Respiratory Motion Research Articles

CT-augmented digital tomosynthesis image reconstruction in image-guided bronchoscopy interventions.

Transbronchial needle biopsy is crucial for diagnosing lung cancer, yet its efficacy depends on accurately localizing the target lesion and biopsy needle. Digital tomosynthesis (DTS) is considered a promising imaging modality for guiding bronchoscopy procedures due to its low radiation dose and small footprint relative to cone-beam computed tomography (CBCT). However, the image quality of DTS is still not sufficient for an accurate guidance, mainly due to its limited-angleacquisition. Preoperative computed tomography (CT) scans are often performed prior to bronchoscopy interventions for diagnosis or to plan the procedure. The CT images are of high quality and are characterized by a high spatial resolution compared to intraoperative DTS images. These patient-specific prior CT images and the intraoperative DTS images share a fair amount of anatomical information. The main differences only stem from patient positioning and respiratory motion. When these differences are addressed properly, prior CT images augment intraoperative DTS image reconstruction with strong prior knowledge and potentially enhance DTS imagequality. We propose in this work a prior-aided DTS image reconstruction technique leveraging prior CT images to improve DTS image quality. This technique is based on a recently published deformable CT-to-DTS image registration algorithm which is customized for bronchoscopy interventions. The main idea is to register a prior CT image to an intermediate DTS image reconstructed using the standard iterative algebraic reconstruction technique (ART), then to re-reconstruct the DTS image using ART and the registered prior CT image as a firstestimation. The proposed prior-aided reconstruction method was tested on a physical phantom and six patient bronchoscopy datasets. Real DTS data acquired with a pseudo-linear (PL) scan geometry and simulated DTS data generated according to a spherical ellipse (SE) scan geometry were considered. Results evaluated qualitatively by visual inspection and quantitatively by computing Pearson's correlation (PC) with respect to the reference CBCT images suggest significant improvements in image quality using the prior-aided DTS reconstruction compared to the standard zero-initialized ART reconstruction. PC coefficients of the six patient datasets were on average and using a zero-initialized ART reconstruction with SE data and PL data, respectively, and and using the proposed prior-aided reconstruction with SE data and PL data,respectively. While the initial estimation in iterative reconstruction algorithms is often overlooked, we proved that initial estimation is of critical importance in DTS image reconstruction and we have demonstrated the profound advantages of integrating prior CT images in intraoperative DTS image reconstruction. CT-augmented DTS offers a viable alternative to CBCT in guiding bronchoscopy interventions at a fraction of the radiation dose. Further clinical studies are needed to validate improved diagnosticyield.

Rapid non-invasive mechanical ventilation appears superior to non-invasive high-frequency jet ventilation in reducing respiratory motion for radiotherapy

Rapid non-invasive mechanical ventilation appears superior to non-invasive high-frequency jet ventilation in reducing respiratory motion for radiotherapy

Markerless tracking of tumor and tissues: A motion model approach.

Respiratory motion management is essential in order to achieve high-precision radiotherapy. Markerless motion tracking of tumor can provide a non-invasive way to manage respiratory motion, thereby enhancing treatment accuracy. However, the low contrast in real-time x-ray images for image guidance limits the application of markerless tracking. We present a novel approach based on a motion model to perform markerless tracking of tumor and surrounding tissues even when they have low contrast in real-time x-ray images. A proof-of-concept validation of the method has been performed using digital and physical phantoms at breathing conditions that are significantly different than the planning stage. A motion model is first constructed by performing principal component analysis (PCA) on the planning 4DCT. During treatment, the motion of a surrogate is tracked and used as the input of the motion model, which generates a 3D real-time volume estimation. Such 3D estimation is then projected to 2D to create digitally reconstructed radiographs (DRRs). The relationships between the real-time DRRs, reference DRRs, and reference x-ray images are first established to simulate 2D real-time images from the real-time volume. The registration between the simulated 2D real-time images and real-time x-ray images corrects the initial motion model estimation to ensure the estimated volume matches the real-time condition. In digital phantom, the Dice index of pancreas was improved from 0.74 to 0.78 after correction using real-time DRRs in fully inhaled phase. Validation on lung and pancreas is performed in physical phantom with two motion traces. The surrogate-tumor relationships were intentionally altered to generate large target localization errors due to the differences in body condition between treatment planning stage and during treatment. The real-time correction for the estimated 3D real-time volume was performed using a pair of 2D x-ray images. For the deep breathing motion trace, the tumor localization mean absolute error (MAE) throughout the tracking decreases from around 3mm to less than 1mm after correction. For the shallow breathing motion trace with a 1.7mm baseline shift, the tumor localization MAE throughout the tracking decreases from around 1.5mm to less than 1mm after correction. The method combines the detailed structural information from planning 4DCT and real-time information from real-time x-ray images through a motion model. The matching between the real-time model estimation and 2D real-time images is performed in the same modality so that it can be applied to regions with low contrast in the images. The real-time images successfully corrected the initial motion model estimations in our proof-of-concept validation. This suggests the potential to perform markerless tracking in low-contrast region using a motion model.

Evaluation of dose distributions and respiratory motion tolerance for layer-stacking conformal carbon-ion radiotherapy.

