Institutional experience report on the target contouring workflow in the radiotherapy department for stereotactic arrhythmia radioablation delivered on conventional linear accelerators.

PURPOSE: In stereotactic arrhythmia radioablation (STAR), the target is defined using multiple imaging studies and a multidisciplinary team consisting of electrophysiologist, cardiologist, cardiac radiologist, and radiation oncologist collaborate to identify the target and delineate it on the imaging studies of interest. This report describes the workflow employed in our radiotherapy department to transfer the target identified based on electrophysiology and cardiology imaging to the treatment planning image set. METHODS: The radiotherapy team was presented with an initial target in cardiac axes orientation, contoured on a wideband late gadolinium-enhanced (WB-LGE) cardiac magnetic resonance (CMR) study, which was subsequently transferred to the computed tomography (CT) scan used for treatment planning-i.e., the average intensity projection (AIP) image set derived from a 4D CT-via an axial CMR image set, using rigid image registration focused on the target area. The cardiac and the respiratory motion of the target were resolved using ciné-CMR and 4D CT imaging studies, respectively. RESULTS: The workflow was carried out for 6 patients and resulted in an internal target defined in standard anatomical orientation that encompassed the cardiac and the respiratory motion of the initial target. CONCLUSION: An image registration-based workflow was implemented to render the STAR target on the planning image set in a consistent manner, using commercial software traditionally available for radiation therapy.

Is clinical target volume necessary for locally advanced non-small cell lung cancer treated with 4D-CT intensity-modulated radiation therapy.

BACKGROUND: A dosimetric evaluation is still lacking in terms of clinical target volume (CTV) omission in stage III patients treated with 4D-CT Intensity-Modulated Radiation Therapy (IMRT). METHODS: 49 stage III NSCLC patients received 4D-CT IMRT were reviewed. Target volumes and organs at risk (OARs) were re-delineated. Four IMRT plans were conducted retrospectively to deliver different prescribed dose (74 Gy-60 Gy), and with or without CTV implementation. Dose and volume histogram (DVH) parameters were collected and compared. RESULTS: In the PTV-g 60 Gy plan (PTV-g refers to the PTV generated from the internal gross tumor volume), only 5 of 49 patients had the isodose ≥ 50 Gy line covering at least 95% of the PTV-c (PTV-c refers to the PTV generated from the internal CTV) volume. When the prescribed dose was elevated to 74 Gy to the PTV-g, 33 of 49 patients could have the isodose ≥ 50 Gy line covering at least 95% of the PTV-c volume. In terms of OARs protection, the SIB-IMRT plan showed the lowest value of V5, V20, and mean dose of lung, had the lowest V55 of esophagus, and the lowest estimated radiation doses to immune cells (EDIC). The V20, V30, and mean dose of heart was lower in the simultaneous integrated boost (SIB) IMRT (SIB-IMRT) plan than that of the PTV-c 60 Gy plan. CONCLUSIONS: CTV omission was not suitable for stage III patients when the prescribed dose to PTV-g was 60 Gy in the era of 4D-CT IMRT. CTV omission plus high dose to PTV-g (74 Gy for example) warranted further exploration. The SIB-IMRT plan had the best protection to normal tissue including lymphocytes, and might be the optimal choice.

Development and evaluation of two open-source nnU-Net models for automatic segmentation of lung tumors on PET and CT images with and without respiratory motion compensation.

