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The aim of this paper is to enable model guided multi-scale and multi-modal image integration for the head and neck anatomy. The image modality used for this purpose includes multi-pose Magnetic Resonance Imaging (MRI), Mega Voltage CT, and hand-held Optical Coherence Tomography. A biomechanical model that incorporates subject-specific young's modulus and shear modulus properties is developed from multi-pose MRI, positioned in the treatment setup using Mega Voltage CT (MVCT), and actuated using multiple kinect surface cameras to mimic patient postures during Optical Coherence Microscopy (OCM) imaging. Two different 3D tracking mechanisms were employed for aligning the patient surface and the probe position to the MRI data. The results show the accuracy of the two tracking algorithms and the 3D head and neck deformation representing the multiple poses, the subject will take during the OCM imaging.
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Neoplasias de Cabeça e Pescoço/diagnóstico , Neoplasias de Cabeça e Pescoço/radioterapia , Modelos Biológicos , Radioterapia Assistida por Computador/métodos , Técnica de Subtração , Interface Usuário-Computador , Simulação por Computador , Humanos , Integração de SistemasRESUMO
INTRODUCTION: Unscheduled machine downtime can cause treatment interruptions and adversely impact patient treatment outcomes. Conventional Quality Assurance (QA) programs of a proton Pencil Beam Scanning (PBS) system ensure its operational performance by keeping the beam parameters within clinical tolerances but often do not reveal the underlying issues of the device prior to a machine malfunction event. In this study, we propose a Predictive Maintenance (PdM) approach that leverages an advanced analytical tool built on a deep neural network to detect treatment delivery machine issues early. METHODS: Beam delivery log file data from daily QA performed at the Burr Proton Center of Massachusetts General Hospital were collected. A novel PdM framework consisting of long short-term memory-based autoencoder (LSTM-AE) modeling of the proton PBS delivery system and a Mahalanobis distance-based error metric evaluation was constructed to detect rare anomalous machine events. These included QA beam pauses, clinical operational issues, and treatment interruptions. The model was trained in an unsupervised fashion on the QA data of normal sessions so that the model learned characteristics of normal machine operation. The anomaly is quantified as the multivariate deviation between the model predicted data and the measured data of the day using Mahalanobis distance (M-Score). Two-layer and three-layer Long short-term memory-based stacked autoencoder (LSTM-SAE) models were optimized for exploring model performance improvement. Model validation was performed with two clinical datasets and was analyzed using the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic (AUROC). RESULTS: LSTM-SAE models showed strong performance in predicting QA beam pauses for both clinical validation datasets. Despite severe skew in the dataset, the model achieved AUPRC of 0.60 and 0.82 and AUROC of 0.75 and 0.92 in the respective 2018 and 2020 datasets. Moreover, these amount to 2.8-fold and 10.7-fold enhancement compared to the respective baseline event rates. In addition, in terms of treatment interruption events, model prediction enabled 3.88-fold and 51.2-fold detection improvement, while the detection improvement for clinical operational issues was 1.04-fold and 1.37-fold, respectively, in the 2018 and 2020 datasets. CONCLUSION: Our novel deep LSTM-SAE-based framework allows for highly discriminative prediction of anomalous machine events and demonstrates great promise for enabling PdM for proton PBS beam delivery.
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Terapia com Prótons , Prótons , Humanos , Redes Neurais de ComputaçãoRESUMO
We report the design, implementation, and characterization of a grism-pair stretcher in a near-infrared noncollinear optical parametric chirped-pulse amplifier (OPCPA) that is capable of controlling a bandwidth of 440 nm. Our dynamic dispersion control scheme relies on the grism stretcher working in conjunction with an acousto-optic programmable dispersive filter (Dazzler) to jointly compensate large amount of material dispersion. A spectral interference technique is used to characterize the spectral phase of the grism stretcher. This ultra-broadband device opens up the way to generate sub-2-cycle laser pulses.