While layer-stacking irradiation provides a conformal dose distribution, it is vulnerable to respiratory motion. Considering that the motion tolerance has not yet been demonstrated, this study aimed to determine the tolerance level for the amount of target motion. Dose distributions considering motion were simulated for a numerical water phantom using in-house software. Comparisons with measured and simulated physical dose distributions confirmed the validity of the simulation, with gamma analysis showing almost 90% or greater agreement under all conditions with a criterion of 3%/3mm. The variation in physical dose from static conditions followed a similar trend. Based on the evaluation of the simulated clinical dose uniformity, motion tolerance was derived. The acceptable motion amounts in the lateral direction were 11mm in respiratory-ungated condition and at least 20mm with 30% lateral gating at 4Gy (RBE). In the longitudinal (beam upstream) direction, the acceptable target motion amounts were 3mm without gating and 6mm with gating. These results employed worst-case scenarios considering multiple respiratory cycles. In both lateral and longitudinal directions, the motion amounts of 3mm for non-gating and 5mm for gating were acceptable. The acceptable target motion amounts improved by 1-9mm with gating and increased prescribed doses. The dose uniformity and motion tolerance under multiple conditions, although based on a simple system, may be useful for treatment involving target motion in layer-stacking irradiation.

Comprehensive Image Quality Evaluation and Motion Phantom Studies of an Ultra-Fast (6-Second) Cone-Beam Computed Tomography Imaging System on a Ring Gantry Linear Accelerator

PurposeTo evaluate the image quality of an ultra-fast CBCT system - Varian HyperSight. MethodsIn this evaluation, five-studies were performed to assess the image quality of HyperSight CBCT. First, a HyperSight CBCT image quality evaluation was performed and compared with Siemens simulation-CT and Varian TrueBeam CBCT. Second, a visual comparison of image quality among simulation-CTs, HyperSight CBCT and TrueBeam CBCT was performed for a head-and-neck patient, and patients with metal dental fillings and prosthesis. Third, the HU vs electron density curve of HyperSight CBCT was compared with GE and Siemens simulation-CTs. Fourth, Siemens simulation-CT and HyperSight CBCT scans were acquired on the Catphan setting-up at different locations inside the bore (±10cm in all three principal directions from the center), and the HU variations for different materials were evaluated. Fifth, a 4D lung tumor phantom study was performed to assess moving tumor alignment during image registration. ResultsSignificant improvement of image contrast, HU constancy, and noise level on HyperSight CBCT was observed compared to TrueBeam CBCT. Significant image quality improvement was observed on HyperSight CBCT for patients with dental fillings and prosthesis compared to simulation-CT without metal artifact reduction. The linear fit trend-line of HU vs electron density curves for GE simulation-CT, Siemens simulation-CT and HyperSight CBCT showed 0.6% difference for HU value below 2000. The maximum HU difference for HyperSight CBCT when Catphan positioned within ±10cm in all three principal directions was ≤98 on bone 50%, and ≤29 other than bone, and was ≤31 on bone 50%, and ≤17 other than bone for Siemens simulation-CT. Both tumor shape and tumor alignment discrepancies on CBCT scans were observed in 4D phantom study. ConclusionsThis evaluation shows significant image improvement of HyperSight CBCT over conventional CBCT on image contrast, HU constancy, and noise level with scatter correction and metal artifact reduction reconstruction methods. HyperSight CBCT has similar image quality to simulation-CTs, and shows the potential application for treatment planning. The rapid acquisition of HyperSight CBCT showed both tumor shape and tumor alignment discrepancies of moving target. Careful considerations of patient respiratory motion monitoring and target matching are highly recommended.

Increased survival of aquarium fish under acute hypoxia induced by prior intragastric administration of hydrogen peroxide