OBJECTIVES: In lung cancer, one of the main limitations for the optimal integration of the biological and anatomical information derived from Positron Emission Tomography (PET) and Computed Tomography (CT) is the time and expertise required for the evaluation of the different respiratory phases. In this study, we present two open-source models able to automatically segment lung tumors on PET and CT, with and without motion compensation. MATERIALS AND METHODS: This study involved time-bin gated (4D) and non-gated (3D) PET/CT images from two prospective lung cancer cohorts (Trials 108237 and 108472) and one retrospective. For model construction, the ground truth (GT) was defined by consensus of two experts, and the nnU-Net with 5-fold cross-validation was applied to 560 4D-images for PET and 100 3D-images for CT. The test sets included 270 4D- images and 19 3D-images for PET and 80 4D-images and 27 3D-images for CT, recruited at 10 different centres. RESULTS: In the performance evaluation with the multicentre test sets, the Dice Similarity Coefficients (DSC) obtained for our PET model were DSC(4D-PET) = 0.74 ± 0.06, improving 19% relative to the DSC between experts and DSC(3D-PET) = 0.82 ± 0.11. The performance for CT was DSC(4D-CT) = 0.61 ± 0.28 and DSC(3D-CT) = 0.63 ± 0.34, improving 4% and 15% relative to DSC between experts. CONCLUSIONS: Performance evaluation demonstrated that the automatic segmentation models have the potential to achieve accuracy comparable to manual segmentation and thus hold promise for clinical application. The resulting models can be freely downloaded and employed to support the integration of 3D- or 4D- PET/CT and to facilitate the evaluation of its impact on lung cancer clinical practice. CLINICAL RELEVANCE STATEMENT: We provide two open-source nnU-Net models for the automatic segmentation of lung tumors on PET/CT to facilitate the optimal integration of biological and anatomical information in clinical practice. The models have superior performance compared to the variability observed in manual segmentations by the different experts for images with and without motion compensation, allowing to take advantage in the clinical practice of the more accurate and robust 4D-quantification. KEY POINTS: Lung tumor segmentation on PET/CT imaging is limited by respiratory motion and manual delineation is time consuming and suffer from inter- and intra-variability. Our segmentation models had superior performance compared to the manual segmentations by different experts. Automating PET image segmentation allows for easier clinical implementation of biological information.

Which Localizing Strategy is the Most Cost-Effective in Reoperative Primary Hyperparathyroidism?

INTRODUCTION: 2%-10% of patients with primary hyperparathyroidism (PHPT) who undergo parathyroidectomy develop persistent/recurrent disease. The aim of this study was to determine which preoperative localization method is most cost-effective in reoperative PHPT. METHODS: Clinical decision analytic models comparing cost-effectiveness of localizing studies in reoperative PHPT were constructed using TreeAge Pro. Cost and probability assumptions were varied via Probabilistic Sensitivity Analysis (PSA) to test the robustness of the base case models. RESULTS: Base case analysis of model 1 revealed ultrasound (US)-guided fine-needle aspiration with PTH assay as most cost-effective after localizing US. This was confirmed on PSA of model 1. Model 2 showed four-dimensional computed tomography (4D-CT) as most cost-effective after negative US. If not localized by US, on PSA, 4D-CT was the next most cost-effective test. CONCLUSIONS: US-guided FNA with PTH is the most cost-effective confirmatory test after US localization. 4D-CT should be considered as the next best test after negative US.

Robust optimization of the Gross Tumor Volume compared to conventional Planning Target Volume-based planning in photon Stereotactic Body Radiation Therapy of lung tumors.

BACKGROUND: Robust optimization has been suggested as an approach to reduce the irradiated volume in lung Stereotactic Body Radiation Therapy (SBRT). We performed a retrospective planning study to investigate the potential benefits over Planning Target Volume (PTV)-based planning. MATERIAL AND METHODS: Thirty-nine patients had additional plans using robust optimization with 5-mm isocenter shifts of the Gross Tumor Volume (GTV) created in addition to the PTV-based plan used for treatment. The optimization included the mid-position phase and the extreme breathing phases of the 4D-CT planning scan. The plans were compared for tumor coverage, isodose volumes, and doses to Organs At Risk (OAR). Additionally, we evaluated both plans with respect to observed tumor motion using the peak tumor motion seen on the planning scan and cone-beam CTs. RESULTS: Statistically significant reductions in irradiated isodose volumes and doses to OAR were achieved with robust optimization, while preserving tumor dose. The reductions were largest for the low-dose volumes and reductions up to 188 ccm was observed. The robust evaluation based on observed peak tumor motion showed comparable target doses between the two planning methods. Accumulated mean GTV-dose was increased by a median of 4.46 Gy and a non-significant increase of 100 Monitor Units (MU) was seen in the robust optimized plans. INTERPRETATION: The robust plans required more time to prepare, and while it might not be a feasible planning strategy for all lung SBRT patients, we suggest it might be useful for selected patients.

Regional ventilation dynamics of electrical impedance tomography validated with four-dimensional computed tomography: single-center, prospective, observational study.

