Image-guided Radiotherapy Research Articles

A novel comprehensive metric balancing imaging dose and setup accuracy in image-guided radiotherapy: concept proposal and clinical validation

PurposeTo propose and validate a comprehensive novel metric balancing the registration accuracy and imaging dose for image-guided-radiotherapy based on real patient data.Materials and methodsWith written informed consent and ethical approval, 56 patients were scanned using 6MV CBCT, 140 kV CBCT, and 100 kV CBCT on Halcyon system for three consecutive treatment fractions. Online registration was performed by various on-duty therapists under routine clinical pressure and time limitation. Offline registration was carried out by an experienced physicist without pressure. The consistency between the online and offline results was used as a surrogate of the missing ground-truth of registration accuracy, which was usually developed by introducing ‘known’ setup errors and rescan the phantoms, yet is ethnically not applicable to real patients. The registration differences (ΔD) between various imaging methods and observers were analyzed. The weighted CT dose index (CTDIw) for kV and MV CBCT was acquired using the PTW CTDI head phantom. The weighted-Dose-Accuracy-Product (DAPw) index was defined as DAPw =ΔD(mm) w1* CTDIw(mGy) w2, where w1 and w2 are the weighting factors of accuracy and dose respectively (w1+w2 = 1).ResultsThe mean and interquartile range (IQR) of ΔD decreased monotonically for MV CBCT, 100 kV CBCT, and 140 kV CBCT, supporting the registration consistency as a surrogate metric of image quality. Significant differences of ΔD were observed between the online and offline registration across three imaging methods (P<0.05). The 140 kV CBCT provides superior positioning accuracy, less dependency on observer subjectivity and time pressure of clinical workflow. Using w1=w2 = 0.5 as an example, the smallest mean, standard deviation, and IQR of DAPw were observed on the 100 kV CBCT, indicating optimal balance between dose and accuracy than the other two methods. Analysis of variance (ANOVA) showed statistically significant differences in DAPw among the different imaging methods (P<0.01, F=50.57).ConclusionUsing registration consistency as a surrogate indicator of image quality, this study proposed and validated a novel “DAPw” parameter based on real patient data, providing a purpose-specific tool for balancing setup accuracy and radiation dose in clinic.

Assessment of Setup-errors in 3Dd-Conformal Radiotherapy for Head and Neck Cancer Patients Using an Electronic Portal Imaging Device

Patient setup is crucial in radiotherapy since treatment is delivered as fractionated treatment over a period of time. Using own institutional margins by considering the setup errors will provide better radiotherapy outcome. Therefore, this study aims to assess set up errors for head and neck cancer patients using an electronic portal imaging device at Apeksha Hospital, Maharagama, Sri Lanka. A total of 101 head and neck cancer patients who were immobilized with thermoplastic mask were selected in this study. Stored data from July 2021 to July 2022 were obtained from ARIA patient management system in the Varian 2300CD Unit at Apeksha Hospital. In order to calculate systematic and random errors, translational errors in all directions were collected utilizing 303 pairs of orthogonal portal images. Moreover, three different algorithms were used to obtain the margin of clinical target volume (CTV) to planning target volume (PTV). The estimated systematic and random errors in the directions of antero-posterior, superior-inferior and medio-lateral are 0.13 cm, 0.10 cm and 0.08 cm, and 0.22 cm, 0.21 cm, and 0.19 cm respectively. Less than 0.5 cm margin were obtained by applying three different algorithms. This study indicates that using a 0.5 cm margin for head and neck cancer patients treating in 2300CD Varian Unit at Apeksha Hospital is safe. Further, this study recommends to developing institutional CTV to PTV margin for all sites of cancer to reduce unnecessary radiation to the surrounding normal healthy tissues.

The TROG 15.01 stereotactic prostate adaptive radiotherapy utilizing kilovoltage intrafraction monitoring (SPARK) clinical trial database.

