Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients

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

BACKGROUND

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.

PURPOSE

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.

METHODS

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 × 5 mm3) free-breathing (FB) 3D cine MRFB images in 40 s (2 Hz) and a high-resolution (highR: 2 × 2 × 2 mm3) 3D breath-hold (BH) MRBH image for each patient. A CT (1 × 1 × 3 mm3) image was selected from 10-bin RC-4DCT with minimal binning artifacts and a close diaphragm match (<1 cm) 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:C T Source → MR Target BH ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Source}}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{BH}}}$ and F2:C T Target ← MR Source BH ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Target}}}} \leftarrow {\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}}$ ) to establish CT-MR voxel correspondences. An intensity-based enhanced Demons DIR was then applied forMR Source BH → MR Target FB ${\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{FB}}}$ , in which the original MRBH was used in D1:C T Source → ( MR Source BH → MR Target FB ) Target ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Source}}}} \to {{({\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{FB}}})}_{{\mathrm{Target}}}}$ , while the deformed MRBH was used in D2:( C T Target ← MR Source BH ) Source → MR Target FB ${{( \text{C}{{\text{T}}_{\text{Target}}}\leftarrow \text{MR}_{\text{Source}}^{\text{BH}} )}_{\text{Source}}}\to \text{MR}_{\text{Target}}^{\text{FB}}$ . 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 2.5 cm diaphragmatic motion and three spherical targets (ϕ = 2, 3, 4 cm) 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.

RESULTS

In the phantom, TR-4DCT quality is assessed by MDA = 2.0 ± 0.8 mm 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, 4 cm tumors, respectively. In six patients, the MDA in diaphragm match is -1.6 ± 3.1 mm (D1) and 1.0 ± 3.9 mm (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 ± 0.8 mm between D1 and D2 reconstructions.

CONCLUSION

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.

Impact of breathing signal-guided dose modulation on step-and-shoot 4D CT image reconstruction

BACKGROUND

Breathing signal-guided 4D CT sequence scanning such as the intelligent 4D CT (i4DCT) approach reduces imaging artifacts compared to conventional 4D CT. By design, i4DCT captures entire breathing cycles during beam-on periods, leading to redundant projection data and increased radiation exposure to patients exhibiting prolonged exhalation phases. A recently proposed breathing-guided dose modulation (DM) algorithm promises to lower the imaging dose by temporarily reducing the CT tube current, but the impact on image reconstruction and the resulting images have not been investigated.

PURPOSE

We evaluate the impact of breathing signal-guided DM on 4D CT image reconstruction and corresponding images.

METHODS

This study is designed as a comparative and retrospective analysis based on 104 4D CT datasets. Each dataset underwent retrospective reconstruction twice: (a) utilizing the acquired clinical projection data for reconstruction, which yields reference image data, and (b) excluding projections acquired during potential DM phases from image reconstruction, resulting in DM-affected image data. Resulting images underwent automatic organ segmentation (lung/liver). (Dis)Similarity of reference and DM-affected images were quantified by the Dice coefficient of the entire organ masks and the organ overlaps within the DM-affected slices. Further, for lung cases, (a) and (b) were deformably registered and median magnitudes of the obtained displacement field were computed. Eventually, for 17 lung cases, gross tumor volumes (GTV) were recontoured on both (a) and (b). Target volume similarity was quantified by the Hausdorff distance.

RESULTS

DM resulted in a median imaging dose reduction of 15.4% (interquartile range [IQR]: 11.3%-19.9%) for the present patient cohort. Dice coefficients for lung (n = 73 $n=73$ ) and liver (n = 31 $n=31$ ) patients were consistently high for both the entire organs and the DM-affected slices (IQR lung:0.985 / 0.982 $0.985/0.982$ [entire lung/DM-affected slices only] to0.992 / 0.989 $0.992/0.989$ ; IQR liver:0.977 / 0.972 $0.977/0.972$ to0.986 / 0.986 $0.986/0.986$ ), demonstrating that DM did not cause organ distortions or alterations. Median displacements for DM-affected to reference image registration varied; however, only two out of 73 cases exhibited a median displacement larger than one isotropic 1mm 3 ${\rm mm}^3$ voxel size. The impact on GTV definition for the end-exhalation phase was also minor (median Hausdorff distance: 0.38 mm, IQR: 0.15-0.46 mm).

CONCLUSION

This study demonstrates that breathing signal-guided DM has a minimal impact on image reconstruction and image appearance while improving patient safety by reducing dose exposure.

A novel internal target volume definition based on velocity and time of respiratory target motion for external beam radiotherapy

This study aimed to develop a novel internal target volume (ITV) definition for respiratory motion targets, considering target motion velocity and time. The proposed ITV was evaluated in respiratory-gated radiotherapy. An ITV modified with target motion velocity and time (ITVvt) was defined as an ITV that includes a target motion based on target motion velocity and time. The target motion velocity was calculated using four-dimensional computed tomography (4DCT) images. The ITVvts were created from phantom and clinical 4DCT images. The phantom 4DCT images were acquired using a solid phantom that moved with a sinusoidal waveform (peak-to-peak amplitudes of 10 and 20 mm and cycles of 2-6 s). The clinical 4DCT images were obtained from eight lung cancer cases. In respiratory-gated radiotherapy, the ITVvt was compared with conventional ITVs for beam times of 0.5-2 s within the gating window. The conventional ITV was created by adding a uniform margin as the maximum motion within the gating window. In the phantom images, the maximum volume difference between the ITVvt and conventional ITV was -81.9%. In the clinical images, the maximum volume difference was -53.6%. Shorter respiratory cycles and longer BTs resulted in smaller ITVvt compared with the conventional ITV. Therefore, the proposed ITVvt plan could be used to reduce treatment volumes and doses to normal tissues.

Optimising 4D imaging of fast-oscillating structures using X-ray microtomography with retrospective gating

Imaging the internal architecture of fast-vibrating structures at micrometer scale and kilohertz frequencies poses great challenges for numerous applications, including the study of biological oscillators, mechanical testing of materials, and process engineering. Over the past decade, X-ray microtomography with retrospective gating has shown very promising advances in meeting these challenges. However, breakthroughs are still expected in acquisition and reconstruction procedures to keep improving the spatiotemporal resolution, and study the mechanics of fast-vibrating multiscale structures. Thereby, this works aims to improve this imaging technique by minimising streaking and motion blur artefacts through the optimisation of experimental parameters. For that purpose, we have coupled a numerical approach relying on tomography simulation with vibrating particles with known and ideal 3D geometry (micro-spheres or fibres) with experimental campaigns. These were carried out on soft composites, imaged in synchrotron X-ray beamlines while oscillating up to 400 Hz, thanks to a custom-developed vibromechanical device. This approach yields homogeneous angular sampling of projections and gives reliable predictions of image quality degradation due to motion blur. By overcoming several technical and scientific barriers limiting the feasibility and reproducibility of such investigations, we provide guidelines to enhance gated-CT 4D imaging for the analysis of heterogeneous, high-frequency oscillating materials.

Optimizing target and diaphragmatic configuration, and dosimetric benefits using continuous positive airway pressure in stereotactic ablative radiotherapy for lung tumors

PURPOSE

This study aimed to evaluate the impact of facilitating target delineation of continuous positive airway pressure (CPAP) in patients undergoing stereotactic ablative radiation therapy (SABR) for lung tumors by lung expansion and respiratory motion management.

MATERIALS AND METHODS

We performed a prospective single-institutional trial of patients who were diagnosed with either primary lung cancer or lung metastases and received SABR with a dose of 40 to 60 Gy in 4 fractions. Four-dimensional computed tomography simulations were conducted for each patient: once without CPAP and again with CPAP.

RESULTS

Thirty-two patients with 39 tumors were analyzed, after the withdrawal of five patients due to discomfort. For 26 tumors separated from the diaphragm, CPAP significantly increased the superoinferior distance between the tumor and the diaphragm (5.96 cm vs. 8.06 cm; p < 0.001). For 13 tumors located adjacent to the diaphragm, CPAP decreased the overlap of planning target volume (PTV) with the diaphragm significantly (6.32 cm3 vs. 4.09 cm3; p = 0.002). PTV showed a significant reduction with CPAP (25.06 cm3 vs. 22.52 cm3, p = 0.017). In dosimetric analyses, CPAP expanded lung volume by 58.4% with a significant reduction in mean dose and V5 to V40. No more than grade 2 adverse events were reported.

CONCLUSION

This trial demonstrated significant improvement of CPAP in target delineation uncertainties for lung SABR, with dosimetric benefits, a favorable safety profile and tolerability. Further investigation is warranted to explore the role of CPAP as a novel strategy for respiratory motion management.

The impact of deep-inspiration breath-hold total-body PET/CT imaging on thoracic 18F-FDG avid lesions compared with free-breathing

OBJECTIVES

To investigate PET/CT registration and quantification accuracy of thoracic lesions of a single 30-second deep-inspiration breath-hold (DIBH) technique with a total-body PET (TB-PET) scanner, and compared with free-breathing (FB) PET/CT.