BACKGROUND: A solution of 3% hydrogen peroxide is an over-the-counter oxygen-releasing antiseptic, which forms oxygen foam when interacting locally with the wound surface. Therefore, this drug is widely used for mechanical cleansing of the surface of chronic wounds from purulent masses. The release of oxygen during catalase cleavage of hydrogen peroxide indicates the possibility of achieving anti-ischemic and anti-hypoxic action. AIM: A study of the effect of intragastric hydrogen peroxide on the resistance of aquarium fish to acute hypoxia. MATERIALS AND METHODS: Experiments were conducted on 80 adult aquarium fish of the guppy, blue neon, tri-linear parsings, swordtail fish and zebrafish (Danio rerio) breeds. To create acute hypoxia, each fish was placed in a transparent plastic container containing 5, 10 or 20 ml of fresh water at a temperature of +25 - +26 °C together with the fish, after which the container was hermetically sealed. Then, the motor activity of the fish's body, the respiratory movements of the gill arches, the opening of the oral cavity, the fluctuations of the fins and the dynamics of their coloration were monitored until the complete final immobilization of the fish and their death. Immediately before the experiment, 0.05 or 0.1 ml of fresh water in the control series and 0.05 ml or 0.1 ml of 0.05% hydrogen peroxide solution in the experimental series were injected into the stomach of the fish. The liquid was injected into the fish's stomach using a gastric mini-probe connected to an insulin syringe. RESULTS: It is shown that aquarium fish retain their viability in a small volume of fresh water inside a hermetically sealed container for a limited period of time, since fish continuously consume oxygen dissolved in water, thereby deepening hypoxia. At the same time, after sealing the container, the fish very quickly assume a stationary state, in which they remain for a certain period of time until their death. However, just before death, the immobility of the fish is disturbed. At the same time, the fish suddenly appear convulsive body movements, active movements of pectoral fins, mouths and gill arches, pectoral fins change their color, after which the fish defecate into the water. The results showed that the preliminary injection of 0.05 or 0.1 ml of 0.05% hydrogen peroxide solution into the stomach of fish prolongs the period of immobility of fish in hypoxia by an average of 20%. In all likelihood, the immobile state of fish is part of the complex of their adaptive adjustment to the cessation of oxygen supply to the water and reflects the availability of reserves of adaptation to hypoxia. The fact is that the absence of muscle contractions stops the muscles from using oxygen, which they use to generate energy. It is assumed that inside the stomach, hydrogen peroxide is absorbed into the blood, where, under the action of the enzyme catalase, it is split into water and gaseous oxygen, which replaces oxygen in the gills in the absence of oxygen in the surrounding water. CONCLUSIONS: Under model conditions, it was shown that pre-administration of 0.05 or 0.1 ml of 0.05% hydrogen peroxide solution into the stomach of fish increases their survival in conditions of acute hypoxia. Therefore, hydrogen peroxide can be considered as a potential antihypoxant for prolonging life in various types of suffocation, including the final stage of COVID-19.

Spectrally selective and interleaved water imaging and fat imaging (siWIFI).

To develop a novel imaging sequence that independently acquires water and fat images while being inherently insensitive to motion. The new sequence, termed spectrally selective and interleaved water imaging and fat imaging (siWIFI), uses a narrow bandwidth RF pulse for selective excitation of water and fat separately. The interleaved acquisition method ensures that the obtained water and fat images are inherently coregistered. A radial sampling strategy further reduces motion-induced artifacts. Phantoms with lipid concentrations ranging from 0% to 50% were scanned to measure fat fraction. Moreover, healthy volunteers were scanned to assess the in vivo feasibility of fat fraction measurement at the hip, knee, and liver. In vivo fat fraction measurements were compared with those from vendor-provided iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) scans. Furthermore, a magnetization transfer (MT) preparation module was incorporated to demonstrate the feasibility of simultaneous measurement of fat fraction and MT ratio utilizing the siWIFI framework. The phantom fat fractions measured by siWIFI showed excellent correlation with lipid concentrations (R2 = 0.9995, p < 0.0001). In vivo studies demonstrated that the fat fractions obtained from siWIFI were comparable to those from IDEAL. Additionally, siWIFI demonstrates reduced motion artifacts from pulsatile flow in knee imaging compared to IDEAL scans and exhibits less sensitivity to respiratory motion in liver imaging compared to IDEAL scans without breath-hold. The knee imaging study demonstrated that MT-prepared siWIFI is capable of generating fat fraction and MT ratio maps simultaneously. The proposed siWIFI sequence allows selective water-fat imaging and quantification with reduced motion artifacts.

Reproducibility and stability of voluntary deep inspiration breath hold and free breath in breast radiotherapy based on real-time 3-dimensional optical surface imaging system

BackgroundThe aim of this study was to evaluate the inter-fraction reproducibility and intra-fraction stability of breast radiotherapy using voluntary deep-inspiration breath hold (DIBH) and free breathing (FB) based on an optical surface imaging system (OSIS).MethodsSeventeen patients (510 breath-hold sessions) treated using a field-in-field (FiF) technique and twenty patients (600 breath-free sessions) treated with a volume-modulated arc therapy (VMAT) technique were included in this retrospective study. All the patients were positioned with the guidance of CBCT and OSIS, and also monitored with OSIS throughout the whole treatment session. Eight setup variations in three directions were extracted from the treatment reports of OSIS for all sessions and were subsequently manually introduced to treatment plans, resulting in a total of 296 perturbed plans. All perturbed plans were recalculated, and the dose volume histograms (DVH) for the target and organs at risk (OAR) were analyzed.ResultsThe OSIS and CBCT for both DIBH and FB treatments showed a good agreement of less than 0.30 cm in each direction. The intra-fraction respiratory motion data during DIBH were −0.06 ± 0.07 cm, 0.12 ± 0.15 cm, and 0.12 ± 0.12 cm in the lateral, longitudinal, and vertical directions, respectively; for FB, the respiratory motion data were −0.02 ± 0.12 cm, 0.08 ± 0.18 cm, and 0.14 ± 0.20 cm, respectively. For the target, DIBH plans were more sensitive to setup errors; the mean deviations in D95 for CTV were 39.78 Gy–40.17 Gy for DIBH and 38.46 Gy–40.52 Gy for FB, respectively. For the OARs, the mean deviations of V10, V20, and Dmean to the heart; V5, V20, and Dmean to the ipsilateral lung; and Dmean to the breast were lower for the FB plan compared with the DIBH plan.ConclusionBased on OSIS, our results indicate that both DIBH and FB can provide good reproducibility in the inter-fractions and stability in the intra-fractions. When the patient respiratory motion is large, the FB technology has greater possibility for the undercoverage of the target volume, while DIBH technology is more likely to result in increases in dose to OARs (the lung, heart, and contralateral breast).