The US National Institutes of Health state that Sharing of clinical trial data has great potential to accelerate scientific progress and ultimately improve public health by generating better evidence on the safety and effectiveness of therapies for patients (https://www.ncbi.nlm.nih.gov/books/NBK285999/ accessed 2024-01-24.). Aligned with this initiative, the Trial Management Committee of the Trans-Tasman Radiation Oncology Group (TROG) 15.01 Stereotactic Prostate Adaptive Radiotherapy utilizing Kilovoltage intrafraction monitoring (KIM) (SPARK) clinical trial supported the public sharing of the clinical trial data. The data originate from the TROG 15.01 SPARK clinical trial. The SPARK trial was a phase II prospective multi-institutional clinical trial (NCT02397317). The aim of the SPARK clinical trial was to measure the geometric and dosimetric cancer targeting accuracy achieved with a real-time image-guided radiotherapy technology named KIM for 48 prostate cancer patients treated in 5 treatment sessions. During treatment, real-time tumor translational and rotational motion were determined from x-ray images using the KIM technology. A dose reconstruction method was used to evaluate the dose delivered to the target and organs-at-risk. Patient-reported outcomes and toxicity data were monitored up to 2 years after the completion of the treatment. The dataset contains planning CT images, treatment plans, structure sets, planned and motion-included dose-volume histograms, intrafraction kilovoltage, and megavoltage projection images, tumor translational and rotational motion determined by KIM, tumor motion ground truth data, the linear accelerator trajectory traces, and patient treatment outcomes. The dataset is publicly hosted by the University of Sydney eScholarship Repository at https://doi.org/10.25910/qg5d-6058. The 3.6Tb dataset, with approximately 1 million patient images, could be used for a variety of applications, including the development of real-time image-guided methods, adaptation strategies, tumor, and normal tissue control modeling, and prostate-specific antigen kinetics.

Image-Guided Radiation Therapy Is Equally Effective for Basal and Squamous Cell Carcinoma.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are highly prevalent and a significant cause of morbidity. Image-guided superficial radiation therapy (IGSRT) uses integrated high-resolution dermal ultrasound to improve lesion visualization, but it is unknown whether efficacy varies by histology. This large retrospective cohort study was conducted to determine the effect of tumor histology on freedom from recurrence in 20,069 biopsy-proven NMSC lesions treated with IGSRT, including 9928 BCCs (49.5%), 5294 SCCs (26.4%), 4648 SCCIS cases (23.2%), and 199 lesions with ≥2 NMSCs (1.0%). Freedom from recurrence at 2, 4, and 6 years was 99.60%, 99.45%, and 99.45% in BCC; 99.58%, 99.49%, and 99.49% in SCC; and 99.96%, 99.80%, and 99.80% in SCCIS. Freedom from recurrence at 2, 4, and 6 years following IGSRT did not differ significantly comparing BCC vs. non-BCC or SCC vs. non-SCC but were slightly lower among SCCIS vs. non-SCCIS (p = 0.002). There were no significant differences in freedom from recurrence when stratifying lesions by histologic subtype. This study demonstrates that there is no significant effect of histology on freedom from recurrence in IGSRT-treated NMSC except in SCCIS. These findings support IGSRT as a first-line therapeutic option for NMSC regardless of histology.

A radiation therapy platform to enable upright cone beam computed tomography and future upright treatment on existing photon therapy machines

