Image-guided Radiotherapy Research Articles

Analysis of the gamma index using an indigenously developed anthropomorphic heterogeneous female pelvis (AHFP) phantom.

It is essential in modern radiotherapy treatment practices to evaluate the quality assurance (QA) of the treatment plan prior to the exclusion of patient from treatment. The typical suitable tools used for patient pretreatment QA are phantoms representing the human anatomy. An anthropomorphic heterogeneous female pelvic (AHFP) phantom has been developed to represent the real female pelvic structure. The objective of the current study is to assess the findings of relative dosimetry carried out utilizing an electronic portal imaging device (EPID) on the AHFP phantom fabricated. The planning target volume (PTV) was created on CT slices of an AHFP phantom to confirm the tool's ability to represent female pelvic anatomy and serve as a QA tool. In order to assess the dose received by healthy organs during radiotherapy, organs at risk such as the bladder and rectum were additionally drawn alongside the PTV. Rapid Arc and Intensity modulated radiation therapy (IMRT) were both used to create the treatment plan on treatment planning system, and the Anisotropic Analytical Algorithm Version 11.0.31 was used to calculate the dose. The results obtained for the average gamma value in RapidArc plans are 0.26, 0.27, and 0.28 (g ≤1) and IMRT plans are 0.39, 0.40, and 0.46 (g ≤1) for target 1, target 2, and target 3, respectively. According to the findings of the current study, the AHFP phantom was used to explore the potential of relative dosimetry using EPID as a QA tool, which was found to be suitable.

Artificial intelligence for treatment delivery: image-guided radiotherapy.

Radiation therapy (RT) is ahighly digitized field relying heavily on computational methods and, as such, has ahigh affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is concerned and is especially so during image-guided RT (IGRT). With the advent of online adaptive RT (ART) workflows at magnetic resonance (MR) linear accelerators (linacs) and at cone-beam computed tomography (CBCT) linacs, the need for automation is further increased. AI as applied to modern IGRT is thus one area of RT where we can expect important developments in the near future. In this review article, after outlining modern IGRT and online ART workflows, we cover the role of AI in CBCT and MRI correction for dose calculation, auto-segmentation on IGRT imaging, motion management, and response assessment based on in-room imaging.

Understanding the Importance of Daily Imaging in the Treatment of Non-Melanoma Skin Cancer with Image-Guided Superficial Radiation Therapy

Image-guided superficial radiation therapy (IGSRT) combines superficial radiation therapy (SRT) with full dermal visualization (FDV) via high-resolution dermal ultrasound (HRDUS) for the treatment of non-melanoma skin cancer (NMSC). The gold standard for IGSRT delivery includes a comprehensive cancer care model with support for dermatologists from a multidisciplinary team. When delivered in this model, IGSRT can achieve cure rates of 99% for treatment of NMSC. This paper focuses on the benefits of HRDUS used in conjunction with SRT for NMSC. Medical records from 7 dermatology clinics of 883 patients with 1507 cases of NMSC treated with IGSRT between 2017 and 2018 were retrospectively reviewed. In total, 92% of the NMSC lesions showed daily depth fluctuations, 60.32% of lesions did not require changes during therapy, and nearly 40% of lesions required at least one compensatory change during therapy. In total, 83% of NMSC lesions were labeled as high risk based on the 2024 NCCN guidelines. Increasing and decreasing tumor depth measurements during IGSRT inform dermatologists when adaptive changes in energy (kV), TDF, and dose will result in more efficacy and less toxicity, respectively.