Development of quantitative PET/MR imaging for measurements of hepatic portal vein input function: a phantom study

BackgroundAccurate pharmacokinetic modelling in PET necessitates measurements of an input function, which ideally is acquired non-invasively from image data. For hepatic pharmacokinetic modelling two input functions need to be considered, to account for the blood supply from the hepatic artery and portal vein. Image-derived measurements at the portal vein are challenging due to its small size and image artifacts caused by respiratory motion. In this work we seek to demonstrate, using phantom experiments, how a dedicated PET/MR protocol can tackle these challenges and potentially provide input function measurements of the portal vein in a clinical setup.MethodsA custom 3D printed PET/MR phantom was constructed to mimic the liver and portal vein. PET/MR acquisitions were made with emulated respiratory motion. The PET/MR imaging protocol consisted of high-resolution anatomical MR imaging of the portal vein, followed by a PET acquisition in parallel to a dedicated motion-tracking MR sequence. Motion tracking and deformation information were extracted from PET data and subsequently used in PET reconstruction to produce dynamic series of motion-free PET images. Anatomical MR images were used post PET reconstruction for partial volume correction of the input function measurements.ResultsReconstruction of dynamic PET data with motion-compensation provided nearly motion-free series of PET frame data, suitable for image derived input function measurements of the portal vein. After partial volume correction, the individual input function measurements were within a 16.1% error range from the true activity in the portal vein compartment at the time of PET acquisition.ConclusionThe proposed protocol demonstrates clinically feasible PET/MR imaging of the liver for pharmacokinetic studies with accurate quantification of the portal vein input function, including correction for respiratory motion and partial volume effects.

The Development of Volumetric Quantitative Evaluation Software for Assessing Respiratory-Induced Target Motion.

Purpose We developed a volumetric quantitative evaluation software called vector volume histogram (VVH) to evaluate respiratory-induced organ motion using deformable image registration (DIR). Methods The B-spline-based DIR algorithm was used to compute the deformation vector field (DVF), which included the DVFLR (left-right), DVFAP (anterior-posterior), and DVFCC (craniocaudal). The VVH software was written as a plug-in using Python, thus allowing anyone to easily modify the code. A shifted target within the moving phantom was used to evaluate the performance of the VVH software. The 2 cm diameter target was systematically shifted by 5, 10, 15, and 20 mm in the CC direction. To evaluate respiration-induced target motion, the VVH method was applied during the inhalation and exhalation phases of 4D CT scans in a patient with lung cancer. Length at 5% volume (L5%) and length at 50% volume (L50%​​​​​) were calculated to evaluate the target motion. Results In the phantom study, the VVH software accurately measured target displacements with L5% and L50% values of 5.4 mm and 4.8 mm, 10.4 mm and 9.8 mm, 14.9 mm, and 14.6 mm, and 19.9 mm and 19.6 mm for 5, 10, 15 and 20 mm displacements, respectively. For the lung cancer patient study, the VVH method showed target motion with L5% and L50% values of 1.9 mm and 1.8 mm in LR, 1.9 mm and 0.9 mm in AP, 18.8 mm and 15.8 mm in CC, and 18.9 mm and 15.8 mm in 3D vector. The centroid method measured respiratory tumor motion between the inhalation and exhalation phases as 0.5 mm, 0.7 mm, 13.5 mm, and 13.5 mm in the LR, AP, and CC directions and in the 3D vector. Conclusions The VVH software provided a volumetric quantitative assessment of respiratory-induced target motion and may provide strategic decisions for clinical use at the time of treatment planning.

CvTMorph: Improving Local Feature Extraction in Medical Image Registration for Respiratory Motion Modeling with Convolutional Vision Transformer.

Accurately modeling respiratory motion in medical images is crucial for various applications, including radiation therapy planning. However, existing registration methods often struggle to extract local features effectively, limiting their performance. In this paper, we aimed to propose a new framework called CvTMorph, which utilizes a Convolutional vision Transformer (CvT) and Convolutional Neural Networks (CNN) to improve local feature extraction. CvTMorph integrates CvT and CNN to construct a hybrid model that combines the strengths of both approaches. Additionally, scaling and square layers are added to enhance the registration performance. We have evaluated the performance of CvTMorph on the 4D-Lung and DIR-Lab datasets and compared it with state-of-the-art methods to demonstrate its effectiveness. The experimental results have demonstrated CvTMorph to outperform the existing methods in terms of accuracy and robustness for respiratory motion modeling in 4D images. The incorporation of the convolutional vision transformer has significantly improved the registration performance and enhanced the representation of local structures. CvTMorph offers a promising solution for accurately modeling respiratory motion in 4D medical images. The hybrid model, leveraging convolutional vision transformer and convolutional neural networks, has proven effective in extracting local features and improving registration performance. The results have highlighted the potential of CvTMorph for various applications, such as radiation therapy planning, and provided a basis for further research in this field.

Technical and Quality Considerations for Stereotactic Radiation Treatment Techniques.

Stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT), collectively termed SRS-SBRT, are advanced treatment modalities delivering high doses of radiation in a single treatment or condensed treatment phase. Due to the small margins and steep dose gradient used in SRS-SBRT, the technical and safety considerations are more stringent than traditional radiation therapy and may include more advanced simulation, patient immobilization, treatment planning, and treatment delivery techniques. Respiratory motion management and intrafraction motion monitoring are often used during SRS-SBRT to ensure treatments are robust to both internal organ motion and patient movement during treatment. To ensure optimal treatment quality, SRS-SBRT programs should use multidisciplinary coordination of care to ensure patient-specific treatment strategies are used for optimal patient outcomes. Quality and safety considerations are presented, including peer review and external validation, for optimizing quality and adhering to national guidelines for stereotactic techniques.

Data-Driven Volumetric CT Image Generation from Surface Structures using a Patient-Specific Deep Leaning Model

PurposeOptical surface imaging presents radiation-dose-free and noninvasive approaches for image-guided radiotherapy, allowing continuous monitoring during treatment delivery. However, it falls short in cases where correlation of motion between body surface and internal tumor is complex, limiting the use of purely surface-guided surrogates for tumor tracking. Relying solely on surface-guided radiation therapy (SGRT) may not ensure accurate intra-fractional monitoring. This work aims to develop a data-driven framework, mitigating the limitations of SGRT in lung cancer radiotherapy by reconstructing volumetric CT images from surface images. Methods and MaterialsWe conducted a retrospective analysis involving 50 lung cancer patients who underwent radiotherapy and had 10-phase 4DCT scans during their treatment simulation. For each patient, we utilized nine phases of 4DCT images for patient-specific model training and validation, reserving one phase for testing purposes. Our approach employed a surface-to-volume image synthesis framework, harnessing cycle-consistency generative adversarial networks to transform surface images into volumetric representations. The framework was extensively validated using an additional 6-patient cohort with re-simulated 4DCT. ResultsThe proposed technique has produced accurate volumetric CT images from the patient's body surface. In comparison to the ground truth CT images, those generated synthetically by the proposed method exhibited the GTV center of mass difference of 1.72±0.87 mm, the overall mean absolute error of 36.2±7.0 HU, structural similarity index measure of 0.94±0.02, and Dice score coefficient of 0.81±0.07. Furthermore, the robustness of the proposed framework was found to be linked to respiratory motion. ConclusionThe proposed approach provides a novel solution to overcome the limitation of SGRT for lung cancer radiotherapy, which can potentially enable real-time volumetric imaging during radiation treatment delivery for accurate tumor tracking without radiation-induced risk. This data-driven framework offers a comprehensive solution to tackle motion management in radiotherapy, without necessitating the rigid application of first principles modeling for organ motion.

Cherenkov Imaged Bio-morphological Features Verify Patient Positioning with Deformable Tissue Translocation in Breast Radiotherapy

PurposeAccurate patient positioning is crucial for precise radiotherapy dose delivery, as errors in positioning can profoundly influence treatment outcomes. This study introduces a novel application for loco-regional tissue deformation tracking via Cherenkov image analysis, during fractionated breast cancer radiotherapy. The primary objective of this research was to develop and test an algorithmic method for Cherenkov-based position accuracy quantification, particularly for loco-regional deformations which do not have an ideal method for quantification during radiotherapy. Methods and materialsBio-morphological features in the Cherenkov images such as vessels were segmented. A rigid/non-rigid combined registration technique was employed to pinpoint both inter- and intra-fractional positioning variations. The methodology was tested on an anthropomorphic chest phantom experiment via shifting treatment couch with known distances and inducing respiratory motion, to simulate inter-fraction setup uncertainties and intra-fraction motions respectively. It was then applied to a dataset of fractionated whole breast radiotherapy human imaging (n=10 patients). ResultsThe methodology provides quantified positioning variations, comprising two components: a global shift determined through rigid registration, and a two-dimensional variation map illustrating loco-regional tissue deformation quantified via non-rigid registration. Controlled phantom testing yielded an average accuracy of 0.83 mm for couch translations up to 20 mm in various directions. Analysis of clinical Cherenkov imaging data from ten breast cancer patients compared to their first imaged fraction revealed an inter-fraction setup variation of 3.7 ± 2.4 mm in the global shift and loco-regional deformation up to 3.3 ± 1.9 mm (95th percentile of all regional deformation). ConclusionsThis study introduces the use of Cherenkov visualized bio-morphological features to quantify the global and local variations in patient positioning based on rigid and non-rigid registrations. This new approach demonstrates the feasibility to provide quantitative guidance for inter-/intra-fraction positioning, particularly for the loco-regional deformations that have been unappreciated in current practice with conventional imaging techniques.