AbstractBackgroundThe conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone‐beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation.PurposeTo design, manufacture, and test a device for upright radiation therapy. A collaborative partnership between physicists, engineers, radiation therapists, radiation oncologists, implementation researchers and consumers was established, to create a device that meets both the clinical and technical requirements of upright radiation therapy. The device is central to a clinical trial (ACTRN12623000498695) which will evaluate upright image quality in the context of future image guided radiation therapy for patients with lung cancer or head and neck cancer.MethodsThe weight and physical constraints of the device were assessed with respect to the American civilian population. The final design was evaluated with a series of tests to characterize the angular accuracy of the platform rotation and the reproducibility of the platform setup position in a radiation treatment room. To acquire an upright CBCT, the platform movement system was synchronized to the kilo‐voltage fluoroscopic imaging on an existing treatment machine. The accuracy of the synchronization was evaluated by assessing the positional reproducibility of upright CBCT imaging of a chest phantom.ResultsThe platform has a weight limit of up to 125 kg which is suitable for approximately 90% of males and 95% of females. The platform has physical constraints that accommodate approximately 95.6% of males and 99.6% of females: a maximum seated height of 97.5 cm, a maximum hip breadth of 63.0 cm, and maximum elbow to knuckle length of 46.5 cm. The angular accuracy of the motion system is within ±0.15° over a full rotation, which is within the guidelines for machine movement accuracy in radiation therapy (1 mm/1°). The platform is a portable device and can be reproducibly positioned in a radiation therapy treatment room with a translational range within ±0.04 mm and a rotational range within ±0.025°. The CBCT imaging can reproducibly detect the position of a chest phantom with a translational uncertainty of ±0.07 mm and a rotational uncertainly of ±0.22°, when imaging is acquired following a strict procedure.ConclusionThe upright radiation therapy platform is suitable for the evaluation of CBCT imaging in the context of image guided radiation therapy. The platform will allow the investigation of open questions in upright radiation therapy in the areas of patient experience, positional stability, anatomical changes, and treatment delivery. Improvements to the materials in the radiation beam line, synchronization with the existing treatment machine, and increasing the device weight limit are suggested prior to delivery of future upright treatments.

Offline Adaptive Radiotherapy for Large Non-small Cell Lung Cancer With Volumetric Modulated Arc Therapy Replanning After Creation of Dose Distribution Using Cone-Beam Computed Tomographic Images of Image-Guided Radiotherapy

Offline Adaptive Radiotherapy for Large Non-small Cell Lung Cancer With Volumetric Modulated Arc Therapy Replanning After Creation of Dose Distribution Using Cone-Beam Computed Tomographic Images of Image-Guided Radiotherapy

Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.

We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy. A total of 76 patients of abdominal and pelvic tumors were prospectively selected. The Catphan504 was acquired with the same conditions as the standard phantom test set. We used a CycleGAN-based model for image enhancement. Normal dose CT (NDCT), ultra-low dose CT (LDCT) and deep learning enhanced CT (DLR) were evaluated by subjective and objective analyses in terms of imaging quality, HU accuracy, and image signal-to-noise ratio (SNR). The image noise of DLR was significantly reduced, and the contrast-to-noise ratio (CNR) was significantly improved compared to the LDCT. The most significant improvement was the acrylic which represented soft tissue in CNR from 1.89 to 3.37, improving by 76%, nearly approaching the NDCT, and in low-density resolution from 7.64 to 12.6, improving by 64%. The spatial frequencies of MTF10 and MTF50 in DLR were 4.28 and 2.35 cycles/mm in DLR, respectively, which are higher than LDCT 3.87 and 2.12 cycles/mm, and even slightly higher than NDCT 4.15 and 2.28 cycles/mm. The accuracy and stability of HU values of DLR were similar to NDCT. The image quality evaluation of the two doctors agreed well with DLR and NDCT. A two-by-two comparison between groups showed that the differences in image scores of LDCT compared with NDCT and DLR were all statistically significant (p<0.05), and the subjective scores of DLR were close to NDCT. The image quality of DLR was close to NDCT with reduced radiation dose, which can fully meet the needs of conventional image-guided adaptive radiotherapy (ART) and achieve the quality requirements of clinical radiotherapy. The proposed method provided a technical basis for LDCT-guided ART.

Quantification of uncertainties in reference and relative dose measurements, dose calculations, and patient setup in modern external beam radiotherapy.