METHODS

137 of the 145 prospectively enrolled patients finished a routine FB-300 s PET/CT exam and a 30-second DIBH TB-PET with chest to pelvis low dose CT. The total-body FB-300 s, FB-30 s, and DIBH-30 s PET images were reconstructed. Quantitative assessment (SUVmax and SUVmean of lung and other organs), PET/CT registration assessment and lesion analysis (SUVmax, SUVpeak, SUVmean and tumor-background ratio) were compared with Wilcoxon signed-rank tests.

RESULTS

The SUVmax and SUVmean of the lung with DIBH-30 s were significantly lower than those with FB. The distances of the liver dome between PET and CT were significantly smaller with DIBH-30 s than with FB. 195 assessable lesions in 106 patients were included, and the detection sensitivity was 97.9 % and 99.0 % in FB-300 s, and DIBH-30 s, respectively. For both small co-identified lesions (n = 86) and larger co-identified lesions with a diameter ≥ 1 cm (n = 91), the lesion SUVs were significantly greater with DIBH-30 s than with FB-300 s. Regarding lesion location, the differences of the SUVs for the lesions in the lower thorax area (n = 97, p < 0.001) were significant between DIBH-30 s and FB-300 s, while these differences were not statistically significant in the upper thorax (n = 80, p > 0.05). The lesion tumor-to-surrounding-background ratio (TsBR) was significantly increased, both in the upper and lower thorax.

CONCLUSION

The TB DIBH PET/CT technique is feasible in clinical practice. It reduces the background lung uptake and achieves better registration and lesion quantification, especially in the lower thorax.

A systematic review of 4D magnetic resonance imaging techniques for abdominal radiotherapy treatment planning

Background and purpose

Four-dimensional magnetic resonance imaging (4DMRI) has gained interest as an alternative to the current standard for motion management four-dimensional tomography (4DCT) in abdominal radiotherapy treatment planning (RTP). This review aims to assess the 4DMRI literature in abdomen, focusing on technical considerations and the validity of using 4DMRI for patients within radiotherapy protocols.

Materials and methods

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search was performed across the Medline, Embase, Scopus, and Web of Science databases, covering all years up to December 31, 2023. The studies were grouped into two categories: 4DMRI reconstructed from 3DMRI acquisition; and 4DMRI reconstructed from multi-slice 2DMRI acquisition.

Results

A total of 39 studies met the inclusion criteria and were analysed to provide key findings. Key findings were 4DMRI had the potential to improve abdominal RTP for patients by providing accurate tumour definition and motion assessment compared to 4DCT. 4DMRI reconstructed from 3DMRI acquisition showed promise as a feasible approach for motion management in abdominal RTP regarding spatial resolution. Currently,the slice thickness achieved on 4DMRI reconstructed from multi-slice 2DMRI acquisitions was unsuitable for clinical purposes. Lastly, the current barriers for clinical implementation of 4DMRI were the limited availability of validated commercial solutions and the lack of larger cohort comparative studies to 4DCT for target delineation and plan optimisation.

Conclusion

4DMRI showed potential improvements in abdominal RTP, but standards and guidelines for the use of 4DMRI in radiotherapy were required to demonstrate clinical benefits.

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656-0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237-0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images

BACKGROUND

4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability.

PURPOSE

In this work, deep learning (DL)-based conditional inpainting is proposed to restore anatomically correct image information of artifact-affected areas.

METHODS

The restoration approach consists of a two-stage process: DL-based detection of common interpolation (INT) and double structure (DS) artifacts, followed by conditional inpainting applied to the artifact areas. In this context, conditional refers to a guidance of the inpainting process by patient-specific image data to ensure anatomically reliable results. The study is based on 65 in-house 4D CT images of lung cancer patients (48 with only slight artifacts, 17 with pronounced artifacts) and two publicly available 4D CT data sets that serve as independent external test sets.

RESULTS

Automated artifact detection revealed a ROC-AUC of 0.99 for INT and of 0.97 for DS artifacts (in-house data). The proposed inpainting method decreased the average root mean squared error (RMSE) by 52 % (INT) and 59 % (DS) for the in-house data. For the external test data sets, the RMSE improvement is similar (50 % and 59 %, respectively). Applied to 4D CT data with pronounced artifacts (not part of the training set), 72 % of the detectable artifacts were removed.

CONCLUSIONS

The results highlight the potential of DL-based inpainting for restoration of artifact-affected 4D CT data. Compared to recent 4D CT inpainting and restoration approaches, the proposed methodology illustrates the advantages of exploiting patient-specific prior image information.

Motion compensated cone-beam CT reconstruction using ana priorimotion model from CT simulation: a pilot study

Objective. To combat the motion artifacts present in traditional 4D-CBCT reconstruction, an iterative technique known as the motion-compensated simultaneous algebraic reconstruction technique (MC-SART) was previously developed. MC-SART employs a 4D-CBCT reconstruction to obtain an initial model, which suffers from a lack of sufficient projections in each bin. The purpose of this study is to demonstrate the feasibility of introducing a motion model acquired during CT simulation to MC-SART, coined model-based CBCT (MB-CBCT).Approach. For each of 5 patients, we acquired 5DCTs during simulation and pre-treatment CBCTs with a simultaneous breathing surrogate. We cross-calibrated the 5DCT and CBCT breathing waveforms by matching the diaphragms and employed the 5DCT motion model parameters for MC-SART. We introduced the Amplitude Reassignment Motion Modeling technique, which measures the ability of the model to control diaphragm sharpness by reassigning projection amplitudes with varying resolution. We evaluated the sharpness of tumors and compared them between MB-CBCT and 4D-CBCT. We quantified sharpness by fitting an error function across anatomical boundaries. Furthermore, we compared our MB-CBCT approach to the traditional MC-SART approach. We evaluated MB-CBCT's robustness over time by reconstructing multiple fractions for each patient and measuring consistency in tumor centroid locations between 4D-CBCT and MB-CBCT.Main results. We found that the diaphragm sharpness rose consistently with increasing amplitude resolution for 4/5 patients. We observed consistently high image quality across multiple fractions, and observed stable tumor centroids with an average 0.74 ± 0.31 mm difference between the 4D-CBCT and MB-CBCT. Overall, vast improvements over 3D-CBCT and 4D-CBCT were demonstrated by our MB-CBCT technique in terms of both diaphragm sharpness and overall image quality.Significance. This work is an important extension of the MC-SART technique. We demonstrated the ability ofa priori5DCT models to provide motion compensation for CBCT reconstruction. We showed improvements in image quality over both 4D-CBCT and the traditional MC-SART approach.

Dosimetric Evaluation and Reproducibility of Breath-hold Plans in Intensity Modulated Proton Therapy: An Initial Clinical Experience

Purpose

Breath-hold (BH) technique can mitigate target motion, minimize target margins, reduce normal tissue doses, and lower the effect of interplay effects with intensity-modulated proton therapy (IMPT). This study presents dosimetric comparisons between BH and nonbreath-hold (non-BH) IMPT plans and investigates the reproducibility of BH plans using frequent quality assurance (QA) computed tomography scans (CT).

Methods and Materials

Data from 77 consecutive patients with liver (n = 32), mediastinal/lung (n = 21), nonliver upper abdomen (n = 20), and malignancies in the gastroesophageal junction (n = 4), that were treated with a BH spirometry system (SDX) were evaluated. All patients underwent both BH CT and 4-dimensional CT simulations. Clinically acceptable BH and non-BH plans were generated on each scan, and dose-volume histograms of the 2 plans were compared. Reproducibility of the BH plans for 30 consecutive patients was assessed using 1 to 3 QA CTs per patient and variations in dose-volume histograms for deformed target and organs at risk (OARs) volumes were compared with the initial CT plan.

Results

Use of BH scans reduced initial and boost target volumes to 72% ± 20% and 70% ± 17% of non-BH volumes, respectively. Additionally, mean dose to liver, stomach, kidney, esophagus, heart, and lung V20 were each reduced to 71% to 79% with the BH technique. Similarly, small and large bowels, heart, and spinal cord maximum doses were each lowered to 68% to 84%. Analysis of 62 QA CT scans demonstrated that mean target and OAR doses using BH scans were reproducible to within 5% of their nominal plan values.

Conclusions

The BH technique reduces the irradiated volume, leading to clinically significant reductions in OAR doses. By mitigating tumor motion, the BH technique leads to reproducible target coverage and OAR doses. Its use can reduce motion-related uncertainties that are normally associated with the treatment of thoracic and abdominal tumors and, therefore, optimize IMPT delivery.

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

Deep learning-based combination of [18F]-FDG PET and CT images for producing pulmonary perfusion image

BACKGROUND

The main application of [18F] FDG-PET (18 FDG-PET) and CT images in oncology is tumor identification and quantification. Combining PET and CT images to mine pulmonary perfusion information for functional lung avoidance radiation therapy (FLART) is desirable but remains challenging.

PURPOSE

To develop a deep-learning-based (DL) method to combine 18 FDG-PET and CT images for producing pulmonary perfusion images (PPI).