Effect of breathing phase number on the 4D robust optimization for pancreatic cancer intensity modulated proton therapy

PurposeRespiratory movement, as one of the main challenges in proton therapy for pancreatic cancer patients, could not only lead to harm to normal tissues but also lead to failure of the tumor control, resulting in irreversible consequences. Including respiratory movements into the plan optimization, i.e. 4D robust optimization, may mitigate the interplay effect. However, 4D robust optimization considering images of all breathing phases is time-consuming and less efficient. This work aims to investigate the effect of the breathing phase number on the 4D robust optimization for pancreatic cancer intensity modulated proton therapy (IMPT) by examining plan quality and computational efficiency.MethodsA total of 15 pancreatic cancer patients were retrospectively analyzed. In this study, both anterior-fields and posterior-fields plans were created for each patient. For each plan, six four-dimensional (4D) robust treatment planning strategies with different numbers of respiratory phases and one three-dimensional (3D) treatment plan were created. Optimization of the plans were performed on all ten phases (10phase plan), two extreme phases (2phase plan), two extreme phases plus an intermediate state (3phase plan), two extreme phases plus the 3D CT (3Aphase plan), six phases during the exhalation stage (6Exphase plan), six phases during the inhalation stage (6Inphase plan) and 3D Computed Tomography (CT) scan image (3D plan), respectively. 4D dynamic dose (4DDD) was then calculated to access the interplay effect by considering respiratory motion and dynamic beam delivery. Plan quality and dosimetric parameters for the target and organs at risk (OARs) were then analyzed.ResultsCompared to the 4D plans, 3D plan performed terribly in terms of target coverage and organs at risk. Target dose in anterior-fields plan varied slightly among all six 4D treatment planning strategies. Both the 6Exphase and 6Inphase plans demonstrated performance that was comparable to the 10phase plan in target coverage, outperforming the other five plans for anterior-fields plan. It’s basically the same for the posterior-fields plan. The six strategies showed similar OARs sparing effect for both anterior-fields and posterior-fields plan. Compared with the 10phase plan, the average decline rates of the optimization time of the six plans of 2phase, 3phase, 3Aphase, 6Exphase, 6Inphase, and 3D were 73.26 ± 6.54% vs. 74.48 ± 6.63%, 65.80 ± 7.89% vs. 65.81 ± 9.58%, 54.67 ± 11.52% vs. 65.75 ± 9.58%, 42.14 ± 13.57% vs. 39.63 ± 16.93%, 37.72 ± 11.70% vs. 40.79 ± 13.62% and 75.52 ± 8.21% vs. 80.67 ± 5.62%, respectively (anterior vs. posterior). With the decrease of the number of phases selected for optimization, the decline rates increased, while the other dosimetry parameters generally showed a deterioration trend.ConclusionIn this study, a comprehensive evaluation of six 4D robust treatment planning strategies and one 3D treatment planning strategy for pancreatic cancer patients receiving IMPT was performed. The results showed that six 4D robust optimization strategies were comparable in common posterior field therapy. 2phase and 3phase (including 3Aphase) treatment planning strategies could replace the 10phase treatment planning strategy. It should be noted that patients with large motion amplitudes should receive special attention. The dosimetric performance of the 6Exphase and 6Inphase plans closely aligned with that of the 10phase plan in anterior fields. These plans offered a feasible alternative to 10phase treatment planning strategy by reducing optimization time while maintaining dose coverage of the target and protection of OARs. This research provides guidelines to reduce optimization time and improve clinical efficiency for pancreatic cancer IMPT.

Incorporating intrathoracic pressure fluctuation can improve noninvasive prediction of left ventricular end-diastolic pressure

Abstract Introduction Heart failure (HF) is a leading cause of mortality and morbidity, with a prevalence above 10% in elderly population (1). Left ventricular end-diastolic pressure (LVEDP) is a known indicator for all types of HF. An invasive pressure catheter is the gold standard for measuring LVEDP (2). However, it involves an in-hospital procedure and is costly, which limits the accessibility. A noninvasive strategy would improve early diagnosis and reduce the burden on secondary care. Several noninvasive classifiers are able to detect elevated LVEDP (3-5), with some receiving FDA clearance (6). While beneficial for triaging patients, these classifiers cannot quantify the severity and track disease progression. Developing a noninvasive LVEDP regression model requires accounting for respiration dynamics. Even invasively, the dynamics make measuring LVEDP challenging. This study uses an error metric from ANSI/AAMI/ISO 81060-2:2019 (AAMI) (7) to evaluate the effect of respiration on noninvasive LVEDP regression results. Methods The dataset (147 patients, 21+ yrs old, mean 65 ± 10 yrs; 68% male) consisted of patients referred for nonemergent left heart catheterisation inclusive of direct assessment of LVEDP. Noninvasive data was collected by a modified brachial cuff with a single-lead electrocardiogram (ECG). Invasive data was acquired using a Millar pressure catheter. LVEDP was derived based on the time of the R-wave of the ECG (8). For each patient, 40 secs of noninvasive data with synchronised catheter signals were analysed to build an LVEDP regression model. Inputs were generated from the ECG and brachial pressure waves based on fiducials identified in both signals. Leave-one-subject-out cross-validation (LOSO CV) was used to train and test the algorithm. The impact of respirophasic variation on the model was analysed by comparing the prediction with the mean LVEDP and the range of the mean ± standard deviation (std) (i.e. AAMI error metric). Results The results, evaluated using Bland-Altman and correlation analysis, showed a decrease in the mean absolute error (MAE) from 3.6 mmHg to 1.4 mmHg, the std from 4.9 mmHg to 3.0 mmHg, and the correlation (r) from 0.57 to 0.77 when incorporating intrathoracic pressure swings (Fig.1 and Fig.2). A Levene test on the residuals of the two error determinations showed a significant difference (p-value &amp;lt; 0.01). Conclusion Irrespective of the error metric, the model performance meets the AAMI standard for blood pressure (BP) measurement. Moreover, when respiratory motion is included, agreement with invasive LVEDP improves considerably. From a clinical perspective, this emphasises the importance of targeting end-expiratory LVEDP. With respect to noninvasive BP measurement, it suggests that both brachial BP evaluation and LVEDP prediction should attempt to quantify fluctuations. While the challenge remains, these results indicate that noninvasive LVEDP prediction could be realised in the near future.Fig.1 Prediction vs mean LVEDP.Fig. 2 Prediction vs mean +/- std.