Uncertainties in the steps of external beam radiotherapy (EBRT) affect patient outcomes. However, few studies have investigated major contributors to these uncertainties. This study investigated factors contributing to reducing uncertainty in delivering a dose to a target volume. The EBRT process was classified into four steps: reference dosimetry, relative dosimetry [percentage depth doses (PDDs) and off-center ratios (OCRs)], dose calculations (PDDs and OCRs in a virtual water phantom), and patient setup using an image-guided radiation therapy system. We evaluated the uncertainties for these steps in conventionally fractionated EBRT for intracranial disease using 4-, 6-, and 10-MV flattened photon beams generated from clinical linear accelerators following the Guide to the Expression of Uncertainty in Measurement and an uncertainty evaluation method with uncorrected deflection. The following were the major contributors to these uncertainties: beam quality conversion factors for reference dosimetry; charge measurements, chamber depth, source-to-surface distance, water evaporation, and field size for relative dosimetry; dose calculation accuracy for the dose calculations; image registration, radiation-imaging isocenter coincidence, variation in radiation isocenter due to gantry and couch rotation, and intrafractional motion for the patient setup. Among the four steps, the relative dosimetry and dose calculation (namely, both penumbral OCRs) steps involved an uncertainty of more than 5% with a coverage factor of 1. In the EBRT process evaluated herein, the uncertainties in the relative dosimetry and dose calculations must be reduced.

OGC SO06 - Novel Non-metallic Fiducial marker for Radiotherapy in Oesophageal Cancer

Abstract Background Early oesophageal tumours are technically difficult to delineate on the planning computed tomography (pCT) for Image Guided Radiotherapy (IGRT). We describe the use of a novel non-metallic fiducial marker for this purpose. Method Non-metallic fiducial marker (NFM) (BioXmark) was used in 17 patients from April 2021 to November 2022 for marking tumour site prior to radical or palliative radiotherapy. NFM was injected in the sub-mucosal plane using fluoroscopy under general anaesthesia, with the patient supine and using regular injection catheter and syringes. After the initial series, further modifications to the technique improved the injection and shortened operative time. These include left lateral positioning, an ultra-fine injection catheters and micro-dosing syringes. Feedback from the treating radiation oncologists was sought for all the patients. Results Injection was successful in all the patients. In the initial series before the modifications to the technique, often the marker was a larger than anticipated due to a combination of poor visibility when the patients were supine and use of larger bore injection catheters. Once the patient position was changed along with the changes in the injection catheters and the syringes, marking was very precise. Conclusion Previously used fiducial markers are gold based. While these were visible on pCTs, they are known to cause distortion along with being expensive and cumbersome to inject. In comparison, NFM is easy to inject without the artefacts seen with metallic markers. We refined the technique further by changing the patient’s position to left lateral which afforded a improved fluoroscopic visibility. Introducing finer injection catheters and micro-dosing syringes further led to usage of lesser volume and precise marking respectively. In summary we present a series of patients whose early oesophageal tumours were marked with a NFM aiding precise delivery of radiotherapy.

Cone-Beam CT to CT Image Translation Using a Transformer-Based Deep Learning Model for Prostate Cancer Adaptive Radiotherapy.

Cone-beam computed tomography (CBCT) is widely utilized in image-guided radiation therapy; however, its image quality is poor compared to planning CT (pCT), thus restricting its utility for adaptive radiotherapy (ART). Our objective was to enhance CBCT image quality utilizing a transformer-based deep learning model, SwinUNETR, which we compared with a conventional convolutional neural network (CNN) model, U-net. This retrospective study involved 260 patients undergoing prostate radiotherapy, with 245 patients used for training and 15 patients reserved as an independent hold-out test dataset. Employing a CycleGAN framework, we generated synthetic CT (sCT) images from CBCT images, employing SwinUNETR and U-net as generators. We evaluated sCT image quality and assessed its dosimetric impact for photon therapy through gamma analysis and dose-volume histogram (DVH) comparisons. The mean absolute error values for the CT numbers, calculated using all voxels within the patient's body contour and taking the pCT images as a reference, were 84.07, 73.49, and 64.69 Hounsfield units for CBCT, U-net, and SwinUNETR images, respectively. Gamma analysis revealed superior agreement between the dose on the pCT images and on the SwinUNETR-based sCT plans compared to those based on U-net. DVH parameters calculated on the SwinUNETR-based sCT deviated by < 1% from those in pCT plans. Our study showed that, compared to the U-net model, SwinUNETR could proficiently generate more precise sCT images from CBCT images, facilitating more accurate dose calculations. This study demonstrates the superiority of transformer-based models over conventional CNN-based approaches for CBCT-to-CT translation, contributing to the advancement of image synthesis techniques in ART.