BACKGROUND: The dynamic regional accuracy of electrical impedance tomography has not yet been validated. We aimed to compare the regional accuracy of electrical impedance tomography with that of four-dimensional computed tomography during dynamic ventilation. METHODS: This single-center, prospective, observational study conducted in a general intensive care unit included adult patients receiving mechanical ventilation from July 2021 to February 2024. The patients were mechanically ventilated passively and underwent electrical impedance tomography and four-dimensional computed tomography on the same day. RESULTS: Overall, 45 patients were analyzed. The correlation coefficients in regional dynamic ventilation between four-dimensional computed tomography and electrical impedance tomography in each region were 0.963, 0.963, 0.835 (ventral, central, and dorsal, respectively) in the right lung and 0.947, 0.927, 0.823 (ventral, central, and dorsal, respectively) in the left lung. The correlation coefficient was low when the regional ventilation distribution detected by the electrical impedance tomography was < 2%. After excluding nine patients with a regional ventilation distribution of < 2%, the ventral, central, and dorsal correlation coefficients were 0.963, 0.963, and 0.946 in the right lung and 0.942, 0.924, and 0.951, respectively, in the left lung. CONCLUSIONS: Regional ventilation using electrical impedance tomography during dynamic ventilation was highly accurate and consistent with the time phase compared to four-dimensional computed tomography. Given the high correlation between these modalities, they can contribute significantly to further studies on regional ventilation dynamics. Trial registration number ClinicalTrials.gov (No. UMIN00044386).

Providing clinical context to the spatio-temporal analysis of 4D CT perfusion to predict acute ischemic stroke lesion outcomes.

Acute ischemic stroke is a leading cause of mortality and morbidity worldwide. Timely identification of the extent of a stroke is crucial for effective treatment, whereas spatio-temporal (4D) Computed Tomography Perfusion (CTP) imaging is playing a critical role in this process. Recently, the first deep learning-based methods that leverage the full spatio-temporal nature of perfusion imaging for predicting stroke lesion outcomes have been proposed. However, clinical information is typically not integrated into the learning process, which may be helpful to improve the tissue outcome prediction given the known influence of various factors (i.e., physiological, demographic, and treatment factors) on lesion growth. Cross-attention, a multimodal fusion strategy, has been successfully used to combine information from multiple sources, but it has yet to be applied to stroke lesion outcome prediction. Therefore, this work aimed to develop and evaluate a novel multimodal and spatio-temporal deep learning model that utilizes cross-attention to combine information from 4D CTP and clinical metadata simultaneously to predict stroke lesion outcomes. The proposed model was evaluated using a dataset of 70 acute ischemic stroke patients, demonstrating significantly improved volume estimates (mean error = 19 ml) compared to a baseline unimodal approach (mean error = 35 ml, p< 0.05). The proposed model allows generating attention maps and counterfactual outcome scenarios to investigate the relevance of clinical variables in predicting stroke lesion outcomes at a patient level, helping to provide a better understanding of the model's decision-making process.

Automatic analysis of the scapholunate distance using 4DCT imaging: normal values in the healthy wrist.

AIM: Early diagnosis of scapholunate ligament (SLL) injuries is crucial to prevent progression to debilitating osteoarthritis. Four-Dimensional Computed Tomography (4DCT) is a promising dynamic imaging modality for assessing such injuries. Capitalizing on the known correlation between SLL injuries and an increased scapholunate distance (SLD), this study aims to develop a fully automatic approach to evaluate the SLD continuously during wrist motion and to apply it to a dataset of healthy wrists to establish reference values. MATERIALS AND METHODS: 50 healthy wrists were analysed in this study. All subjects performed radioulnar deviation (RUD), flexion-extension (FE), and clenching fist (CF) movements during 4DCT acquisition. A novel, automatic method was developed to continuously compute the SLD at five distinct locations within the scapholunate joint, encompassing a centre, volar, dorsal, proximal, and distal measurement. RESULTS: The developed algorithm successfully processed datasets from all subjects. Our results showed that the SLD remained below 2 mm and exhibited minimal changes (median ranges between 0.3 mm and 0.65 mm) during RUD and CF at all measured locations. During FE, the volar and dorsal SLD changed significantly, with median ranges of 0.90 and 1.27 mm, respectively. CONCLUSION: This study establishes a unique database of normal SLD values in healthy wrists during wrist motion. Our results indicate that, aside from RUD and CF, FE may also be important in assessing wrist kinematics. Given the labour-intensive and time-consuming nature of manual analysis of 4DCT images, the introduction of this automated algorithm enhances the clinical utility of 4DCT in diagnosing dynamic wrist injuries.