METHODS

Pulmonary technetium-99 m-labeled macroaggregated albumin SPECT (PPISPECT ), 18 FDG-PET, and CT images obtained from 53 patients were enrolled. CT and PPISPECT images were rigidly registered, and registration displacement was subsequently used to align 18 FDG-PET and PPISPECT images. The left/right lung was separated and rigidly registered again to improve the registration accuracy. A DL model based on 3D Unet architecture was constructed to directly combine multi-modality 18 FDG-PET and CT images for producing PPI (PPIDLM ). 3D Unet architecture was used as the basic architecture, and the input was expanded from a single-channel to a dual-channel to combine multi-modality images. For comparative evaluation, 18 FDG-PET images were also used alone to generate PPIDLPET . Sixty-seven samples were randomly selected for training and cross-validation, and 36 were used for testing. The Spearman correlation coefficient (rs ) and multi-scale structural similarity index measure (MS-SSIM) between PPIDLM /PPIDLPET and PPISPECT were computed to assess the statistical and perceptual image similarities. The Dice similarity coefficient (DSC) was calculated to determine the similarity between high-/low- functional lung (HFL/LFL) volumes.

RESULTS

The voxel-wise rs and MS-SSIM of PPIDLM /PPIDLPET were 0.78 ± 0.04/0.57 ± 0.03, 0.93 ± 0.01/0.89 ± 0.01 for cross-validation and 0.78 ± 0.11/0.55 ± 0.18, 0.93 ± 0.03/0.90 ± 0.04 for testing. PPIDLM /PPIDLPET achieved averaged DSC values of 0.78 ± 0.03/0.64 ± 0.02 for HFL and 0.83 ± 0.01/0.72 ± 0.03 for LFL in the training dataset and 0.77 ± 0.11/0.64 ± 0.12, 0.82 ± 0.05/0.72 ± 0.06 in the testing dataset. PPIDLM yielded a stronger correlation and higher MS-SSIM with PPISPECT than PPIDLPET (p < 0.001).

CONCLUSIONS

The DL-based method integrates lung metabolic and anatomy information for producing PPI and significantly improved the accuracy over methods based on metabolic information alone. The generated PPIDLM can be applied for pulmonary perfusion volume segmentation, which is potentially beneficial for FLART treatment plan optimization.

Dose reduction in sequence scanning 4D CT imaging through respiratory signal-guided tube current modulation: A feasibility study

BACKGROUND

Respiratory signal-guided 4D CT sequence scanning such as the recently introduced Intelligent 4D CT (i4DCT) approach reduces image artifacts compared to conventional 4D CT, especially for irregular breathing. i4DCT selects beam-on periods during scanning such that data sufficiency conditions are fulfilled for each couch position. However, covering entire breathing cycles during beam-on periods leads to redundant projection data and unnecessary dose to the patient during long exhalation phases.

PURPOSE

We propose and evaluate the feasibility of respiratory signal-guided dose modulation (i.e., temporary reduction of the CT tube current) to reduce the i4DCT imaging dose while maintaining high projection data coverage for image reconstruction.

METHODS

The study is designed as an in-silico feasibility study. Dose down- and up-regulation criteria were defined based on the patients' breathing signals and their representative breathing cycle learned before and during scanning. The evaluation (including an analysis of the impact of the dose modulation criteria parameters) was based on 510 clinical 4D CT breathing curves. Dose reduction was determined as the fraction of the downregulated dose delivery time to the overall beam-on time. Furthermore, under the assumption of a 10-phase 4D CT and amplitude-based reconstruction, beam-on periods were considered negatively affected by dose modulation if the downregulation period covered an entire phase-specific amplitude range for a specific breathing phase (i.e., no appropriate reconstruction of the phase image possible for this specific beam-on period). Corresponding phase-specific amplitude bins are subsequently denoted as compromised bins.

RESULTS

Dose modulation resulted in a median dose reduction of 10.4% (lower quartile: 7.4%, upper quartile: 13.8%, maximum: 28.6%; all values corresponding to a default parameterization of the dose modulation criteria). Compromised bins were observed in 1.0% of the beam-on periods (72 / 7370 periods) and affected 10.6% of the curves (54/510 curves). The extent of possible dose modulation depends strongly on the individual breathing patterns and is weakly correlated with the median breathing cycle length (Spearman correlation coefficient 0.22, p < 0.001). Moreover, the fraction of beam-on periods with compromised bins is weakly anti-correlated with the patient's median breathing cycle length (Spearman correlation coefficient -0.24; p < 0.001). Among the curves with the 17% longest average breathing cycles, no negatively affected beam-on periods were observed.

CONCLUSION

Respiratory signal-guided dose modulation for i4DCT imaging is feasible and promises to significantly reduce the imaging dose with little impact on projection data coverage. However, the impact on image quality remains to be investigated in a follow-up study.

Novel simulation for dosimetry impact of diaphragm respiratory motion in four-dimensional volumetric modulated arc therapy for esophageal cancer

BACKGROUND AND PURPOSE

The diaphragm respiratory motion (RM) could impact the target dose robustness in the lower esophageal cancer (EC). We aimed to develop a framework evaluating the impact of different RM patterns quantitatively in one patient, by creating virtual four-dimensional computed-tomography (v4DCT) images, which could lead to tailored treatment for the breathing pattern. We validated virtual 4D radiotherapy (v4DRT) along with exploring the acceptability of free-breathing volumetric modulated arc therapy (FB-VMAT).

METHODS AND MATERIALS

We assessed 10 patients with superficial EC through their real 4DCT (r4DCT) scans. v4DCT images were derived from the end-inhalation computed tomography (CT) image (reference CT) and the v4DRT dose was accumulated dose over all phases. r4DRT diaphragm shifts were applied with magnitudes derived from r4DCT scans; clinical target volume (CTV) dose of v4DRT was compared with that of r4DRT to validate v4DRT. CTV dosage modifications and planning organ at risk volume (PRV) margins of the spinal cord were examined with the diaphragm movement. The percentage dose differences (ΔDx) were determined between the v4DRT and the dose calculated on the reference CT image.

RESULTS

The CTV ΔDx between the r4DRT and v4DRT were within 1% in cases with RM ≦ 15 mm. The average ΔD100% and ΔDmean of the CTV ranging from 5 to 15 mm of diaphragm motion was 0.3% to 1.7% and 0.1% to 0.4%, respectively. All CTV index changes were within 3% and ΔD1cc and ΔD2cc of Cord PRV were within 1%.

CONCLUSION

We postulate a novel method for evaluating the CTV robustness, comparable to the conventional r4DCT method under the diaphragm RM ≦ 15 mm permitting an impact of within 3% in FB-VMAT for EC on the CTV dose distribution.

Assessing four-dimensional CT stress maps derived from patient-specific biomechanical models of the lung with pulmonary function test data in lung cancer patients

OBJECTIVE

This study aims to retrospectively compare the stress map of the lung with pulmonary function test (PFT) results in lung cancer patients and to evaluate the potential of the stress map as an imaging biomarker for chronic obstructive pulmonary disease (COPD).

METHODS

25 lung cancer patients with pre-treatment four-dimensional CT (4DCT) and PFT data were retrospectively analysed. PFT metrics were used to diagnose obstructive lung disease. For each patient, forced expiratory volume in 1 s (FEV1 % predicted) and the ratio of FEV1 and forced vital capacity (FEV1/FVC) were recorded. 4DCT and biomechanical model-deformable image registration (BM-DIR) were used to obtain the lung stress map. The relationship between the mean of the total lung stress and PFT data was evaluated, and the COPD classification grade was also evaluated.

RESULTS

The mean values of the total lung stress and FEV1 % predicted showed a significant strong correlation [R = 0.833, (p < 0.001)]. The mean values and FEV1/FVC showed a significant strong correlation [R = 0.805, (p < 0.001)]. For the total lung stress, the area under the curve and the optimal cut-off value were 0.94 and 510.8 Pa for the classification of normal or abnormal lung function, respectively.

CONCLUSION

This study has demonstrated the potential of lung stress maps based on BM-DIR to accurately assess lung function by comparing them with PFT data.

ADVANCES IN KNOWLEDGE

The derivation of stress map directly from 4DCT is novel method. The BM-DIR-based lung stress map can provide an accurate assessment of lung function.

A comprehensive quality assurance program for four-dimensional computed tomography in radiotherapy

This study aimed to develop and validate a comprehensive, reproducible and automatic 4DCT Quality Assurance (QA) workflow (QAMotion) that evaluates image accuracy across various regular and irregular breathing patterns. Volume and amplitude deviations, CT number accuracy, and spatial integrity were used as evaluation metrics. For repeatability tests, tolerances were respected with a mean CT number deviation < 10 HU, volume deviation < 2% and diameter and amplitude deviation < 2 mm except for irregular amplitude curves for which an amplitude deviation up to 6 mm was measured. QAMotion was able to flag image artefacts for our clinical 4DCT system.

Breathing-Adapted Imaging Techniques for Rapid 4-Dimensional Lung Tomosynthesis

Purpose

This article presents enhancements to a 4-dimensional (4D) lung digital tomosynthesis (DTS) model introduced in a 2018 paper. That model was proposed as an adjunct to 4D computed tomography (4DCT) to improve tumor localization through artifact reduction achieved by imaging the entire lung in all projections, reducing the projection collection time duration for each phase compared with 4DCT, and requiring only a single-breath cycle to capture all phases. This is applicable to SABR treatment planning. Enhancements comprise customized patient 4D-DTS x-ray scanning parameters.