A Review of Contemporary Image Guidance Techniques in Head and Neck Cancer.

Traditional head and neck cancer treatment involves open surgery, cytotoxic chemotherapy, and conventional radiotherapy planning. Emerging techniques aim to improve precision and reduce associated toxicity and functional impairment in current practice. This review article describes four such adaptations in image guidance, tailored to next generation therapies. This is a review of current literature, including feasibility studies from our cancer center, relating to: saline-aided intra-oral ultrasound-guided retropharyngeal biopsy; intra-oral ultrasound guided trans-oral robotic surgery (TORS); ultrasound-guided injection of "directly injectedtherapies"; and magnetic resonance imaging-guided radiotherapy. Presented within the context of the wider literature, initial local experience and data indicate good technical outcomes and patient tolerance, and low technical complications in all four image guidance techniques. Initial findings suggest a potentially important future role for these four image guidance techniques, on which next generation therapies are reliant. The broader implications on cross-disciplinary collaboration are also explored herein.

CBCT-based online adaptive radiotherapy of the prostate bed: first clinical experience and comparison to nonadaptive conventional IGRT.

Conventional image-guided radiotherapy (IGRT) of the prostate bed is challenged by the varying anatomy due to dynamic changes of surrounding organs such as the bladder and rectum. This leads to changed dose coverage of target and surrounding tissue. The novel online adaptive radiotherapy (oART) aims to improve target coverage as well as reduce dose exposure to surrounding healthy tissues by daily reoptimization of treatment plans. Here we set out to quantify the resulting changes of this adaptation for patients and treatment team. Atotal of 198 fractions of radiotherapy of the prostate bed (6patients) were treated using oART with the Ethos accelerator (Varian Medical Systems, Palo Alto, CA, USA). For each fraction, volumes and several dose-volume parameters of target volumes and organs at risk were recorded for the scheduled plan (initial plan, recalculated based on daily cone beam computed tomography [CBCT]), the adapted plan, and the verification plan, which is the dose distribution of the applied plan recalculated on the closing CBCT after the adaptation process. Clinical acceptability for all plans was determined using given dose-volume parameters of target volumes. Additionally, the time needed for the adaptation process was registered and compared to the time required for the daily treatment of five conventional IGRT patients. Volumes of target and organs at risk (OAR) exhibited broad variation from day to day. The differences in dose coverage D98% of the clinical target volume (CTV) were significant through adaptation (p < 0.0001; median D98% 97.1-98.0%) and further after verification CBCT (p < 0.001; median D98% 98.1%). Similarly, differences in D98% of the planning target volume (PTV) were significant with adaptation (p < 0.0001; median D98% 91.8-96.5%) and after verification CBCT (p < 0.001; median D98% 96.4%) with decreasing interquartile ranges (IQR). Dose to OAR varied extensively and did not show aconsistent benefit from oART but decreased in IQR. Clinical acceptability increased significantly from 19.2% for scheduled plans to 76.8% for adapted plans and decreased to 70.7% for verification plans. The scheduled plan was never chosen for treatment. The median time needed for oART was 25 min compared to 8 min for IGRT. Target dose coverage was significantly improved using oART. IQR decreased for target coverage as well as OAR doses indicating higher repeatability of dose delivery using oART. Differences in doses after verification CBCT for targets as well as OAR were significant compared to adapted plans but did not offset the overall dosimetric gain of oART. The median time required is three times higher for oART compared to IGRT.

Quantifying thermoplastic mask quality for precision radiotherapy in head and neck cancer: A 3D stress test and 6D-axis error analysis.