Using Texture Analysis of Neck Computed Tomography Images to Differentiate Primary Hyperparathyroidism From Normal Controls.

OBJECTIVE: To investigate the utility of texture analysis in detecting osseous changes associated with hyperparathyroidism on neck CT examinations compared with control patients and to explore the best regions in the head and neck to evaluate changes in the trabecular architecture secondary to hyperparathyroidism. METHODS: Patients with hyperparathyroidism who underwent a 4D CT of the neck with contrast were included in this study. Age-matched control patients with no history of hyperparathyroidism who underwent a contrast-enhanced neck CT were also included. Mandibular condyles, bilateral mandibular bodies, the body of the C4 vertebra, the manubrium of the sternum, and bilateral clavicular heads were selected for analysis, and oval-shaped regions of interest were manually placed. These segmented areas were imported into an in-house developed texture analysis program, and 41 texture analysis features were extracted. A mixed linear regression model was used to compare differences in the texture analysis features contoured at each of the osseous structures between patients with hyperparathyroidism and age-matched control patients. RESULTS: A total of 30 patients with hyperparathyroidism and 30 age-matched control patients were included in this study. Statistically significant differences in texture features between patients with hyperparathyroidism and control patients in all 8 investigated osseous regions. The sternum showed the greatest number of texture features with statistically significant differences between these groups. CONCLUSIONS: Some CT texture features demonstrated statistically significant differences between patients with hyperparathyroidism and control patients. The results suggest that texture features may discriminate changes in the osseous architecture of the head and neck in patients with hyperparathyroidism.

Imaging Characteristics and Interpretation Strategy for Renal Hyperparathyroidism: A Retrospective 4-Dimensional Computed Tomography Study.

OBJECTIVE: Parathyroidectomy treats uncontrolled renal hyperparathyroidism (RHPT), requiring identification of all glands. Three types of enhancement are proposed. Type A lesions have higher arterial phase attenuation than the thyroid, type B lesions lack higher arterial phase attenuation but have lower venous phase attenuation, and type C lesions have neither higher arterial phase attenuation nor lower venous phase attenuation than the thyroid. We aimed to outline the image features of problematic parathyroid glands in RHPT and propose a 4-dimensional computed tomography (4DCT) interpretation algorithm. METHODS: This retrospective study involved data collection from patients with RHPT who underwent preoperative 4DCT for parathyroidectomy between January and November 2022. Pathologically confirmed parathyroid lesions were retrospectively identified on 4DCT according to the location and size described in the surgical notes. The attenuation of parathyroid lesions and the thyroid glands was assessed in 3 phases, and demographic data of the patients were collected. RESULTS: Ninety-seven pathology-proven parathyroid glands from 27 patients were obtained, with 86 retrospectively detected on 4DCT. In the arterial phase, the attenuation of parathyroid lesions in RHPT did not exceed that of the thyroid gland (P < .001). In the venous phase, parathyroid lesions demonstrated lower attenuation than the thyroid gland (P < .001). A total of 81 parathyroid lesions (94.2%) exhibited type B patterns. CONCLUSION: Unlike primary hyperparathyroidism, lesions in RHPT exhibited more type B enhancement, making them less readily identifiable in the arterial phase. Therefore, we propose a distinct imaging interpretation strategy to locate these problematic glands more efficiently.

Localization of Ectopic Hyperparathyroidism: Ultrasound Versus 99mTc-sestamibi, 4-Dimensional Computed Tomography, and 11C-choline Positron Emission Tomography/Computed Tomography.