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Amplificadores Eletrônicos , Lasers , Refratometria/instrumentação , Desenho de Equipamento , Análise de Falha de EquipamentoRESUMO
PURPOSE: Radiomics provides quantitative tissue heterogeneity profiling and is an exciting approach to developing imaging biomarkers in the context of precision medicine. Normal-appearing parenchymal tissues surrounding primary tumors can harbor microscopic disease that leads to increased risk of distant metastasis (DM). This study assesses whether computed-tomography (CT) imaging features of such peritumoral tissues can predict DM in locally advanced non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: 200 NSCLC patients of histological adenocarcinoma were included in this study. The investigated lung tissues were tumor rim, defined to be 3mm of tumor and parenchymal tissue on either side of the tumor border and the exterior region extended from 3 to 9mm outside of the tumor. Fifteen stable radiomic features were extracted and evaluated from each of these regions on pre-treatment CT images. For comparison, features from expert-delineated tumor contours were similarly prepared. The patient cohort was separated into training and validation datasets for prognostic power evaluation. Both univariable and multivariable analyses were performed for each region using concordance index (CI). RESULTS: Univariable analysis reveals that six out of fifteen tumor rim features were significantly prognostic of DM (p-value < 0.05), as were ten features from the visible tumor, and only one of the exterior features was. Multivariablely, a rim radiomic signature achieved the highest prognostic performance in the independent validation sub-cohort (CI = 0.64, p-value = 2.4×10-5) significantly over a multivariable clinical model (CI = 0.53), a visible tumor radiomics model (CI = 0.59), or an exterior tissue model (CI = 0.55). Furthermore, patient stratification by the combined rim signature and clinical predictor led to a significant improvement on the clinical predictor alone and also outperformed stratification using the combined tumor signature and clinical predictor. CONCLUSIONS: We identified peritumoral rim radiomic features significantly associated with DM. This study demonstrated that peritumoral imaging characteristics may provide additional valuable information over the visible tumor features for patient risk stratification due to cancer metastasis.
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Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Tomografia Computadorizada por Raios X , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Estadiamento de Neoplasias , Reprodutibilidade dos Testes , Resultado do TratamentoRESUMO
OBJECTIVE: A recently proposed "5DCT" protocol uses deformable registration of free-breathing fast-helical CT scans to generate a breathing motion model. In order to allow accurate registration, free-breathing images are required to be free of doubling-artefacts, which arise when tissue motion is greater than scan speed. METHODS: Using a unique set of digital phantoms based on patient data and verified with a motion phantom, this work identifies the minimum scanner parameters required to successfully generate free-breathing artefact-free fast-helical scans. A motion phantom and 5 patients were imaged 25 times under free-breathing conditions in alternating directions with a 64-slice CT scanner employing a low-dose fast-helical protocol. A series of high temporal resolution (0.1 s) 5DCT scan data sets was generated in each case. A simulated CT scanner was used to "image" each free-breathing data set. Various CT scanner detector widths and rotation times were simulated, and verified using the motion phantom results. Motion-induced artefacts were quantified in patient images using structural similarity maps to determine the similarity between axial slices. RESULTS: Increasing amounts of motion-induced artefacts were observed with increasing rotation times >0.2 s for 16 mm detector configuration. CONCLUSION: The current generation of 16-slice CT scanners, which are present in the majority of Radiation Oncology departments, are not capable of generating free-breathing sorting artefact-free images required for 5DCT. Advances in knowledge: A recently proposed "5DCT" protocol uses deformable registration of free-breathing fast-helical CT scans to generate a breathing motion model. In order to allow accurate registration, free-breathing images are required to be free of doubling-artefacts, which arise when tissue motion is greater than scan speed. The results suggest that the current generation of 16-slice CT scanners, present in the majority of Radiation Oncology departments, are not capable of generating the free-breathing images required for 5DCT.