Methods and Materials

Imaging parameters derived with the 4D-DTS model were arc duration, frames per second, pulse duration, and tube current normalized to single-chest radiographic milliampere-seconds (mA/mAs_AEC). Optimized phase-specific DTS projections imaging parameters were derived for volunteer respiration-tracking surrogate waveforms and for sinusoidal waveforms. These parameters are temporally matched to the respiratory surrogate waveform and presented as continuous data plots during a period of 20 seconds. Comparison is made between surrogate excursions during a single-phase CT and 4D-DTS reconstructions.

Results

4D-DTS imaging techniques were customized to volunteer respiratory waveforms and sinusoidal waveforms. Technique settings at the highest velocity portions of the volunteer waveforms were arc duration 0.066 seconds, frame rate 921 Hz, pulse duration 1.076 ms, and normalized tube current 76.2 s^-1. Technique settings at the highest velocity portions of the sinusoidal waveforms were arc duration 0.029 seconds, frame rate 2074 Hz, pulse duration 0.472 ms, and normalized tube current 173.6 s^-1. Sinusoidal surrogate excursion distance at the highest velocity portion of the waveform during a CT rotation of 0.5 seconds ranged from 2.68 to 21.09 mm, all greater than the limiting excursion distance chosen in the 4D-DTS model.

Conclusions

4D-DTS image technique settings can be customized to individual patient breathing patterns so that captured range of motion satisfies an operator-selected value.

Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images

PURPOSE

Radiation pneumonitis (RP) is dose-limiting toxicity for non-small-cell cancer (NSCLC). This study developed an RP prediction model by integrating dose-function features from computed four-dimensional computed tomography (4DCT) ventilation using the least absolute shrinkage and selection operator (LASSO).

METHODS

Between 2013 and 2020, 126 NSCLC patients were included in this study who underwent a 4DCT scan to calculate ventilation images. We computed two sets of candidate dose-function features from (1) the percentage volume receiving > 20 Gy or the mean dose on the functioning zones determined with the lower cutoff percentile ventilation value, (2) the functioning zones determined with lower and upper cutoff percentile ventilation value using 4DCT ventilation images. An RP prediction model was developed by LASSO while simultaneously determining the regression coefficient and feature selection through fivefold cross-validation.

RESULTS

We found 39.3 % of our patients had a ≥ grade 2 RP. The mean area under the curve (AUC) values for the developed models using clinical, dose-volume, and dose-function features with a lower cutoff were 0.791, and the mean AUC values with lower and upper cutoffs were 0.814. The relative regression coefficient (RRC) on dose-function features with upper and lower cutoffs revealed a relative impact of dose to each functioning zone to RP. RRCs were 0.52 for the mean dose on the functioning zone, with top 20 % of all functioning zone was two times greater than that of 0.19 for these with 60 %-80 % and 0.17 with 40 %-60 % (P < 0.01).

CONCLUSIONS

The introduction of dose-function features computed from functioning zones with lower and upper cutoffs in a machine learning framework can improve RP prediction. The RRC given by LASSO using dose-function features allows for the quantification of the RP impact of dose on each functioning zones and having the potential to support treatment planning on functional image-guided radiotherapy.

A temporo-spatial description of moving tumor and organs by the probability of presence time proportion: concept and implementation for 4D dose calculation and optimization

Objective. The binary definition of the internal target volume (ITV) artificially separates tumor from healthy organs at motion overlapping area for dose evaluation and optimization, bringing confusion about taking partial organs as tumor or adversely. In this work, the probability of presence time (PPT) proportion of a moving anatomic voxel at a geometric voxel is defined to construct a temporo-spatial description of moving objects. The geometric overlapping of tumor and organs in 3D space is distinguished by individual residence time proportion. The dose deposition at a geometric voxel is decomposed into individual dose delivered to tumor and organs for accumulative dose calculation and optimization.Approach.A novel PPT-based plan optimization strategy is proposed to generate an optimized non-uniform dose distribution based on the temporo-spatial relationship between tumor and organs.Main results.Results from a simulation study on phantoms show that the proposed method provides promising performance for surrounding organs at risk (OAR) avoidance with a reduction of mean and maximum dose at a range of 22.6%-23.1% and 23.6%-28.3% compared with ITV-based plans under different geometric conditions, while keeping the clinical target volume dose as prescription.Significance.The PPT definition constructs a unified framework to deal with the 4D temporo-spatial distribution, accumulative dose calculation and optimization of moving tumor and organs. The advantages of the PPT-based dose calculation and optimization approach are demonstrated by simulation study with significant reduction of OARs dose level compared with conventional ITV-based plan.

CArdiac and REspiratory adaptive Computed Tomography (CARE-CT): a proof-of-concept digital phantom study

Current respiratory 4DCT imaging for high-dose rate thoracic radiotherapy treatments are negatively affected by the complex interaction of cardiac and respiratory motion. We propose an imaging method to reduce artifacts caused by thoracic motion, CArdiac and REspiratory adaptive CT (CARE-CT), that monitors respiratory motion and ECG signals in real-time, triggering CT acquisition during combined cardiac and respiratory bins. Using a digital phantom, conventional 4DCT and CARE-CT acquisitions for nineteen patient-measured physiological traces were simulated. Ten respiratory bins were acquired for conventional 4DCT scans and ten respiratory bins during cardiac diastole were acquired for CARE-CT scans. Image artifacts were quantified for 10 common thoracic organs at risk (OAR) substructures using the differential normalized cross correlation between axial slices (ΔNCC), mean squared error (MSE) and sensitivity. For all images, on average, CARE-CT improved the ΔNCC for 18/19 and the MSE and sensitivity for all patient traces. The ΔNCC was reduced for all cardiac OARs (mean reduction 21%). The MSE was reduced for all OARs (mean reduction 36%). In the digital phantom study, the average scan time was increased from 1.8 ± 0.4 min to 7.5 ± 2.2 min with a reduction in average beam on time from 98 ± 28 s to 45 s using CARE-CT compared to conventional 4DCT. The proof-of-concept study indicates the potential for CARE-CT to image the thorax in real-time during the cardiac and respiratory cycle simultaneously, to reduce image artifacts for common thoracic OARs.

Experience With Normal Breathhold Planning Scans for Radiosurgery of Moving Targets With Live Tracking

PURPOSE

Utilization of breathhold scans with live tracking has a long track record of good published outcomes for stereotactic body radiation therapy (SBRT) and is recommended by the manufacturer of the Synchrony tracking system. However, the popularity of four-dimensional computed tomography (4DCT) scans challenges the validity of the breathhold scan with live tracking technique. Although this study is not intended to prove the superiority of either method, we demonstrate the feasibility of using the breathhold scans with a phantom test and clinical examples.

METHODS

A 4DCT of a perfect sphere was scanned at 20 breaths per minute and compared to a 4DCT of a small lung tumor in one patient and a 4DCT of a larger renal tumor in another patient, as well as to fiducial matching in a patient with pancreatic cancer. Normal exhale and normal inhale breathhold CT scans were performed for the pancreatic cancer patient, combined with Synchrony tracking on CyberKnife (Sunnyvale, CA: Accuray) for treatment.

RESULTS

The 4DCT scan of the phantom exhibited considerable apparent deformation, which must be entirely due to imaging artifact since the perfect sphere in the phantom is known to be completely rigid. The 4DCT of the lung and renal tumors in patients had similar apparent deformation. Usually in patients, from 4DCT alone, it is difficult to determine how much was due to deformation and how much was due to artifact. Fiducial positions in the final normal exhale and normal inhale breathhold scans for Synchrony matched each other within 1mm for the pancreatic cancer patient.

CONCLUSION

We demonstrated the feasibility of breathhold scans with Synchrony live tracking, as recommended by the manufacturer. More studies will be needed to determine whether this method is better than using a 4DCT.

A study of quantitative indicators for slice sorting in cine-mode 4DCT

The uncertainties of four-dimensional computed tomography (4DCT), also called as residual motion artefacts (RMA), induced from irregular respiratory patterns can degrade the quality of overall radiotherapy. This study aims to quantify and reduce those uncertainties. A comparative study on quantitative indicators for RMA was performed, and based on this, we proposed a new 4DCT sorting method that is applicable without disrupting the current clinical workflow. In addition to the default phase sorting strategy, both additional amplitude information from external surrogates and the quantitative metric for RMA, investigated in this study, were introduced. The comparison of quantitative indicators and the performance of the proposed sorting method were evaluated via 10 cases of breath-hold (BH) CT and 30 cases of 4DCT. It was confirmed that N-RMSD (normalised root-mean-square-deviation) was best matched to the visual standards of our institute’s regime, manual sorting method, and could accurately represent RMA. The performance of the proposed method to reduce 4DCT uncertainties was improved by about 18.8% in the averaged value of N-RMSD compared to the default phase sorting method. To the best of our knowledge, this is the first study that evaluates RMA indicators using both BHCT and 4DCT with visual-criteria-based manual sorting and proposes an improved 4DCT sorting strategy based on them.

Quality assurance of a breathing controlled four-dimensional computed tomography algorithm

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Initial quality assurance of a novel breathing-controlled four-dimensional computed tomography algorithm.

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Assessment of geometry, motion representation and image quality for regular and irregular breathing.

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No clinically relevant differences in results for regular and irregular breathing.

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Only minor differences in tumor geometry representation and image quality compared to static three-dimensional computed tomography.

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Table flexion has no clinically relevant impact on geometry representation.

