos ou mais , Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/fisiopatologia , Feminino , Humanos , Fígado/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Neoplasias Pulmonares/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Movimento , Variações Dependentes do Observador , Radiografia , Reprodutibilidade dos Testes , Gravação em Vídeo
19.
Med Phys ; 33(10): 3874-900, 2006 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-17089851

RESUMO

This document is the report of a task group of the AAPM and has been prepared primarily to advise medical physicists involved in the external-beam radiation therapy of patients with thoracic, abdominal, and pelvic tumors affected by respiratory motion. This report describes the magnitude of respiratory motion, discusses radiotherapy specific problems caused by respiratory motion, explains techniques that explicitly manage respiratory motion during radiotherapy and gives recommendations in the application of these techniques for patient care, including quality assurance (QA) guidelines for these devices and their use with conformal and intensity modulated radiotherapy. The technologies covered by this report are motion-encompassing methods, respiratory gated techniques, breath-hold techniques, forced shallow-breathing methods, and respiration-synchronized techniques. The main outcome of this report is a clinical process guide for managing respiratory motion. Included in this guide is the recommendation that tumor motion should be measured (when possible) for each patient for whom respiratory motion is a concern. If target motion is greater than 5 mm, a method of respiratory motion management is available, and if the patient can tolerate the procedure, respiratory motion management technology is appropriate. Respiratory motion management is also appropriate when the procedure will increase normal tissue sparing. Respiratory motion management involves further resources, education and the development of and adherence to QA procedures.


Assuntos
Neoplasias/radioterapia , Radioterapia (Especialidade)/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada/métodos , Respiração , Guias como Assunto , Humanos , Movimento (Física) , Neoplasias/patologia , Controle de Qualidade , Radiometria , Dosagem Radioterapêutica , Radioterapia Assistida por Computador , Fatores de Tempo , Tomografia Computadorizada por Raios X/métodos
20.
Technol Cancer Res Treat ; 15(3): 460-71, 2016 06.
Artigo em Inglês | MEDLINE | ID: mdl-25948321

RESUMO

Although spatially precise systems are now available for small-animal irradiations, there are currently limited software tools available for treatment planning for such irradiations. We report on the adaptation, commissioning, and evaluation of a 3-dimensional treatment planning system for use with a small-animal irradiation system. The 225-kV X-ray beam of the X-RAD 225Cx microirradiator (Precision X-Ray) was commissioned using both ion-chamber and radiochromic film for 10 different collimators ranging in field size from 1 mm in diameter to 40 × 40 mm(2) A clinical 3-dimensional treatment planning system (Metropolis) developed at our institution was adapted to small-animal irradiation by making it compatible with the dimensions of mice and rats, modeling the microirradiator beam orientations and collimators, and incorporating the measured beam data for dose calculation. Dose calculations in Metropolis were verified by comparison with measurements in phantoms. Treatment plans for irradiation of a tumor-bearing mouse were generated with both the Metropolis and the vendor-supplied software. The calculated beam-on times and the plan evaluation tools were compared. The dose rate at the central axis ranges from 74 to 365 cGy/min depending on the collimator size. Doses calculated with Metropolis agreed with phantom measurements within 3% for all collimators. The beam-on times calculated by Metropolis and the vendor-supplied software agreed within 1% at the isocenter. The modified 3-dimensional treatment planning system provides better visualization of the relationship between the X-ray beams and the small-animal anatomy as well as more complete dosimetric information on target tissues and organs at risk. It thereby enhances the potential of image-guided microirradiator systems for evaluation of dose-response relationships and for preclinical experimentation generally.


Assuntos
Modelos Animais , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia Guiada por Imagem/métodos , Animais , Camundongos , Tomografia Computadorizada por Raios X
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