Cardiac motion in patients with ventricular tachycardia: potential implications for the treatment of patients candidates to stereotactic arrhythmia radio-ablation (STAR)

Abstract Background Stereotactic arrhythmia radio-ablation (STAR) has proven to be a valid alternative treatment for refractory ventricular tachycardia (VT) in patients who are unsuitable to undergo standard catheter ablation (CA). It consists in the application of external beam radiotherapy in a single dose of 25 Gy to the target areas. There is increased research activity on better understanding the complex and fast motion of the heart and on reducing radiation toxicity. Purpose In the context of an in silico study to evaluate the feasibility of STAR with protons in patients with VT, the initial findings related to cardiac motion on the first 10 patients are here presented. Methods Prior to CA, each patient underwent ECG gated CT scans in expiratory breath-hold, with and without contrast and reconstructed at 30% (systole) and 80% (diastole) of the cardiac R-R cycle. Contouring of the ablation target as a clinical target volume (CTV) for proton treatment planning was performed based on a standard electrophysiological study with 3D eletroanatomical mapping. Two different treatment plans were created: the first with only the diastolic CTV as target (gated treatment), the second including both diastolic and systolic CTVs to create an Internal Target Volume (ITV) in the hypothesis of non-gated treatment. Robust optimization was used to create the Planning Target Volume (PTV). Results The target volumes used for treatment planning are given in Table 1. The median CTV was 10.90 (2.93-36.94) cm3 for diastole and 14.26 (1.73-36.31) cm3 for systole. These volumes are somewhat smaller than those reported in patients treated previously with STAR: this difference may be due to the fact that no respiratory motion was included in the target contour and that the study population includes many patients referred for ventricular ectopic beats without structural heart disease, where the ablation target is expected to be smaller as compared to patients with VT in structural heart disease. Despite a small median difference between the diastolic and systolic CTV of 0.53 (0.03-9.61) cm3, the ITV approach resulted in a median increase in volume compared to the largest of the two CTVs of 29 % (1%-44%). When considering the proton range uncertainty and potential errors in patient positioning (PTV), the target is this time enlarged by a factor 2.9 (1.9-3.9). This data indicates that both cardiac motion and uncertainties in patient positioning before treatment will have a large impact on the treatment volume thus affecting the amount of surrounding tissue exposed to radiation. Conclusion The ablation target contour at systole and diastole are of similar magnitude but their non-overlap results in a large increase in treated volume when radiation delivery is not gated for cardiac motion. Further analysis shall investigate on a case-by-case basis the potential reduction in risk of healthy tissue toxicity with cardiac-gated proton delivery.Table 1

Evaluation and Improving Treatment Plans of Gated Radiotherapy in Left-Sided Breast Cancer Patients Using Respiratory Motion Management System for Deep Inspiration Breath-Hold (DIBH)

Background: One essential part of treating breast cancer is radiation therapy. Patients with breast cancer are more likely to develop cardiac problems and die if they accidentally expose their hearts to radiation. In order to minimize radiation exposure to the heart, the deep inspiration breath-hold technique (DIBH) has been implemented into clinical practice. This study aimed to assess the use of the Varian Respiratory Motion Management System (RGSC) for radiation application in DIBH, with a focus on dosimetric plan comparison and treatment planning during free breathing (FB) and DIBH Methods and Material: This prospective clinical trial comprised 100 patients with left-sided breast cancer who had undergone breast-conserving surgery. Gating control and the RGS system were employed for therapy application. Analytical anisotropic algorithm (AAA) was used to generate dual treatment plans after CT data were obtained in FB and DIBH. Using the Dose Volume Histogram (DVH), dosimetric output parameters of organs at risk were compared. Results: The RGSC is connected to the LINAC systems and enables con- tinuous, touchless respiratory motion tracking using a camera. After each patient underwent dual treatment planning, 50 patients received treatment in Intensity Modulated Radiotherapy (IMRT) using DIBH, while 50 more patients received treatment in IMRT using Free Breath (FB). The mean cardiac dose reduction for DIBH in these patients was 7.23 to 3.41 Gy when compared to FB. Conclusion: The current data demonstrate that RT could greatly lower mean doses to the heart and high-dose locations by implementing the DIBH approach.

Super-resolution reconstruction of time-resolved four-dimensional computed tomography (TR-4DCT) with multiple breathing cycles based on TR-4DMRI.