Patients with head and neck cancers often require radiotherapy, where immobilization devices like thermoplastic masks ensure precise radiation delivery by minimizing movement. However, the quality of these masks lacks standard reference data. This study aimed to establish institutional acceptance criteria for thermoplastic mask quality and quantify their effectiveness using a 3 dimensional stress test and verified the setup errors using daily megavoltage computed tomography (MVCT). Between April and June 2022, 30 patients underwent radiotherapy with thermoplastic masks. Four key facial points (forehead, bilateral cheekbones, and chin) were tested for supporting force. Mean forces ranged from 3.97 N to 8.8 N. MVCT was used to assess 6 dimensional-axis errors, with mean translational errors (x, y, z) of 0.32 mm, -1.09 mm, and 2.24 mm, respectively, and rotational errors (yaw, pitch, roll) of -0.12°, 0.22°, and 0.35°, respectively. The results demonstrated that the thermoplastic masks provided precise immobilization, minimizing setup errors in 6 dimensions. Our findings offer a quantifiable method to ensure high-quality immobilization during radiotherapy for patients with head and neck cancers.

P059 Evaluation of image-guided dose-escalated salvage radiotherapy in patients with macroscopic local recurrences in the prostatectomy bed (SPIDER-SR): A systematic review

P059 Evaluation of image-guided dose-escalated salvage radiotherapy in patients with macroscopic local recurrences in the prostatectomy bed (SPIDER-SR): A systematic review

Locoregional control in high-risk neuroblastoma using highly-conformal image-guided radiotherapy, with reduced margins and a boost dose for residual lesions

IntroductionRadiotherapy protocols for high-risk neuroblastoma (HR-NBL) vary across international studies. The purpose of this study was to evaluate the locoregional control in a national HR-NBL cohort treated with highly-conformal image-guided radiotherapy (IGRT), using reduced margins, and a boost dose for residual lesions. Materials and methodsPatients treated with radiotherapy as part of first-line HR-NBL treatment between 2015 and 2022 were eligible. To obtain clinical, internal, and planning target volumes, +0.5 cm, 4DCT-based, and + 0.3/0.5 cm margins, respectively, were added to the edited gross tumour volumes. Prescription dose was 21.6/1.8 Gy, followed by 14.4/1.8 Gy for any residual lesions measuring ≥ 1 cm3 at the time of radiotherapy planning. Intensity-modulated arc therapy was combined with daily cone beam CT-based online patient position verification. Locoregional failure (LRF) rates were compared for the presence of residual lesions < 1 cm3 vs. ≥ 1 cm3 (with/without locoregional activity on nuclear- and MRI[diffusion-weighted imaging]-scans) pre-radiotherapy, age at diagnosis, MYCN-status, [131I]mIBG therapy, response to induction chemotherapy, interval to radiotherapy onset, and metastatic site irradiation. ResultsAmong the 77 included patients, 34 had residual lesions (median volume: 10.0 cm3, IQR 4.8–29.9) with activity visible on 17 nuclear- and 10 MRI-scans. Five-year LRF rate was 7.8 % (95 % confidence interval 1.8–13.8), and not significantly different between those with residual lesions < 1 cm3 vs. ≥ 1 cm3 (6.4 % vs. 14.3 %, respectively, p = 0.27), or any of the other variables. All 6 LRFs (2 isolated, 4 combined) occurred < 1.5 years post-radiotherapy. ConclusionIn HR-NBL, IGRT with reduced margins and a boost dose for residual lesions ≥ 1 cm3 demonstrated excellent locoregional control, comparable to modern literature.

Estimation of weighted computed tomography dose index (CTDIw) in megavoltage computed tomography (MVCT)