Optimal Correction Strategy of Image Guided Radiation Therapy Including the Paraortic Lymph Node Region in Patients With Cervical Cancers

The clinically accepted planning target volume margin for radiation therapy to the paraortic nodal region in cervical cancer patients is 5 mm. However, the comprehensive alignment and variability from the pelvic bone to all lumbar vertebrae are undetermined. This study aims to quantify the residual setup errors between the pelvic bone and lumbar vertebrae and determine the optimal correction strategy for patients with cervical cancer. Fifteen patients underwent pretreatment mega-voltage computed tomography scans (375 total fractions). Residual setup errors and required margins for each lumbar vertebra were calculated based on registrations accounting for pelvic rotation and translation. The systematic residual errors (1 SD) at L1, L2, L3, L4, and L5 using pelvic bone registration were 6.5, 4.9, 3.1, 1.5, and 0.6 mm in the anterior-posterior (AP) direction, 3.1, 2.3, 1.4, 0.6, and 0.3 mm in the right-left direction, and 2.7, 2.2, 1.7, 1.0, and 0.5 mm in the superior-inferior direction, respectively. The residual setup errors were the largest in the AP direction. Registration based on the pelvic bone required margins in the AP direction of 16.0, 12.1, 7.7, 3.6, and 1.3 mm for L1, L2, L3, L4, and L5, respectively, whereas registration based on L3 required margins of 8.8, 4.8, 4.4, 7.1, and 7.7 mm for L1, L2, L4, L5, and pelvic bone, respectively. Considerable local setup variability was found in patients with cervical cancer. After reviewing the corrective strategies, we determined that L3-based registration effectively minimized the required margins.

Turning the attention to time-resolved EPID-images: treatment error classification with transformer multiple instance learning

Objective. The aim of this work was to develop a novel artificial intelligence-assisted in vivo dosimetry method using time-resolved (TR) dose verification data to improve quality of external beam radiotherapy. Approach. Although threshold classification methods are commonly used in error classification, they may lead to missing errors due to the loss of information resulting from the compression of multi-dimensional electronic portal imaging device (EPID) data into one or a few numbers. Recent research has investigated the classification of errors on time-integrated (TI) in vivo EPID images, with convolutional neural networks showing promise. However, it has been observed previously that TI approaches may cancel out the error presence on γ-maps during dynamic treatments. To address this limitation, simulated TR γ-maps for each volumetric modulated arc radiotherapy angle were used to detect treatment errors caused by complex patient geometries and beam arrangements. Typically, such images can be interpreted as a set of segments where only set class labels are provided. Inspired by recent weakly supervised approaches on histopathology images, we implemented a transformer based multiple instance learning approach and utilized transfer learning from TI to TR γ-maps. Main results. The proposed algorithm performed well on classification of error type and error magnitude. The accuracy in the test set was up to 0.94 and 0.81 for 11 (error type) and 22 (error magnitude) classes of treatment errors, respectively. Significance. TR dose distributions can enhance treatment delivery decision-making, however manual data analysis is nearly impossible due to the complexity and quantity of this data. Our proposed model efficiently handles data complexity, substantially improving treatment error classification compared to models that leverage TI data.

CBCT-based synthetic CT image generation using a diffusion model for CBCT-guided lung radiotherapy.

Although cone beam computed tomography (CBCT) has lower resolution compared to planning CTs (pCT), its lower dose, higher high-contrast resolution, and shorter scanning time support its widespread use in clinical applications, especially in ensuring accurate patient positioning during the image-guided radiation therapy (IGRT) process. While CBCT is critical to IGRT, CBCT image quality can be compromised by severe stripe and scattering artifacts. Tumor movement secondary to respiratory motion also decreases CBCT resolution. In order to improve the image quality of CBCT, we propose a Lung Diffusion Model (L-DM) framework. Our proposed algorithm is based on a conditional diffusion model trained on pCT and deformed CBCT (dCBCT) image pairs to synthesize lung CT images from dCBCT images and benefit CBCT-based radiotherapy. dCBCT images were used as the constraint for the L-DM. The image quality and Hounsfield unit (HU) values of the synthetic CTs (sCT) images generated by the proposed L-DM were compared to three selected mainstream generation models. We verified our model in both an institutional lung cancer dataset and a selected public dataset. Our L-DM showed significant improvement in the four metrics of mean absolute error (MAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and structural similarity index measure (SSIM). In our institutional dataset, our proposed L-DM decreased the MAE from 101.47 to 37.87HU and increased the PSNR from 24.97 to 29.89 dB, the NCC from 0.81 to 0.97, and the SSIM from 0.80 to 0.93. In the public dataset, our proposed L-DM decreased the MAE from 173.65 to 58.95HU, while increasing the PSNR, NCC, and SSIM from 13.07 to 24.05 dB, 0.68 to 0.94, and 0.41 to 0.88, respectively. The proposed L-DM significantly improved sCT image quality compared to the pre-correction CBCT andthree mainstream generative models. Our model can benefit CBCT-based IGRT and other potential clinical applications as it increases the HU accuracy and decreases the artifacts from input CBCT images.