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Artefatos , Pulmão/diagnóstico por imagem , Movimento (Física) , Respiração , Tomografia Computadorizada Espiral/métodos , Humanos , Processamento de Imagem Assistida por Computador , Imagens de FantasmasRESUMO
PURPOSE: To compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol. METHODS AND MATERIALS: Twenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts. RESULTS: Mean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images. CONCLUSION: Tumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods.
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Tomografia Computadorizada Quadridimensional/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-IdadeRESUMO
To determine if the parameters relating lung tissue displacement to a breathing surrogate signal in a previously published respiratory motion model vary with the rate of breathing during image acquisition. An anesthetized pig was imaged using multiple fast helical scans to sample the breathing cycle with simultaneous surrogate monitoring. Three datasets were collected while the animal was mechanically ventilated with different respiratory rates: 12 bpm (breaths per minute), 17 bpm, and 24 bpm. Three sets of motion model parameters describing the correspondences between surrogate signals and tissue displacements were determined. The model error was calculated individually for each dataset, as well asfor pairs of parameters and surrogate signals from different experiments. The values of one model parameter, a vector field denoted [Formula: see text] which related tissue displacement to surrogate amplitude, determined for each experiment were compared. The mean model error of the three datasets was 1.00 ± 0.36 mm with a 95th percentile value of 1.69 mm. The mean error computed from all combinations of parameters and surrogate signals from different datasets was 1.14 ± 0.42 mm with a 95th percentile of 1.95 mm. The mean difference in [Formula: see text] over all pairs of experiments was 4.7% ± 5.4%, and the 95th percentile was 16.8%. The mean angle between pairs of [Formula: see text] was 5.0 ± 4.0 degrees, with a 95th percentile of 13.2 mm. The motion model parameters were largely unaffected by changes in the breathing rate during image acquisition. The mean error associated with mismatched sets of parameters and surrogate signals was 0.14 mm greater than the error achieved when using parameters and surrogate signals acquired with the same breathing rate, while maximum respiratory motion was 23.23 mm on average.
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Movimentos dos Órgãos , Taxa Respiratória , Tomografia Computadorizada Espiral/métodos , Animais , Pulmão/diagnóstico por imagem , Suínos , Tomografia Computadorizada Espiral/normasRESUMO
PURPOSE: To develop a technique that assesses the accuracy of the breathing phase-specific volume image generation process by patient-specific breathing motion model using the original free-breathing computed tomographic (CT) scans as ground truths. METHODS: Sixteen lung cancer patients underwent a previously published protocol in which 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. A patient-specific motion model was constructed based on the tissue displacements determined by a state-of-the-art deformable image registration. The first image was arbitrarily selected as the reference image. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields that mapped the reference image to the 24 nonreference images. The high-pitch helically acquired original scans served as ground truths because they captured the instantaneous tissue positions during free breathing. Image similarity between the simulated and the original scans was assessed using deformable registration that evaluated the pointwise discordance throughout the lungs. RESULTS: Qualitative comparisons using image overlays showed excellent agreement between the simulated images and the original images. Even large 2-cm diaphragm displacements were very well modeled, as was sliding motion across the lung-chest wall boundary. The mean error across the patient cohort was 1.15 ± 0.37 mm, and the mean 95th percentile error was 2.47 ± 0.78 mm. CONCLUSION: The proposed ground truth-based technique provided voxel-by-voxel accuracy analysis that could identify organ-specific or tumor-specific motion modeling errors for treatment planning. Despite a large variety of breathing patterns and lung deformations during the free-breathing scanning session, the 5-dimensionl CT technique was able to accurately reproduce the original helical CT scans, suggesting its applicability to a wide range of patients.