OBJECTIVE: To investigate the usefulness of ultrasound (US) for the localization of ectopic hyperparathyroidism and compare it with 99mTc-sestamibi (99mTc-MIBI), 4-dimensional computed tomography (4D-CT), and 11C-choline positron emission tomography/ computed tomography (PET/CT). METHODS: Of the 527 patients with surgically confirmed primary hyperparathyroidism, 79 patients with ectopic hyperparathyroidism were enrolled. The diagnostic performance of US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT was calculated, and the factors affecting the sensitivity of US and 99mTc-MIBI were analyzed. RESULTS: Eighty-three ectopic parathyroid lesions were found in 79 patients. The sensitivity was 75.9%, 81.7%, 95.1%, 83.3%, and 100% for US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT, respectively. The difference in sensitivity among these different modalities did not achieve statistical significance (P > .05). The US sensitivity was significantly higher for ectopic lesions in the neck region than for those in the anterior mediastinum/chest wall (85.9% vs. 42.1%, P < .001). The 99mTc-MIBI and 4D-CT sensitivity was not significantly different between these two groups (84.1% vs. 94.6%, P = .193 and 81.3% vs. 85.7%, P = 1). The 11C-choline PET/CT sensitivity was 100% in both groups. CONCLUSIONS: US is a valuable tool for the localization of ectopic hyperparathyroidism, especially for ectopic lesions in the neck region.

Verification of acromion marker cluster and scapula spinal marker cluster methods for tracking shoulder kinematics: a comparative study with upright four-dimensional computed tomography.

BACKGROUND: This study validated the accuracy of the acromion marker cluster (AMC) and scapula spinal marker cluster (SSMC) methods compared with upright four-dimensional computed tomography (4DCT) analysis. METHODS: Sixteen shoulders of eight healthy males underwent AMC and SSMC assessments. Active shoulder elevation was tracked using upright 4DCT and optical motion capture system. The scapulothoracic and glenohumeral rotation angles calculated from AMC and SSMC were compared with 4DCT. Additionally, the motion of these marker clusters on the skin with shoulder elevation was evaluated. RESULTS: The average differences between AMC and 4DCT during 10°-140° of humerothoracic elevation were - 2.2° ± 7.5° in scapulothoracic upward rotation, 14.0° ± 7.4° in internal rotation, 6.5° ± 7.5° in posterior tilting, 3.7° ± 8.1° in glenohumeral elevation, - 8.3° ± 10.7° in external rotation, and - 8.6° ± 8.9° in anterior plane of elevation. The difference between AMC and 4DCT was significant at 120° of humerothoracic elevation in scapulothoracic upward rotation, 50° in internal rotation, 90° in posterior tilting, 120° in glenohumeral elevation, 100° in external rotation, and 100° in anterior plane of elevation. However, the average differences between SSMC and 4DCT were - 7.5 ± 7.7° in scapulothoracic upward rotation, 2.0° ± 7.0° in internal rotation, 2.3° ± 7.2° in posterior tilting, 8.8° ± 7.9° in glenohumeral elevation, 2.0° ± 9.1° in external rotation, and 1.9° ± 10.1° in anterior plane of elevation. The difference between SSMC and 4DCT was significant at 50° of humerothoracic elevation in scapulothoracic upward rotation and 60° in glenohumeral elevation, with no significant differences observed in other rotations. Skin motion was significantly smaller in AMC (28.7 ± 4.0 mm) than SSMC (38.6 ± 5.8 mm). Although there was smaller skin motion in AMC, SSMC exhibited smaller differences in scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation compared to 4DCT. CONCLUSION: This study demonstrates that AMC is more accurate for assessing scapulothoracic upward rotation and glenohumeral elevation, while SSMC is preferable for evaluating scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation, with smaller differences compared to 4DCT.

Ultrafast four-dimensional imaging of cardiac mechanical wave propagation with sparse optoacoustic sensing.

Propagation of electromechanical waves in excitable heart muscles follows complex spatiotemporal patterns holding the key to understanding life-threatening arrhythmias and other cardiac conditions. Accurate volumetric mapping of cardiac wave propagation is currently hampered by fast heart motion, particularly in small model organisms. Here we demonstrate that ultrafast four-dimensional imaging of cardiac mechanical wave propagation in entire beating murine heart can be accomplished by sparse optoacoustic sensing with high contrast, ∼115-µm spatial and submillisecond temporal resolution. We extract accurate dispersion and phase velocity maps of the cardiac waves and reveal vortex-like patterns associated with mechanical phase singularities that occur during arrhythmic events induced via burst ventricular electric stimulation. The newly introduced cardiac mapping approach is a bold step toward deciphering the complex mechanisms underlying cardiac arrhythmias and enabling precise therapeutic interventions.