Background & purpose

Material & methods

Results

Conclusions

Technical note: Institutional solution of clinical cine MRI for tumor motion evaluation in radiotherapy

PURPOSE

Since 4D-MRI is inadequate to capture dynamic respiratory variations, real-time cinematographic (cine) MRI is actively used in MR-guided radiotherapy (MRgRT) for tumor motion evaluation, delineation, and tracking. However, most radiotherapy imaging platforms do not support the format of cine MRI from clinical MRI systems. This study developed an institutional solution of clinical cine MRI for tumor motion evaluation in radiotherapy applications.

METHODS

Cine MRI manipulation software (called Cine Viewer) was developed within a commercial Treatment Planning System (TPS). It consists of (1) single/orthogonal viewers, (2) display controllers, (3) measurement grids/markers, and (4) manual contouring tools.

RESULTS

The institutional solution of clinical cine MRI incorporated with radiotherapy application was assessed through case presentations (liver cancer). Cine Viewer loaded cine MRIs from 1.5T Philips Ingenia MRI, handling MRI DICOM format. The measurement grids and markers were used to quantify the displacement of anatomical structures in addition to the tumor. The contouring tool was utilized to localize the tumor and surrogates on the designated frame. The stacks of the contours were exhibited to present the ranges of tumor and surrogate motions. For example, the stacks of the tumor contours from case-1 were used to determine the ranges of tumor motions (∼8.17 mm on the x-direction [AP-direction] and ∼14 mm on the y-direction [SI-direction]). In addition, the patterns of the displacement of the contours over frames were analyzed and reported using in-house software. In the case-1 review, the tumor was displaced from +146.0 mm on the x-direction and +125.0 mm on the y-direction from the ROI of the abdominal surface.

CONCLUSION

We demonstrated the institutional solution of clinical cine MRI in radiotherapy. The proposed tools can streamline the utilization of cine MRI for tumor motion evaluation using Eclipse for treatment planning.

Improving the accuracy of motion quantification using area detector computed tomography for real-time tumor-tracking irradiation in stereotactic ablative radiotherapy

CyberKnife radiotherapy enables tumor-tracking irradiation using positional information regarding the tumor and a fiducial marker in a patient's body. This positional information acts as a surrogate of tumor motion. Therefore, deviations in these movements should be quantitatively estimated and included as an internal margin for radiation treatment planning. This study aimed to investigate variations between the positions of fiducial markers and tumor regions using 320-row area detector computed tomography and to analyze the effectiveness of our proposed method in contouring tumor regions based on the fiducial marker position. To determine the moving tumor volume, a typical single-phase image was selected, and pixel values in other phase images were accumulated. Moreover, a maximum-intensity projection image was created to clarify motion deviations in the tumor volume. To evaluate the delineation accuracy, the dice similarity coefficient and mean distance to agreement were calculated in phase-selected and breath-holding computed tomography. Moving chest phantom images were acquired using helical scanning 4-dimensional computed tomography (H-4DCT) and volumetric scanning 4-dimensional computed tomography (V-4DCT), and the delineation accuracies were compared for each scanning type. The average dice similarity coefficient and mean distance to agreement were degraded in limited-phase images, which cannot represent the hysteretic motion of a tumor. Moreover, deviations in tumor volume with unstable motion reached 71.6% in H-4DCT but only 1.6% in V-4DCT. Our proposed method with V-4DCT using area detector computed tomography can achieve accurate moving tumor delineation and can clarify positional associations between the fiducial marker and tumor under respiratory motion.

Abdominal motion tracking with free-breathing XD-GRASP acquisitions using spatio-temporal geodesic trajectories

Free-breathing external beam radiotherapy remains challenging due to the complex elastic or irregular motion of abdominal organs, as imaging moving organs leads to the creation of motion blurring artifacts. In this paper, we propose a radial-based MRI reconstruction method from 3D free-breathing abdominal data using spatio-temporal geodesic trajectories, to quantify motion during radiotherapy. The prospective study was approved by the institutional review board and consent was obtained from all participants. A total of 25 healthy volunteers, 12 women and 13 men (38 years ± 12 [standard deviation]), and 11 liver cancer patients underwent imaging using a 3.0 T clinical MRI system. The radial acquisition based on golden-angle sparse sampling was performed using a 3D stack-of-stars gradient-echo sequence and reconstructed using a discretized piecewise spatio-temporal trajectory defined in a low-dimensional embedding, which tracks the inhale and exhale phases, allowing the separation between distinct motion phases. Liver displacement between phases as measured with the proposed radial approach based on the deformation vector fields was compared to a navigator-based approach. Images reconstructed with the proposed technique with 20 motion states and registered with the multiscale B-spline approach received on average the highest Likert scores for the overall image quality and visual SNR score 3.2 ± 0.3 (mean ± standard deviation), with liver displacement errors varying between 0.1 and 2.0 mm (mean 0.8 ± 0.6 mm). When compared to navigator-based approaches, the proposed method yields similar deformation vector field magnitudes and angle distributions, and with improved reconstruction accuracy based on mean squared errors. Schematic illustration of the proposed 4D-MRI reconstruction method based on radial golden-angle acquisitions and a respiration motion model from a manifold embedding used for motion tracking. First, data is extracted from the center of k-space using golden-angle sampling, which is then mapped onto a low-dimensional embedding, describing the relationship between neighboring samples in the breathing cycle. The trained model is then used to extract the respiratory motion signal for slice re-ordering. The process then improves the image quality through deformable image registration. Using a reference volume, the deformation vector field (DVF) of sequential motion states are extracted, followed by deformable registrations. The output is a 4DMRI which allows to visualize and quantify motion during free-breathing.

First clinical evaluation of breathing controlled four-dimensional computed tomography imaging

Background and Purpose

Four-dimensional computed tomography (4DCT) has become an essential part of radiotherapy planning but is often affected by artifacts. A new breathing controlled 4DCT (i4DCT) algorithm has been introduced. This study aims to present the first clinical data and to evaluate the achieved image quality, projection data coverage and beam-on time.

Material & Methods

The analysis included i4DCT data for 129 scans of patients with thoracic tumors. Projection data coverage and beam-on time were evaluated. Additionally, image quality was exemplarily discussed and rated by ten clinical experts with a 5-score-scale for 30 patients with large variations in their breathing pattern (‘challenging subgroup’). Rated images were reconstructed amplitude- and phase-based.

Results

Expert scoring revealed that 78% (amplitude-based) and 63% (phase-based) of the challenging subgroup were artifact-free (rating ≥4). For the entire cohort, average beam-on time per couch position was 4.9 ± 1.6 s. For the challenging subgroup, time increased slightly but not significantly compared to the remaining patients (5.1 s vs. 4.9 s; p = 0.64). Median projection data coverage was 93% and 94% for inhalation and exhalation, respectively, for the entire cohort. The comparison for the subgroup and the remaining patients revealed a small but significant decrease of the median coverage values for the challenging cases (inhalation: 90% vs. 94%, p = 0.02; exhalation: 93% vs. 94%, p = 0.02).

Conclusions

This first clinical evaluation of i4DCT shows very promising results in terms of image quality and projection data coverage. The results agree with and support the results of previous i4DCT phantom studies.

Lung-CRNet: A convolutional recurrent neural network for lung 4DCT image registration

PURPOSE

Deformable image registration (DIR) of lung four-dimensional computed tomography (4DCT) plays a vital role in a wide range of clinical applications. Most of the existing deep learning-based lung 4DCT DIR methods focus on pairwise registration which aims to register two images with large deformation. However, the temporal continuities of deformation fields between phases are ignored. This paper proposes a fast and accurate deep learning-based lung 4DCT DIR approach that leverages the temporal component of 4DCT images.

METHODS

We present Lung-CRNet, an end-to-end convolutional recurrent registration neural network for lung 4DCT images and reformulate 4DCT DIR as a spatiotemporal sequence predicting problem in which the input is a sequence of three-dimensional computed tomography images from the inspiratory phase to the expiratory phase in a respiratory cycle. The first phase in the sequence is selected as the only reference image and the rest as moving images. Multiple convolutional gated recurrent units (ConvGRUs) are stacked to capture the temporal clues between images. The proposed network is trained in an unsupervised way using a spatial transformer layer. During inference, Lung-CRNet is able to yield the respective displacement field for each reference-moving image pair in the input sequence.

RESULTS

We have trained the proposed network using a publicly available lung 4DCT dataset and evaluated performance on the widely used the DIR-Lab dataset. The mean and standard deviation of target registration error are 1.56 ± 1.05 mm on the DIR-Lab dataset. The computation time for each forward prediction is less than 1 s on average.

CONCLUSIONS

The proposed Lung-CRNet is comparable to the existing state-of-the-art deep learning-based 4DCT DIR methods in both accuracy and speed. Additionally, the architecture of Lung-CRNet can be generalized to suit other groupwise registration tasks which align multiple images simultaneously.