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Tomografia Computadorizada Quadridimensional/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Movimento , Planejamento da Radioterapia Assistida por Computador/métodos , Respiração , Tomografia Computadorizada Espiral/métodos , Algoritmos , Artefatos , Protocolos Clínicos , Expiração , Tomografia Computadorizada Quadridimensional/normas , Humanos , Inalação , Garantia da Qualidade dos Cuidados de Saúde , Planejamento da Radioterapia Assistida por Computador/normas , Reprodutibilidade dos Testes , Tomografia Computadorizada Espiral/normasRESUMO
PURPOSE: To determine if and by how much the commercial 4DCT protocols under- and overestimate tumor breathing motion. METHODS: 1D simulations were conducted that modeled a 16-slice CT scanner and tumors moving proportionally to breathing amplitude. External breathing surrogate traces of at least 5-min duration for 50 patients were used. Breathing trace amplitudes were converted to motion by relating the nominal tumor motion to the 90th percentile breathing amplitude, reflecting motion defined by the more recent 5DCT approach. Based on clinical low-pitch helical CT acquisition, the CT detector moved according to its velocity while the tumor moved according to the breathing trace. When the CT scanner overlapped the tumor, the overlapping slices were identified as having imaged the tumor. This process was repeated starting at successive 0.1 s time bin in the breathing trace until there was insufficient breathing trace to complete the simulation. The tumor size was subtracted from the distance between the most superior and inferior tumor positions to determine the measured tumor motion for that specific simulation. The effect of the scanning parameter variation was evaluated using two commercial 4DCT protocols with different pitch values. Because clinical 4DCT scan sessions would yield a single tumor motion displacement measurement for each patient, errors in the tumor motion measurement were considered systematic. The mean of largest 5% and smallest 5% of the measured motions was selected to identify over- and underdetermined motion amplitudes, respectively. The process was repeated for tumor motions of 1-4 cm in 1 cm increments and for tumor sizes of 1-4 cm in 1 cm increments. RESULTS: In the examined patient cohort, simulation using pitch of 0.06 showed that 30% of the patients exhibited a 5% chance of mean breathing amplitude overestimations of 47%, while 30% showed a 5% chance of mean breathing amplitude underestimations of 36%; with a separate simulation using pitch of 0.1 showing, respectively, 37% overestimation and 61% underestimation. CONCLUSIONS: The simulation indicates that commercial low-pitch helical 4DCT processes potentially yield large tumor motion measurement errors, both over- and underestimating the tumor motion.
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Neoplasias Abdominais/diagnóstico por imagem , Tomografia Computadorizada Quadridimensional , Neoplasias Pulmonares/diagnóstico por imagem , Erros Médicos , Modelos Teóricos , Movimento , Neoplasias Abdominais/fisiopatologia , Humanos , Neoplasias Pulmonares/fisiopatologia , RespiraçãoRESUMO
PURPOSE: To demonstrate that a "5DCT" technique which utilizes fast helical acquisition yields the same respiratory-gated images as a commercial technique for regular, mechanically produced breathing cycles. METHODS: Respiratory-gated images of an anesthetized, mechanically ventilated pig were generated using a Siemens low-pitch helical protocol and 5DCT for a range of breathing rates and amplitudes and with standard and low dose imaging protocols. 5DCT reconstructions were independently evaluated by measuring the distances between tissue positions predicted by a 5D motion model and those measured using deformable registration, as well by reconstructing the originally acquired scans. Discrepancies between the 5DCT and commercial reconstructions were measured using landmark correspondences. RESULTS: The mean distance between model predicted tissue positions and deformably registered tissue positions over the nine datasets was 0.65 ± 0.28 mm. Reconstructions of the original scans were on average accurate to 0.78 ± 0.57 mm. Mean landmark displacement between the commercial and 5DCT images was 1.76 ± 1.25 mm while the maximum lung tissue motion over the breathing cycle had a mean value of 27.2 ± 4.6 mm. An image composed of the average of 30 deformably registered images acquired with a low dose protocol had 6 HU image noise (single standard deviation) in the heart versus 31 HU for the commercial images. CONCLUSIONS: An end to end evaluation of the 5DCT technique was conducted through landmark based comparison to breathing gated images acquired with a commercial protocol under highly regular ventilation. The techniques were found to agree to within 2 mm for most respiratory phases and most points in the lung.