Respiratory motion irregularities in lung cancer patients are common and can be severe during multi-fractional (∼20 mins/fraction) radiotherapy. However, the current clinical standard of motion management is to use a single-breath respiratory-correlated four-dimension computed tomography (RC-4DCT or 4DCT) to estimate tumor motion to delineate the internal tumor volume (ITV), covering the trajectory of tumor motion, as a treatment target. To develop a novel multi-breath time-resolved (TR) 4DCT using the super-resolution reconstruction framework with TR 4D magnetic resonance imaging (TR-4DMRI) as guidance for patient-specific breathing irregularity assessment, overcoming the shortcomings of RC-4DCT, including binning artifacts and single-breath limitations. Six lung cancer patients participated in the IRB-approved protocol study to receive multiple T1w MRI scans, besides an RC-4DCT scan on the simulation day, including 80 low-resolution (lowR: 5×5×5mm3) free-breathing (FB) 3D cine MRFB images in 40s (2Hz) and a high-resolution (highR: 2×2×2mm3) 3D breath-hold (BH) MRBH image for each patient. A CT (1×1×3mm3) image was selected from 10-bin RC-4DCT with minimal binning artifacts and a close diaphragm match (<1cm) to the MRBH image. A mutual-information-based Freeform deformable image registration (DIR) was used to register the CT and MRBH via the opposite directions (namely F1: and F2: ) to establish CT-MR voxel correspondences. An intensity-based enhanced Demons DIR was then applied for , in which the original MRBH was used in D1: , while the deformed MRBH was used in D2: . The deformation vector fields (DVFs) obtained from each DIR were composed to apply to the deformed CT (D1) and original CT (D2) to reconstruct TR-4DCT images. A digital 4D-XCAT phantom at the end of inhalation (EOI) and end of exhalation (EOE) with 2.5cm diaphragmatic motion and three spherical targets (ϕ=2, 3, 4cm) were first tested to reconstruct TR-4DCT. For each of the six patients, TR-4DCT images at the EOI, middle (MID), and EOE were reconstructed with both D1 and D2 approaches. TR-4DCT image quality was evaluated with mean distance-to-agreement (MDA) at the diaphragm compared with MRFB, tumor volume ratio (TVR) referenced to MRBH, and tumor shape difference (DICE index) compared with the selected input CT. Additionally, differences in the tumor center of mass (|∆COMD1-D2|), together with TVR and DICE comparison, was assessed in the D1 and D2 reconstructed TR-4DCT images. In the phantom, TR-4DCT quality is assessed by MDA=2.0±0.8mm at the diaphragm, TVR=0.8±0.0 for all tumors, and DICE=0.83±0.01, 0.85±0.02, 0.88±0.01 for ϕ=2, 3, 4cm tumors, respectively. In six patients, the MDA in diaphragm match is -1.6±3.1mm (D1) and 1.0±3.9mm (D2) between the reconstructed TR-4DCT and lowR MRFB among 18 images (3 phases/patient). The tumor similarity is TVR=1.2±0.2 and DICE=0.70±0.07 for D1 and TVR=1.4±0.3 (D2) and DICE=0.73±0.07 for D2. The tumor position difference is |∆COMD1-D2|=1.2±0.8mm between D1 and D2 reconstructions. The feasibility of super-resolution reconstruction of multi-breathing-cycle TR-4DCT is demonstrated and image quality at the diaphragm and tumor is assessed in both the 4D-XCAT phantom and six lung cancer patients. The similarity of D1 and D2 reconstruction suggests consistent and reliable DIR results. Clinically, TR-4DCT has the potential for breathing irregularity assessment and dosimetry evaluation in radiotherapy.

Heart Rate Estimation Considering Reconstructed Signal Features Based on Variational Mode Decomposition via Multiple-Input Multiple-Output Frequency Modulated Continuous Wave Radar.

Accurate heart rate estimation using Doppler radar and Frequency Modulated Continuous Wave (FMCW) radar is highly valued for privacy protection and the ability to measure through clothing. Conventional methods struggle to isolate the heartbeat from respiration and body motion. This paper introduces a novel heart rate estimation method using Variational Mode Decomposition (VMD) via Multiple-Input Multiple-Output (MIMO) FMCW radar. The proposed method first estimates human positions within the radar's coverage, reducing noise by focusing on signals from these positions. The signal is then decomposed into multiple Intrinsic Mode Function (IMF) signals using VMD, and the heartbeat-specific IMF is extracted based on its center frequency. The heart rate signal is reconstructed using weighted addition of IMF signals for each radar cell, with cells defined by specific angles and distances within the coverage area. Peak detection is used to estimate heart rate from these reconstructed signals. To ensure accuracy, the method selects the heart rate estimate with the highest energy and periodicity for the first four time windows. From the fifth time window onward, it selects the estimate closest to the average of the previous four, minimizing extraneous variations. Experiments conducted with one and two subjects showed promising results. In case 1, with one subject, the method achieved a Mean Absolute Error (MAE) of 2.54 BPM and an exclusion rate of 0.94% using MIMO FMCW radar, compared to 4.72% with Doppler radar. In case 2, with two subjects, the method achieved an MAE of 2.28 BPM, confirming accurate simultaneous heart rate estimation.