Comparative Evaluation of 4-Dimensional Computed Tomography and 4-Dimensional Magnetic Resonance Imaging to Delineate the Target of Primary Liver Cancer

Purpose: To evaluate the feasibility of 4-dimensional magnetic resonance imaging (4DMRI) in establishing the target of primary liver cancer in comparison with 4-dimensional computed tomography (4DCT). Methods and Materials: A total of 23 patients with primary liver cancer who received radiotherapy were selected, and 4DCT and T2w-4DMRI simulations were conducted to obtain 4DCT and T2w-4DMRI simulation images. The 4DCT and T2w-4DMRI data were sorted into 10 and 8 respiratory phase bins, respectively. The liver and gross tumor volumes (GTVs) were delineated in all images using programmed clinical workflows under tumor delineation guidelines. The internal organs at risk volumes (IRVs) and internal target volumes (ITVs) were the unions of all the phase livers and GTVs, respectively. Then, the artifacts, liver volume, GTV, and motion range in 4DCT and T2w-4DMRI were compared. Results: The mean GTV volume based on 4DMRI was 136.42 ± 231.27 cm³, which was 25.04 cm³ (15.5%) less than that of 4DCT (161.46 ± 280.29 cm³). The average volume of ITV determined by 4DMRI was 166.12 ± 270.43 cm³, which was 22.44 cm³ (11.9%) less than that determined by 4DCT (188.56 ± 307.57 cm³). Liver volume and IRV in 4DMRI increased by 4.0% and 6.6%, respectively, compared with 4DCT. The difference in tumor motion by T2w-4DMRI based on the centroid was greater than that of 4DCT in the L/R, A/P, and S/I directions, and the average displacement differences were 2.6, 2.8, and 6.9 mm, respectively. The severe artifacts in 4DCT were 47.8% (11/23) greater than in 4DMRI 17.4% (4/23). Conclusions: Compared with 4DCT, T2-weighted and navigator-triggered 4DMRI produces fewer artifacts and larger motion differences in hepatic intrafraction tumors, which is a feasible technique for primary liver cancer treatment planning.

Evaluation of four surface surrogates for modeling lung tumor positions over several fractions in radiotherapy

Patient breathing during lung cancer radiotherapy reduces the ability to keep a sharp dose gradient between tumor and normal tissues. To mitigate detrimental effects, accurate information about the tumor position is required. In this work, we evaluate the errors in modeled tumor positions over several fractions of a simple tumor motion model driven by a surface surrogate measure and its time derivative. The model is tested with respect to four different surface surrogates and a varying number of surrogate and image acquisitions used for model training. Fourteen patients were imaged 100 times with cine CT, at three sessions mimicking a planning session followed by two treatment fractions. Patient body contours were concurrently detected by a body surface laser scanning system BSLS from which four surface surrogates were extracted; thoracic point TP, abdominal point AP, the radial distance mean RDM, and a surface derived volume SDV. The motion model was trained on session 1 and evaluated on sessions 2 and 3 by comparing modeled tumor positions with measured positions from the cine images. The number of concurrent surrogate and image acquisitions used in the training set was varied, and its impact on the final result was evaluated. The use of AP as a surface surrogate yielded the smallest error in modeled tumor positions. The mean deviation between modeled and measured tumor positions was 1.9 mm. The corresponding deviations for using the other surrogates were 2.0 mm (RDM), 2.8 mm (SDV), and 3.0 mm (TP). To produce a motion model that accurately models the tumor position over several fractions requires at least 10 simultaneous surrogate and image acquisitions over 1–2 minutes.

Technical Note: Volumetric computed tomography for radiotherapy simulation and treatment planning

Purpose

For lung and liver tumors requiring radiotherapy, motion artifacts are common in 4D‐CT images due to the small axial field‐of‐view (aFOV) of conventional CT scanners. This may negatively impact contouring and dose calculation accuracy and could lead to a geographic miss during treatment. Recent advancements in volumetric CT (vCT) enable an aFOV up to 160 mm in a single rotation, which may reduce motion artifacts. However, the impact of large aFOV on CT number required for dose calculation needs to be evaluated before clinical implementation. The objective of this study was to determine the utility of a 256‐slice vCT scanner for 4D‐CT simulation by evaluating image quality and generating relative electron density (RED) curves.

Methods

Images were acquired on a 256‐slice GE Revolution CT scanner with 40 mm, 80 mm, 120 mm, 140 mm, and 160 mm aFOV. Image quality was assessed by evaluating CT number linearity, uniformity, noise, and low‐contrast resolution. The relationship between each quality metric and aFOV was assessed.

Results

CT number linearity, uniformity, noise, and low‐contrast resolution were within the expected range for each image set, except CT number in Teflon and Delrin, which were underestimated. Spearman correlation coefficient (ρ) showed that the CT number for Teflon (ρ = 1.0, p = 0.02), Delrin (ρ = 1.0, p = 0.02), and air (ρ = 1.0, p = 0.02) was significantly related to aFOV, while all other measurements were not. The measured deviations from expected values were not clinically significant.

Conclusion

These results suggest that vCT can be used for CT simulation for radiation treatment planning.

Residual Set Up Errors of the Surrogate-guided Registration Using Four-dimensional CT Images and Breath Holding Ones in Respiratory Gated Radiotherapy for Liver Cancer

BACKGROUND/AIM

To evaluate the surrogate-guided registration accuracy of two computed tomography (CT) image sets, expiratory phase four-dimensional (Ex4D) CT and breath-holding CT (BHCT), in respiratory-gated radiotherapy for liver cancer.

MATERIALS AND METHODS

The surrogate-guided registration errors were defined as the differences between the diaphragm- and fiducial-guided registrations or the differences between upper and lower fiducial registrations in three directions: left-right (LR), anterior-posterior (AP), and cranio-caudal (CC).

RESULTS

The mean±SDs of the absolute errors for diaphragm-guided registration were 1.9±1.3, 2.7±1.8, and 2.6±1.7 mm with Ex4D and 1.8±1.8, 2.6±1.9, and 1.8±1.7 mm with BHCT in the LR, AP and CC directions, respectively (CC direction, p<0.01). In the fiducial-guided registration, there were no significant differences in any direction. In registration with Ex4D, there were positive correlations between registration errors and the respiratory irregularity during 4D scanning (correlation coefficient; diaphragm: 0.65, fiducial: 0.54).

CONCLUSION

BHCT has the advantage of accurate surrogate-guided registration compared with Ex4D.

Quantifying inter- and intra-fraction variations of breast cancer radiotherapy with skin dose measurements

Aim. The aim of the current study was to compare between the deep inspiration breath-hold (DIBH) technique and free-breathing (FB) method in the treatment delivery uncertainty of breast cancer radiotherapy using skin dose measurements.Methods. In a prospective manner, eighty patients were randomly selected for skin dose measurements, and they were assigned to two groups. DIBH (40 patients) and FB (40 patients). The systematic inter-fraction dose variation was quantified using the mean percentage error (MPE) between the average measured total dose per session in three consecutive sessions and the corresponding calculated point dose from the treatment planning system. The random inter-fraction dose variation was quantified using the standard deviation (SD) of the dose delivered by the medial or lateral tangential fields, or the total session dose in the three sessions (SD_MT, SD_LT, or SD_total, respectively). While the random intra-fraction dose variation was quantified using the SD of the dose difference between the medial and lateral tangential fields in three consecutive sessions (SD_MT-LT).Results. There was no statistically significant difference in MPE between the DIBH and FB groups (p = 0.583). Moreover, the mean SD_totaland SD_MTof the DIBH group were significantly lower than that of the FB group (2.75 ± 2.33 cGy versus 4.45 cGy ± 4.33, p = 0.048) and (1.94 ± 1.63 cGy versus 3.76 ± 3.42 cGy, p = 0.007), respectively. However, there was no significant difference in the mean SD_LTand SD_MT-LTbetween the two groups (p > 0.05).Conclusion. In addition to the advantage of reducing the cardiopulmonary radiation doses in left breast cancer, the DIBH technique could reduce the treatment delivery uncertainty compared to the FB method due to the significant reduction in the random inter-fraction dose variations.

Technical Note: Multiple energy extraction techniques for synchrotron-based proton delivery systems may exacerbate motion interplay effects in lung cancer treatments

PURPOSE

The multiple energy extraction (MEE) delivery technique for synchrotron-based proton delivery systems reduces beam delivery time by decelerating the beam multiple times during one accelerator spill, but this might cause additional plan quality degradation due to intrafractional motion. We seek to determine whether MEE causes significantly different plan quality degradation compared to single energy extraction (SEE) for lung cancer treatments due to the interplay effect.

METHODS

Ten lung cancer patients treated with IMPT at our institution were nonrandomly sampled based on a representative range of tumor motion amplitudes, tumor volumes, and respiratory periods. Dose-volume histogram (DVH) indices from single-fraction SEE and MEE four-dimensional (4D) dynamic dose distributions were compared using the Wilcoxon signed-rank test. Distributions of monitor units (MU) to breathing phases were investigated for features associated with plan quality degradation. SEE and MEE DVH indices were compared in fractionated deliveries of the worst-case patient treatment scenario to evaluate the impact of fractionation.

RESULTS

There were no clinically significant differences in target mean dose, target dose conformity, or dose to organs-at-risk between SEE and MEE in single-fraction delivery. Three patients had significantly worse dose homogeneity with MEE compared to SEE (single-fraction mean D_5% -D_95% increased by up to 9.6% of prescription dose), and plots of MU distribution to breathing phases showed synchronization patterns with MEE but not SEE. However, after 30 fractions the patient in the worst-case scenario had clinically acceptable target dose homogeneity and coverage with MEE (mean D_5% -D_95% increased by 1% compared to SEE).