Comparative evaluation of a surface-based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms.

Four-dimensional computed tomography (4DCT), which relies on breathing-induced motion, requires realistic surrogate information of breathing variations to reconstruct the tumor trajectory and motion variability of normal tissues accurately. Therefore, the SimRT surface-guided respiratory monitoring system has been installed on a Siemens CT scanner. This work evaluated the temporal and spatial accuracy of SimRT versus our commonly used pressure sensor, AZ-733 V. A dynamic thorax phantom was used to reproduce regular and irregular breathing patterns acquired by SimRT and Anzai. Various parameters of the recorded breathing patterns, including mean absolute deviations (MAD), Pearson correlations (PC), and tagging precision, were investigated and compared to ground-truth. Furthermore, 4DCT reconstructions were analyzed to assess the volume discrepancy, shape deformation and tumor trajectory. Compared to the ground-truth, SimRT more precisely reproduced the breathing patterns with a MAD range of 0.37 ± 0.27 and 0.92 ± 1.02 mm versus Anzai with 1.75 ± 1.54 and 5.85 ± 3.61 mm for regular and irregular breathing patterns, respectively. Additionally, SimRT provided a more robust PC of 0.994 ± 0.009 and 0.936 ± 0.062 for all investigated breathing patterns. Further, the peak and valley recognition were found to be more accurate and stable using SimRT. The comparison of tumor trajectories revealed discrepancies up to 7.2 and 2.3 mm for Anzai and SimRT, respectively. Moreover, volume discrepancies up to 1.71 ± 1.62% and 1.24 ± 2.02% were found for both Anzai and SimRT, respectively. SimRT was validated across various breathing patterns and showed a more precise and stable breathing tracking, (i) independent of the amplitude and period, (ii) and without placing any physical devices on the patient's body. These findings resulted in a more accurate temporal and spatial accuracy, thus leading to a more realistic 4DCT reconstruction and breathing-adapted treatment planning.

Intra- and inter-fractional variations of tumors with fiducial markers measured using respiratory-correlated computed tomography images for respiratory gated lung stereotactic body radiation therapy.

PURPOSE: This study evaluated the intra- and inter-fractional variation of tumors with fiducial markers (FMs), relative to the tumor-FM distance, to establish how close an FM should be inserted for respiratory-gated stereotactic body radiation therapy (RG-SBRT). METHODS: Forty-five lung tumors treated with RG-SBRT were enrolled. End-expiratory computed tomography (CT) (CTplan) and four-dimensional-CT (4D-CT) scans were obtained for planning. End-expiratory CT (CTfr) scanning was performed before each fraction. The FMs were divided into two groups based on the median tumor-FM distance in the CTplan (Dp). For the intra-fractional variation, the correlations between the corresponding tumor and FM intra-fractional motions, defined as the centroid coordinates of those in each 0-90% phase, with the 50% phase of 4D-CT as the origin, were calculated in the left-right, anterior-posterior, and superior-inferior directions. Furthermore, the maximum difference in the tumor-FM distance in each phase of 4D-CT scan, based on those in the 50% phase of 4D-CT scan (Dmax), was obtained. Inter-fractional variation was defined as the maximum distance between the tumors in CTplan and CTfr, when the CT scans were fused based on each FM or vertebra. RESULTS: The median Dp was 26.1 mm. While FM intra-fractional motions were significantly and strongly correlated with the tumor intra-fractional motions in only anterior-posterior and superior-inferior directions for the Dp > 26 mm group, they were significantly and strongly correlated in all directions for the Dp ≤ 26 mm group. In all directions, Dmax values of the Dp ≤ 26 mm group were lower than those of the Dp > 26 mm group. The inter-fractional variations based on the Dp ≤ 26 mm were smaller than those on the Dp > 26 mm and on the vertebra in all directions. CONCLUSIONS: Regarding intra- and inter-fractional variation, FMs for Dp ≤ 26 mm can increase the accuracy for RG-SBRT.