Treatment outcome of localized prostate cancer using transperineal ultrasound image-guided radiotherapy

BackgroundWe report the results of a retrospective analysis of localized prostate cancer (LPCa) treated with transperineal ultrasound image-guided radiotherapy (TPUS-IGRT).MethodsA total of 124 patients (median age: 74 y, 46–84 y) with LPCa who underwent TPUS-IGRT (Clarity Autoscan system; CAS, Elekta; Stockholm, Sweden) between April 2016 and October 2021 for curative/after hormone induction were enrolled. The number of patients by risk (National Comprehensive Cancer Network 2019) was 7, 25, 42, and 50 for low (LR), good intermediate (good IR), poor intermediate (poor IR), and high (HR)/very high (VHR), respectively. Ninety-five patients were given neoadjuvant hormonal therapy. The planning target volume margin setting was 3 mm for rectal in most cases, 5–7 mm for superior/inferior, and 5 mm for anterior/right/left. The principle prescribed dose is 74 Gy (LR), 76 Gy (good IR), and 76–78 Gy (poor IR or above). CAS was equipped with a real-time prostate intrafraction monitoring (RTPIFM) system. When a displacement of 2–3 mm or more was detected, irradiation was paused, and the patients were placed on standby for prostate reinstatement/recorrection. Of the 3135 fractions in 85 patients for whom RTPIFM was performed, 1008 fractions (32.1%) were recorrected at least once after starting irradiation.ResultsA total of 123 patients completed the radiotherapy course. The 5-year overall survival rate was 95.9%. The 5-year biological prostate-specific antigen relapse-free survival rate (bPFS) was 100% for LR, 92.9% for intermediate IR, and 93.2% for HR/VHR (Phoenix method). The 5-year late toxicity rate of Grade 2+ was 7.4% for genitourinary (GU) and 6.5% for gastrointestinal (GI) organs. Comparing the ≤ 76 Gy group to the 78 Gy group for both GU and GI organs, the incidence was higher in the 78 Gy group for both groups.ConclusionThese results suggest that TPUS-IGRT is well tolerated, as the bPFS and incidence of late toxicity are almost comparable to those reported by other sources of image-guided radiotherapy.

483 Image-guided adaptive radiation therapy (IGRT)

483 Image-guided adaptive radiation therapy (IGRT)

Magnetic Resonance Imaging Guided Radiation Therapy for Splenomegaly: Clinical Experiences and Technical Tips