CONCLUSIONS

For some patients with breathing periods close to the mean spill duration, MEE resulted in significantly worse single-fraction target dose homogeneity compared to SEE due to the interplay effect. However, this was mitigated by fractionation, and target dose homogeneity and coverage were clinically acceptable after 30 fractions with MEE.

Technical Note: 4D robust optimization in small spot intensity-modulated proton therapy (IMPT) for distal esophageal carcinoma

PURPOSE

To compare the dosimetric performances of small-spot three-dimensional (3D) and four-dimensional (4D) robustly optimized intensity-modulated proton (IMPT) plans in the presence of uncertainties and interplay effect simultaneously for distal esophageal carcinoma.

METHOD AND MATERIALS

Thirteen (13) patients were selected and re-planned with small-spot ( σ  ~ 2-6 mm) 3D and 4D robust optimization in IMPT, respectively. The internal clinical target volumes (CTV_high3d , CTV_low3d ) were used in 3D robust optimization. Different CTVs (CTV_high4d , CTV_low4d ) were generated by subtracting an inner margin of the motion amplitudes in three cardinal directions from the internal CTVs and used in 4D robust optimization. All patients were prescribed the same dose to CTVs (50 Gy[RBE] for CTV_high3d /CTV_high4d and 45 Gy[RBE] for CTV_low3d /CTV_low4d ). Dose-volume histogram (DVH) indices were calculated to assess plan quality. Comprehensive plan robustness evaluations that consisted of 300 perturbed scenarios (10 different motion patterns to consider irregular motion (sampled from a Gaussian distribution) and 30 different uncertainties scenarios (sampled from a 4D uniform distribution) combined), were performed to quantify robustness to uncertainties and interplay effect simultaneously. Wilcoxon signed-rank test was used for statistical analysis.

RESULTS

Compared to 3D robustly optimized plans, 4D robustly optimized plans had statistically improved target coverage and better sparing of lungs and heart (heart D_mean , P = 0.001; heart V_30Gy[RBE] , P = 0.001) in the nominal scenario. 4D robustly optimized plans had better robustness in target dose coverage (CTV_high4d V_100% , P = 0.002) and the protection of lungs and heart (heart D_mean , P = 0.001; heart V_30Gy[RBE] , P = 0.001) when uncertainties and interplay effect were considered simultaneously.

CONCLUSIONS

Even with small spots in IMPT, 4D robust optimization outperformed 3D robust optimization in terms of normal tissue protection and robustness to uncertainties and interplay effect simultaneously. Our findings support the use of 4D robust optimization to treat distal esophageal carcinoma with small spots in IMPT.

Geodesic density regression for correcting 4DCT pulmonary respiratory motion artifacts

Pulmonary respiratory motion artifacts are common in four-dimensional computed tomography (4DCT) of lungs and are caused by missing, duplicated, and misaligned image data. This paper presents a geodesic density regression (GDR) algorithm to correct motion artifacts in 4DCT by correcting artifacts in one breathing phase with artifact-free data from corresponding regions of other breathing phases. The GDR algorithm estimates an artifact-free lung template image and a smooth, dense, 4D (space plus time) vector field that deforms the template image to each breathing phase to produce an artifact-free 4DCT scan. Correspondences are estimated by accounting for the local tissue density change associated with air entering and leaving the lungs, and using binary artifact masks to exclude regions with artifacts from image regression. The artifact-free lung template image is generated by mapping the artifact-free regions of each phase volume to a common reference coordinate system using the estimated correspondences and then averaging. This procedure generates a fixed view of the lung with an improved signal-to-noise ratio. The GDR algorithm was evaluated and compared to a state-of-the-art geodesic intensity regression (GIR) algorithm using simulated CT time-series and 4DCT scans with clinically observed motion artifacts. The simulation shows that the GDR algorithm has achieved significantly more accurate Jacobian images and sharper template images, and is less sensitive to data dropout than the GIR algorithm. We also demonstrate that the GDR algorithm is more effective than the GIR algorithm for removing clinically observed motion artifacts in treatment planning 4DCT scans. Our code is freely available at https://github.com/Wei-Shao-Reg/GDR.

Optimising use of 4D-CT phase information for radiomics analysis in lung cancer patients treated with stereotactic body radiotherapy

Purpose. 4D-CT is routine imaging for lung cancer patients treated with stereotactic body radiotherapy. No studies have investigated optimal 4D phase selection for radiomics. We aim to determine how phase data should be used to identify prognostic biomarkers for distant failure, and test whether stability assessment is required. A phase selection approach will be developed to aid studies with different 4D protocols and account for patient differences. Methods. 186 features were extracted from the tumour and peritumour on all phases for 258 patients. Feature values were selected from phase features using four methods: (A) mean across phases, (B) median across phases, (C) 50% phase, and (D) the most stable phase (closest in value to two neighbours), coined personalised selection. Four levels of stability assessment were also analysed, with inclusion of: (1) all features, (2) stable features across all phases, (3) stable features across phase and neighbour phases, and (4) features averaged over neighbour phases. Clinical-radiomics models were built for twelve combinations of feature type and assessment method. Model performance was assessed by concordance index (c-index) and fraction of new information from radiomic features. Results. The most stable phase spanned the whole range but was most often near exhale. All radiomic signatures provided new information for distant failure prediction. The personalised model had the highest c-index (0.77), and 58% of new information was provided by radiomic features when no stability assessment was performed. Conclusion. The most stable phase varies per-patient and selecting this improves model performance compared to standard methods. We advise the single most stable phase should be determined by minimising feature differences to neighbour phases. Stability assessment over all phases decreases performance by excessively removing features. Instead, averaging of neighbour phases should be used when stability is of concern. The models suggest that higher peritumoural intensity predicts distant failure.

Gated Radiotherapy Development and its Expansion

One of the most important challenges in treatment of patients with cancerous tumors of chest and abdominal areas is organ movement. The delivery of treatment radiation doses to tumor tissue is a challenging matter while protecting healthy and radio sensitive tissues. Since the movement of organs due to respiration causes a discrepancy in the middle of planned and delivered dose distributions. The moderation in the fatalistic effect of intra-fractional target travel on the radiation therapy correctness is necessary for cutting-edge methods of motion remote monitoring and cancerous growth irradiancy. Tracking respiratory milling and implementation of breath-hold techniques by respiratory gating systems have been used for compensation of respiratory motion negative effects. Therefore, these systems help us to deliver precise treatments and also protect healthy and critical organs. It seems aspiration should be kept under observation all over treatment period employing tracking seed markers (e.g. fiducials), skin surface scanners (e.g. camera and laser monitoring systems) and aspiration detectors (e.g. spirometers). However, these systems are not readily available for most radiotherapy centers around the word. It is believed that providing and expanding the required equipment, gated radiotherapy will be a routine technique for treatment of chest and abdominal tumors in all clinical radiotherapy centers in the world by considering benefits of respiratory gating techniques in increasing efficiency of patient treatment in the near future. This review explains the different technologies and systems as well as some strategies available for motion management in radiotherapy centers.

Evaluation of irregular breathing effects on internal target volume definition for lung cancer radiotherapy

PURPOSE

Irregular breathing may compromise the treated volume for free-breathing lung cancer patients during radiotherapy. We try to find a measure based on a breathing amplitude surrogate that can be used to select the patients who need further investigation of tumor motion to ensure that the internal target volume (ITV) provides reliant coverage of the tumor.

MATERIAL AND METHODS

Fourteen patients were scanned with four-dimensional computed tomography (4DCT) during free-breathing. The breathing motion was detected by a pneumatic bellows device used as a breathing amplitude surrogate. In addition to the 4DCT, a breath-hold (BH) scan and three cine CT imaging sessions were acquired. The cine images were taken at randomized intervals at a rate of 12 per minute for 8 minutes to allow tumor motion determination during a typical hypo-fractionated treatment scenario. A clinical target volume (CTV) was segmented in the BH CT and propagated over all cine images and 4DCT bins. The center-of-volume of the translated CTV (CTV_COV ) in the ten 4DCT bins were interconnected to define the 4DCT determined tumor trajectory (4DCT-TT). The volume of CTV inside ITV for all cine CTs was calculated and reported at the 10th percentile (V_CTV10% ). The deviations between CTV_COV in the cine CTs and the 4DCT-TT were calculated and reported at its 90th percentile (d_90% ). The standard deviation of the bellows amplitude peaks (SDP) and the ratio between large and normal inspirations, κ_rel , were tested as surrogates for V_CTV10% and d_90% .

RESULTS

The values of d_90% ranged from 0.6 to 5.2 mm with a mean of 2.2 mm. The values of V_CTV10% ranged from 59-93% with a mean of 78 %. The SDP had a moderate correlation (r = 0.87) to d_90% . Less correlation was seen between SDP and V_CTV10% (r = 0.77), κ_rel and d_90% (r = 0.75) and finally κ_rel and V_CTV10% (r = 0.75).

CONCLUSIONS

The ITV coverage had a large variation for some patients. SDP seems to be a feasible surrogate measure to select patients that needs further tumor motion determination.

Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation

Many surrogate-based motion models (SMMs), proposed to guide motion management in radiotherapy, are constructed by correlating motion of an external surrogate and internal anatomy during CT-simulation. Changes in this correlation define model break down. We validate a methodology that incorporates fluoroscopic images (FL) acquired during treatment for SMM construction and update. Under a prospective IRB, 4DCT scans, VisionRT surfaces, and orthogonal FLs were collected from five lung cancer patients. VisionRT surfaces and two FL time-series were acquired pre- and post-treatment. A simulated annealing optimization scheme was used to estimate optimal lung deformations by maximizing the mutual information between digitally reconstructed radiographs (DRRs) of the SMM-estimated 3D images and FLs. Our SMM used partial-least-regression and was trained using the optimal deformations and VisionRT surfaces from the first breathing-cycle. SMM performance was evaluated using the mutual information score between reference FLs and the corresponding SMM or phase-assigned 4DCT DRRs. The Hausdorff distance for contoured landmarks was used to evaluate target position estimation error. For four out of five patients, two principal components approximated lung surface deformations with submillimeter accuracy. Analysis of the mutual information score between more than 4,000 pairs of FL and DRR demonstrated that our model led to more similarity between the FL and DRR images compared to 4DCT and DRR images from a model based on an a priori correlation model. Our SMM consistently displayed lower mean and 95^th percentile Hausdorff distances. For one patient, 95^th percentile Hausdorff distance was reduced by 11mm. Patient-averaged reductions in mean and 95^th percentile Hausdorff distances were 3.6mm and 7mm for right-lung, and 3.1mm and 4mm for left-lung targets. FL data were used to evaluate model performance and investigate the feasibility of model update. Despite variability in breathing, use of post-treatment FL preserved model fidelity and consistently outperformed 4DCT for position estimation.

Technical Note: Investigating interplay effects in pencil beam scanning proton therapy with a 4D XCAT phantom within the RayStation treatment planning system

PURPOSE

Pencil beam scanning (PBS) for moving targets is known to be impacted by interplay effects. Four-dimensional computed tomography (4DCT)-based motion evaluation is crucial for understanding interplay and developing mitigation strategies. Availability of high-quality 4DCTs with variable breathing traces is limited. Purpose of this work is the development of a framework for interplay analysis using 4D-XCAT phantoms in conjunction with time-resolved irradiation patterns in a commercial treatment planning system (TPS). Four-dimensional dynamically accumulated dose distributions (4DDDs) are simulated in an in-silico study for a PBS liver treatment.

METHODS

An XCAT phantom with 50 phases, varying linearly in amplitude each by 1 mm, was combined with the RayStation TPS (7.99.10). Deformable registration was used with time-resolved dose calculation, mapping XCAT phases to motion signals. To illustrate the applicability of the method a two-field liver irradiation plan was used. A variety sin⁴ type motion signals, varying in amplitude (1-20 mm), period (1.6-5.2 s) and phase (0-2π) were applied. Either single variable variations or random combinations were selected. The interplay effect within a clinical target (5 cm diameter) was characterized in terms of homogeneity index (HI5), with and without five paintings. In total 2092 scenarios were analyzed within RayStation.

RESULTS

A framework is presented for interplay research, allowing for flexibility in determining motion management techniques, increasing reproducibility, and enabling comparisons of different methods. A case study showed the interplay effect was correlated with amplitude and strongly affected by the starting phase, leading to large variance. The average of all scenarios (single fraction) resulted in HI5 of 0.31 (±0.11), while introduction of five times layered repainting reduced this to 0.11(±0.03).

CONCLUSION

The developed framework, which uses the XCAT phantom and RayStation, allows detailed analysis of motion in context of PBS with comparable results to clinical cases. Flexibility in defining motion patterns for detailed anatomies in combination with time-resolved dose calculation, facilitates investigation of optimal treatment and motion mitigation strategies.

In-vivo lung biomechanical modeling for effective tumor motion tracking in external beam radiation therapy

Lung cancer is the most common cause of cancer-related death in both men and women. Radiation therapy is widely used for lung cancer treatment; however, respiratory motion presents challenges that can compromise the accuracy and/or effectiveness of radiation treatment. Respiratory motion compensation using biomechanical modeling is a common approach used to address this challenge. This study focuses on the development and validation of a lung biomechanical model that can accurately estimate the motion and deformation of lung tumor. Towards this goal, treatment planning 4D-CT images of lung cancer patients were processed to develop patient-specific finite element (FE) models of the lung to predict the patients' tumor motion/deformation. The tumor motion/deformation was modeled for a full respiration cycle, as captured by the 4D-CT scans. Parameters driving the lung and tumor deformation model were found through an inverse problem formulation. The CT datasets pertaining to the inhalation phases of respiration were used for validating the model's accuracy. The volumetric Dice similarity coefficient between the actual and simulated gross tumor volumes (GTVs) of the patients calculated across respiration phases was found to range between 0.80 ± 0.03 and 0.92 ± 0.01. The average error in estimating tumor's center of mass calculated across respiration phases ranged between 0.50 ± 0.10 (mm) and 1.04 ± 0.57 (mm), indicating a reasonably good accuracy of the proposed model. The proposed model demonstrates favorable accuracy for estimating the lung tumor motion/deformation, and therefore can potentially be used in radiation therapy applications for respiratory motion compensation.

Comparison of intelligent 4D CT sequence scanning and conventional spiral 4D CT: a first comprehensive phantom study

4D CT imaging is a cornerstone of 4D radiotherapy treatment. Clinical 4D CT data are, however, often affected by severe artifacts. The artifacts are mainly caused by breathing irregularity and retrospective correlation of breathing phase information and acquired projection data, which leads to insufficient projection data coverage to allow for proper reconstruction of 4D CT phase images. The recently introduced 4D CT approach i4DCT (intelligent 4D CT sequence scanning) aims to overcome this problem by breathing signal-driven tube control. The present motion phantom study describes the first in-depth evaluation of i4DCT in a real-world scenario. Twenty-eight 4D CT breathing curves of lung and liver tumor patients with pronounced breathing irregularity were selected to program the motion phantom. For every motion pattern, 4D CT imaging was performed with i4DCT and a conventional spiral 4D CT mode. For qualitative evaluation, the reconstructed 4D CT images were presented to clinical experts, who scored image quality. Further quantitative evaluation was based on established image intensity-based artifact metrics to measure (dis)similarity of neighboring image slices. In addition, beam-on and scan times of the scan modes were analyzed. The expert rating revealed a significantly higher image quality for the i4DCT data. The quantitative evaluation further supported the qualitative: While 20% of the slices of the conventional spiral 4D CT images were found to be artifact-affected, the corresponding fraction was only 4% for i4DCT. The beam-on time (surrogate of imaging dose) did not significantly differ between i4DCT and spiral 4D CT. Overall i4DCT scan times (time between first beam-on and last beam-on event, including scan breaks to compensate for breathing irregularity) were, on average, 53% longer compared to spiral CT. Thus, the results underline that i4DCT significantly improves 4D CT image quality compared to standard spiral CT scanning in the case of breathing irregularity during scanning.

Simulated four-dimensional CT for markerless tumor tracking using a deep learning network with multi-task learning

INTRODUCTION

Our markerless tumor tracking algorithm requires 4DCT data to train models. 4DCT cannot be used for markerless tracking for respiratory-gated treatment due to inaccuracies and a high radiation dose. We developed a deep neural network (DNN) to generate 4DCT from 3DCT data.

METHODS

We used 2420 thoracic 4DCT datasets from 436 patients to train a DNN, designed to export 9 deformation vector fields (each field representing one-ninth of the respiratory cycle) from each CT dataset based on a 3D convolutional autoencoder with shortcut connections using deformable image registration. Then 3DCT data at exhale were transformed using the predicted deformation vector fields to obtain simulated 4DCT data. We compared markerless tracking accuracy between original and simulated 4DCT datasets for 20 patients. Our tracking algorithm used a machine learning approach with patient-specific model parameters. For the training stage, a pair of digitally reconstructed radiography images was generated using 4DCT for each patient. For the prediction stage, the tracking algorithm calculated tumor position using incoming fluoroscopic image data.

RESULTS

Diaphragmatic displacement averaged over 40 cases for the original 4DCT were slightly higher (<1.3 mm) than those for the simulated 4DCT. Tracking positional errors (95th percentile of the absolute value of displacement, "simulated 4DCT" minus "original 4DCT") averaged over the 20 cases were 0.56 mm, 0.65 mm, and 0.96 mm in the X, Y and Z directions, respectively.

CONCLUSIONS

We developed a DNN to generate simulated 4DCT data that are useful for markerless tumor tracking when original 4DCT is not available. Using this DNN would accelerate markerless tumor tracking and increase treatment accuracy in thoracoabdominal treatment.

Intensity-modulated proton therapy (IMPT) interplay effect evaluation of asymmetric breathing with simultaneous uncertainty considerations in patients with non-small cell lung cancer

PURPOSE

Intensity-modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient's outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them.

METHODS

We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient-specific breathing pattern parameters as acquired during the four-dimensional (4D)-computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients' respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose-volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application's example, we compared plan robustness under both three-dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non-small cell lung cancer.

RESULTS

The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D_95% , P = 0.002), CTV homogeneity (D_5% -D_95% , P = 0.002) with less target hot spots (D_5% , P = 0.002), and target coverage robustness (CTV D_95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung D_mean , P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min.

CONCLUSION

A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real-time intra-fractional interplay effect evaluation as a potential application for future use.