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Técnicas de Imagem de Sincronização Respiratória/métodos , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Animais , Pulmão/diagnóstico por imagem , Masculino , Modelos Animais , Modelos Biológicos , Movimento (Física) , Doses de Radiação , Respiração , Técnicas de Imagem de Sincronização Respiratória/instrumentação , Suínos , Tomografia Computadorizada por Raios X/instrumentaçãoRESUMO
Radiotherapy is safely employed for treating wide variety of cancers. The radiotherapy workflow includes a precise positioning of the patient in the intended treatment position. While trained radiation therapists conduct patient positioning, consultation is occasionally required from other experts, including the radiation oncologist, dosimetrist, or medical physicist. In many circumstances, including rural clinics and developing countries, this expertise is not immediately available, so the patient positioning concerns of the treating therapists may not get addressed. In this paper, we present a framework to enable remotely located experts to virtually collaborate and be present inside the 3D treatment room when necessary. A multi-3D camera framework was used for acquiring the 3D treatment space. A client-server framework enabled the acquired 3D treatment room to be visualized in real-time. The computational tasks that would normally occur on the client side were offloaded to the server side to enable hardware flexibility on the client side. On the server side, a client specific real-time stereo rendering of the 3D treatment room was employed using a scalable multi graphics processing units (GPU) system. The rendered 3D images were then encoded using a GPU-based H.264 encoding for streaming. Results showed that for a stereo image size of 1280 × 960 pixels, experts with high-speed gigabit Ethernet connectivity were able to visualize the treatment space at approximately 81 frames per second. For experts remotely located and using a 100 Mbps network, the treatment space visualization occurred at 8-40 frames per second depending upon the network bandwidth. This work demonstrated the feasibility of remote real-time stereoscopic patient setup visualization, enabling expansion of high quality radiation therapy into challenging environments.
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PURPOSE: To determine the validity of the assumption that the γ dose distribution comparison tool defaults to the distance to agreement test under conditions of clinically relevant steep dose gradients and γ test criteria. METHODS: The assumption was tested by computing the angle θ between the dose axis and γ vector for clinical treatment plans. θ was a function of the evaluated dose distribution dose gradient and the ratio (α) of the dose difference to distance to agreement (DTA) criteria. Dose distributions from prostate, head and neck, and lung clinical treatment plans were examined: 50 treatment plans were selected for each of the prostate and head neck sites and 27 treatment plans were selected for lung. Dose-gradient histograms were prepared for each of the treatment plans using α = 1%/mm (e.g., 3%, 3 mm dose difference and DTA criteria, respectively). To determine how frequently different values of α were used in publications, papers that referenced the original γ paper were examined to identify the dose difference and DTA criteria used in those publications. In order to compare θ calculated using α = 1%/mm to θ for other values of α, the relationship between θ and α was determined. RESULTS: For most of the targets and critical structures, the maximum value of θ approached 90°, so the assumption that the γ tool defaulted to the DTA test in steep dose gradients was correct. Most of the published papers using the γ tool employed the 3%, 3 mm dose difference and DTA criteria, respectively. Most of the other evaluations used criteria such that α ≥ 1%/mm, so the conclusions relating to the examined dose distributions applied. There were a few papers employing very small values of α (including one where α = 0.17%/mm), breaking the assumption that the γ dose comparison tool defaulted to the DTA tool in steep dose gradients. CONCLUSIONS: Most published cases utilized values of α ≥ 1%/mm, and for those the implicit assumption that the γ dose comparison tool defaults to the DTA test in steep dose gradient regions was true. There were a few cases for which α was small enough to potentially invalidate this assumption. Care should be taken by investigators when selecting the γ test criteria to assure that the γ test will appropriately default to the DTA test in the steepest dose gradients being evaluated.