Abstract Introduction Advanced technologies in radiation treatment deliveries require high accuracy and precision in setup before treatment to get accurate dose delivery for planned target volumes. During imaging procedures, patients are getting extra doses from kilovoltage computed tomography (KVCT) and megavoltage computed tomography (MVCT). Computed tomography dose index is an important dosimetric parameter to know the degree of radiation-induced side effects. Aim The main aim of this study is to quantify the dose received by patients during MVCT imaging procedures, weighted computed tomography dose index (CTDIw), volume computed tomography dose index (CTDIvol) and dose length product (DLP). Methods and materials This study has been performed on Radixact X9 LINAC machine with 6MV flattening filter-free (FFF) photon beam for treatment and imaging with 3.5 MeV average photon energy. CTDIw and dose length product (DLP) have been calculated for different scanning lengths 18 cm, 10 cm and 0.7 cm with fine, normal and coarse modes with standard imaging A1SL1 ion chamber, cheese phantom and tomoelectrometer. Results CTDIw, CTDIvol, and DLP have been calculated with cheese phantom using A1SL1 ion chamber. CTDIw for 0.7 cm is 2.16 cGy, 1.14 cGy and 0.77 cGy for fine normal and coarse modes, respectively. Conclusion CTDIw is a dosimetric index to know the dose levels at center and periphery of patient according to scan length. It gives an idea about how much additional dose is received by the patient during the imaging procedures. High pitch gives the lesser absorbed dose. DLP gives the knowledge about stochastic effects from radiation to patients after MVCT.

An adaptive parameter decoupling algorithm-based image reconstruction model (ADAIR) for rapid golden-angle radial DCE-MRI

Objective. The acceleration of magnetic resonance imaging (MRI) acquisition is crucial for both clinical and research applications, particularly in dynamic MRI. Existing compressed sensing (CS) methods, despite being effective for fast imaging, face limitations such as the need for incoherent sampling and residual noise, which restrict their practical use for rapid MRI.Approach. To overcome these challenges, we propose a novel image reconstruction framework that integrates the MRI physical model with a flexible, self-adjusting, decoupling data-driven model. We validated this method through experiments using both simulated andin vivodynamic contrast-enhanced MRI datasets.Main results. The experimental results demonstrate that the proposed framework achieves high spatial and temporal resolution reconstructions. Additionally, when compared to state-of-the-art image reconstruction approaches, our method significantly enhances acceleration capabilities, enabling sparse and rapid imaging with high resolution.Significance. Our proposed framework offers a promising solution for real-time imaging and image-guided radiation therapy applications by providing superior performance in achieving high spatial and temporal resolution reconstructions, thus addressing the limitations of existing CS schemes.

Hybrid modality dual-energy imaging aggregating complementary advantages of kV-CT and MV-CBCT: concept proposal and clinical validation

Megavoltage cone-beam CT (MV-CBCT) is advantageous in metal artifact reduction during Image-Guided Radiotherapy (IGRT), although it is limited by poor soft tissue contrast. This study proposed and evaluated a novel hybrid modality dual-energy (DE) imaging method combining the complementary advantages of kV-CT and MV-CBCT.&#xD;Approach: The kV-CT and MV-CBCT images were acquired on a planning CT scanner and a Halcyon linear accelerator respectively. After rigid registration, images of basis materials were generated using the iterative decomposition method in the volumetric images. The decomposition accuracy was quantitatively evaluated on a Gammex 1472 phantom. The performance of contrast enhancement and metal artifact reduction in virtual monochromatic images were evaluated on both phantom and patient studies.&#xD;Main results: Using the proposed method, the mean percentage errors for RED and SPR were 0.90% and 0.81%, outperforming the clinical single-energy mapping method with mean errors of 1.28% and 1.07%, respectively. The contrasts of soft-tissue insets were enhanced by a factor of 2~3 at 40 keV compared to kV-CT. The standard deviation in the metal artifact area was reduced by ~67%, from 42 HU (kV-CT) to 14 HU (150 keV monochromatic). The head and neck patient test showed that the percent error of soft-tissue RED in the metal artifact area was reduced from 18.1% (HU-RED conversion) to less than 1.0% (the proposed method), which was equivalent to the maximum dosimetric difference of 28.7% based on the patient-specific plan.&#xD;Significance: Without hardware modification or extra imaging dose, the proposed hybrid modality method enabled kV-MV DE imaging, providing improved accuracy of quantitative analysis, soft-tissue contrast and metal artifact suppression for more accurate IGRT.&#xD.

Using a patient-specific diffusion model to generate CBCT-based synthetic CTs for CBCT-guided adaptive radiotherapy.