Deep learning based automatic internal gross target volume delineation from 4D-CT of hepatocellular carcinoma patients.

BACKGROUND: The location and morphology of the liver are significantly affected by respiratory motion. Therefore, delineating the gross target volume (GTV) based on 4D medical images is more accurate than regular 3D-CT with contrast. However, the 4D method is also more time-consuming and laborious. This study proposes a deep learning (DL) framework based on 4D-CT that can achieve automatic delineation of internal GTV. METHODS: The proposed network consists of two encoding paths, one for feature extraction of adjacent slices (spatial slices) in a specific 3D-CT sequence, and one for feature extraction of slices at the same location in three adjacent phase 3D-CT sequences (temporal slices), a feature fusion module based on an attention mechanism was proposed for fusing the temporal and spatial features. Twenty-six patients' 4D-CT, each consisting of 10 respiratory phases, were used as the dataset. The Hausdorff distance (HD95), Dice similarity coefficient (DSC), and volume difference (VD) between the manual and predicted tumor contour were computed to evaluate the model's segmentation accuracy. RESULTS: The predicted GTVs and IGTVs were compared quantitatively and visually with the ground truth. For the test dataset, the proposed method achieved a mean DSC of 0.869 ± 0.089 and an HD95 of 5.14 ± 3.34 mm for all GTVs, with under-segmented GTVs on some CT slices being compensated by GTVs on other slices, resulting in better agreement between the predicted IGTVs and the ground truth, with a mean DSC of 0.882 ± 0.085 and an HD95 of 4.88 ± 2.84 mm. The best GTV results were generally observed at the end-inspiration stage. CONCLUSIONS: Our proposed DL framework for tumor segmentation on 4D-CT datasets shows promise for fully automated delineation in the future. The promising results of this work provide impetus for its integration into the 4DCT treatment planning workflow to improve hepatocellular carcinoma radiotherapy.

Four-dimensional treatment planning strategies for dynamic tumor tracking.

INTRODUCTION: Dynamic tumor tracking (DTT) is a motion management technique where the radiation beam follows a moving tumor in real time. Not modelling DTT beam motion in the treatment planning system leaves an organ at risk (OAR) vulnerable to exceeding its dose limit. This work investigates two planning strategies for DTT plans, the "Boolean OAR Method" and the "Aperture Sorting Method," to determine if they can successfully spare an OAR while maintaining sufficient target coverage. MATERIALS AND METHODS: A step-and-shoot intensity modulated radiation therapy (sIMRT) treatment plan was re-optimized for 10 previously treated liver stereotactic ablative radiotherapy patients who each had one OAR very close to the target. Two planning strategies were investigated to determine which is more effective at sparing an OAR while maintaining target coverage: (1) the "Boolean OAR Method" created a union of an OAR's contours from two breathing phases (exhale and inhale) on the exhale phase (the planning CT) and protected this combined OAR during plan optimization, (2) the "Aperture Sorting Method" assigned apertures to the breathing phase where they contributed the least to an OAR's maximum dose. RESULTS: All 10 OARs exceeded their dose constraints on the original plan four-dimensional (4D) dose distributions and average target coverage was V100% = 91.3% ± 2.9% (ranging from 85.1% to 94.8%). The "Boolean OAR Method" spared 7/10 OARs, and mean target coverage decreased to V100% = 87.1% ± 3.8% (ranging from 80.7% to 93.7%). The "Aperture Sorting Method" spared 9/10 OARs and the mean target coverage remained high at V100% = 91.7% ± 2.8% (ranging from 84.9% to 94.5%). CONCLUSIONS: 4D planning strategies are simple to implement and can improve OAR sparing during DTT treatments. The "Boolean OAR Method" improved sparing of OARs but target coverage was reduced. The "Aperture Sorting Method" further improved sparing of OARs and maintained target coverage.

Analysis of respiratory-induced motion trajectories of individual liver segments in patients with hepatocellular carcinoma.