Cone beam computed tomography (CBCT) can be used to evaluate the inter-fraction anatomical changes during the entire course for image-guided radiotherapy (IGRT). However, CBCT artifacts from various sources restrict the full application of CBCT-guided adaptive radiation therapy (ART). Inter-fraction anatomical changes during ART, including variations in tumor size and normal tissue anatomy, can affect radiation therapy (RT) efficacy. Acquiring high-quality CBCT images that accurately capture patient- and fraction-specific (PFS) anatomical changes is crucial for successful IGRT. To enhance CBCT image quality, we proposed PFS lung diffusion models (PFS-LDMs). The proposed PFS models use a pre-trained general lung diffusion model (GLDM) as a baseline, which is trained on historical deformed CBCT (dCBCT)-planning CT (pCT) paired data. For a given patient, a new PFS model is fine-tuned on a CBCT-deformed pCT (dpCT) pair after each fraction to learn the PFS knowledge for generating personalized synthetic CT (sCT) with quality comparable to pCT or dpCT. The learned PFS knowledge is the specific mapping relationships, including personal inter-fraction anatomical changes between personalized CBCT-dpCT pairs. The PFS-LDMs were evaluated on an institutional lung cancer dataset, quantified by mean absolute error (MAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and structural similarity index measure (SSIM) metrics. We also compared our PFS-LDMs with a mainstream GAN-based model, demonstrating that our PFS fine-tuning strategy could be applied to existing generative models. Our models showed remarkable improvements across all four evaluation metrics. The proposed PFS-LDMs outperformed the GLDM, demonstrating the effectiveness of our proposed fine-tuning strategy. The PFS model fine-tuned with CBCT images from four prior fractions, reduced the MAE from 103.95 to 15.96 Hounsfield units (HU), and increased the mean PSNR, NCC, and SSIM from 25.36dB to 33.57dB, 0.77 to 0.98, and 0.75 to 0.97, respectively. Applying our PFS fine-tuning strategy to a Cycle GAN model also showed improvements, with all four fine-tuned PFS Cycle GAN (PFS-CG) models outperforming the general Cycle GAN model. Overall, our proposed PFS fine-tuning strategy improved CBCT image quality compared to both the pre-correction and non-fine-tuned general models, with our proposed PFS-LDMs yielding better performance than the GAN-based model across all metrics. Our proposed PFS-LDMs significantly improve CBCT image quality with increased HU accuracy and fewer artifacts, thus better capturing inter-fraction anatomical changes. This lays the groundwork for enabling CBCT-based ART, which could enhance clinical efficiency and achieve personalized high-precision treatment by accounting for inter-fraction anatomical changes.

Transit-guided radiation therapy: a novel patient monitoring approach

Background and purposeTransit-Guided Radiation Therapy (TGRT) is a novel technique that uses the transit portal images (TPIs) acquired with Electronic Portal Image Devices (EPID) to quantify patient position errors during the treatment. It has been validated using anthropomorphic phantoms but a validation in a clinical setting was lacking. A pilot clinical study is presented to confirm our previous results. Materials and methodsA prospective study was conducted between June and December 2022 with patients who received whole-brain or breast radiotherapy treatments. The selected treatments were composed of radiation fields using skin-flash, where the body contour projected a sharp edge on the EPID which has been used as a surrogate of the true patient position. Daily imaging procedures were applied as scheduled before running the one- and two-parameter model (1PM and 2PM) of the TGRT formalism on the acquired TPIs to independently estimate the patient position errors. Results43 patients and 1015 TPIs have been assessed. The 2PM showed a better correlation with the true position errors (R2 = 0.76 vs. 0.73), a lower detection threshold (0.77 mm vs. 1.24 mm), and a lower overcorrection risk above the detection threshold (7.0 % vs. 11.1 %) than the 1PM. Overall, the 2PM would have significantly reduced the true position errors by a factor of 0.58 (0.49 – 1.27) (p < 0.0001). ConclusionThe TGRT technique has confirmed the ability to reduce the position errors in a clinical setting, demonstrating the potential to enhance the patient position monitoring without increasing treatment time or patient dose.