PURPOSE: To analyze the respiratory-induced motion trajectories of each liver segment for hepatocellular carcinoma (HCC) to derive a more accurate internal margin and optimize treatment protocol selection. MATERIALS AND METHODS: Ten-phase-gated four-dimensional computed tomography (4DCT) scans of 14 patients with HCC were analyzed. For each patient, eight representative regions of interest (ROI) were delineated on each liver segment in all 10 phases. The coordinates of the center of gravity of each ROI were obtained for each phase, and then the respiratory motion in the left-right (LR), anteroposterior (AP), and craniocaudal (CC) directions was analyzed. Two sets of motion in each direction were also compared in terms of only two extreme phases and all 10 phases. RESULTS: Motion of less than 5 mm was detected in 12 (86%) and 10 patients (71%) in the LR and AP directions, respectively, while none in the CC direction. Motion was largest in the CC direction with a maximal value of 19.5 mm, with significant differences between liver segment 7 (S7) and other segments: S1 (p < 0.036), S2 (p < 0.041), S3 (p < 0.016), S4 (p < 0.041), and S5 (p < 0.027). Of the 112 segments, hysteresis >1 mm was observed in 4 (4%), 2 (2%), and 15 (13%) in the LR, AP, and CC directions, respectively, with a maximal value of 5.0 mm in the CC direction. CONCLUSION: A significant amount of respiratory motion was detected in the CC direction, especially in S7, and S8. Despite the small effect of hysteresis, it can be observed specifically in the right lobe. Therefore, caution is required when using 4DCT to determine IM using only end-inspiration and end-expiration. Understanding the respiratory motion in individual liver segments can be helpful when selecting an appropriate treatment protocol.

Impact of abdominal compression on heart and stomach motion for stereotactic arrhythmia radioablation.

PURPOSE: To evaluate the effectiveness of abdominal compression (AC) as a respiratory motion management method for the heart and stomach during stereotactic arrhythmia radioablation (STAR). METHODS: 4D computed tomography (4DCT) scans of patients imaged with AC or without AC (free-breathing: FB) were obtained from ventricular-tachycardia (VT) (n = 3), lung cancer (n = 18), and liver cancer (n = 18) patients. Patients treated for VT were imaged both FB and with AC. Lung and liver patients were imaged once with FB or with AC, respectively. The heart, left ventricle (LV), LV components (LVCs), and stomach were contoured on each phase of the 4DCTs. Centre of mass (COM) translations in the left/right (LR), ant/post (AP), and sup/inf (SI) directions were measured for each structure. Minimum distances between LVCs and the stomach over the respiratory cycle were also measured on each 4DCT phase. Mann-Whitney U-tests were performed between AC and FB datasets with a significance of α = 0.05. RESULTS: No statistical difference (all p values were >0.05) was found in COM translations between FB and AC patient datasets for all contoured cardiac structures. A reduction in COM translation with AC relative to FB was patient, direction, and structure specific for the three VT patients. A significant decrease in the AP range of motion of the stomach was observed under AC compared to FB. No statistical difference was found between minimum distances to the stomach and LVCs between FB and AC. CONCLUSIONS: AC was not a consistent motion management method for STAR, nor does not uniformly affect the separation distance between LVCs and the stomach. If AC is employed in future STAR protocols, the motion of the target volume and its relative distance to the stomach should be compared on two 4DCTs: one while the patient is FB and one under AC.

[Dynamics Evaluation of Remodeling Operation Using 4-dimentional Computed Tomography].

OBJECTIVES: The extensibility of the aortic root after the remodeling procedure was evaluated using 4-dimentional computed tomography( 4D-CT). PATIENTS AND METHODS: Seventeen patients( 13 males/4 females), mean age 52 years, who had undergone the remodeling procedure in the last 3 years were included. To understand the dynamics of the aortic root after reconstruction, the R-R interval on the electrocardiogram was divided into 10 equal parts, and the percentage change in area of the basal ring/Valsalva sinus/sino-tubular junction (STJ) level was calculated to evaluate the extensibility of the aortic root. For the basal ring, changes in ellipticity and circumference were also compared. RESULTS: Basal ring, Valsalva sinus, and STJ area changes with cardiac cycle were similar to those in the control group. Basal ring showed a regular circle in systole and an oval in diastole, and its circumference was enlarged in systole. CONCLUSIONS: The use of 4D-CT made it possible to evaluate the extensibility of the aortic root after remodeling procedure. In particular, the mobility of the basal ring is large, suggesting that it guarantees the physiological opening and closing of the valve and contributes to its durability.