IntroductionSplenomegaly is a common manifestation in chronic lymphoid and myeloid malignancies. While splenectomy is the preferred treatment for symptomatic splenomegaly, it carries significant risks. Radiotherapy (RT) has traditionally been considered a palliative option. This study explores the use of Magnetic Resonance-Guided Radiotherapy (MRgRT) for splenic irradiation (SI) in patients with myelofibrosis (MFI) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN). MethodsThis single-center retrospective analysis includes patients with MFI and MDS/MPN who underwent MRgRT SI between 2018 and 2022. Ten 1 Gy fractions were delivered to the PTV (spleen+3/5mm margin). An adaptive online/offline strategy has been used to reduce the dose to healthy organs. Dosimetric data and clinical outcomes, including pain relief, gastrointestinal symptoms, and hematological values, were assessed. ResultsTwelve patients completed SI without interruption, with supportive transfusions as needed for cytopenias. Pain and gastrointestinal symptoms relief was observed in most cases. The mean percentage reduction in spleen volume was 53.61%, with an average cranio-caudal extension reduction of 77.78%. Twenty-nine (24.2%) out of 120 fractions were online adapted and 14 (11.7%) were replanned offline. Non-hematological toxicities were not reported. At a median follow-up of 12.9 months, 6 patients died, while 9 patients underwent hematopoietic cell transplantation, with 6 of them surviving. ConclusionThis study demonstrates MRgRT SI feasibility in MFI and MDS/MPN patients, offering symptom relief and significant spleen volume reduction. Real-time setup verification and adaptive planning allowed for tailored treatment with reduced margins, minimizing healthy tissue exposure. Larger prospective studies with longer follow-up are needed to further validate its efficacy and safety.

Prostate-Specific Membrane Antigen PET/CT-Guided, Metastasis-Directed Radiotherapy for Oligometastatic Castration-Resistant Prostate Cancer.

Systemic treatments for metastatic castration-resistant prostate cancer (mCRPC) include androgen deprivation therapy, androgen receptor pathway inhibitors, chemotherapy, and radiopharmaceuticals, all of which have associated toxicity. Prostate-specific membrane antigen (PSMA) PET/CT allows for higher sensitivity in detecting metastatic disease than is possible with conventional imaging. We hypothesized that PSMA PET/CT-guided, metastasis-directed radiotherapy may offer durable disease control with low toxicity rates in patients with mCRPC who have a limited number of metastases. Methods: We retrospectively screened 5 prospective PSMA PET/CT studies for patients with mCRPC who had up to 5 sites of oligorecurrent or oligoprogressive disease on PSMA PET/CT and subsequently received definitive-intent, metastasis-directed radiotherapy to all new or progressing sites with concurrent androgen deprivation therapy. Progression-free survival, freedom from new lines of systemic therapy, and overall survival (OS) were calculated from the start of metastasis-directed radiotherapy using Kaplan-Meier analysis. Biochemical response was defined as at least a 50% decrease in prostate-specific antigen 6 mo after the start of treatment. Toxicity was graded using the Common Terminology Criteria for Adverse Events, version 5. Results: Twenty-four patients met the inclusion criteria with a median follow-up of 33.8 mo (interquartile range, 27.6-45.1 mo). Between October 2017 and April 2023, 11 patients (45.8%) had 1 treated site, 10 patients (41.7%) had 2, and 3 patients (12.5%) had 3. Five sites were prostate or prostate bed, 15 were nodal, 19 were osseous, and 1 was visceral. Seventeen patients (70.8%) continued their preexisting systemic therapy, whereas 7 (29.2%) started a new systemic therapy. Median progression-free survival was 16.4 mo (95% CI, 9.8-23.0 mo). The biochemical response rate was 66.7%. Median freedom from a new line of systemic therapy was 29.0 mo (95% CI, 7.6-50.4 mo). Median OS was not reached. The 2- and 4-y OS rates were 91.1% (95% CI, 79.3%-100%) and 68.8% (95% CI, 45.1%-92.5%), respectively. Grade 2 and grade 3 or higher toxicity rates were 4.2% and 0%, respectively. Conclusion: PSMA PET/CT-guided, metastasis-directed radiotherapy appears to offer durable disease control with low toxicity rates for oligometastatic castration-resistant prostate cancer. Further prospective studies are needed to compare metastasis-directed radiotherapy with systemic therapy versus systemic therapy alone and PSMA PET/CT-guided versus conventional imaging-guided radiotherapy.

Editorial Comment to: Lung-heart Toxicity in a Randomized Clinical Trial of Hypofractionated Image-guided Radiation Therapy for Breast Cancer

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Harnessing the Power of Radiotherapy for Lung Cancer: A Narrative Review of the Evolving Role of Magnetic Resonance Imaging Guidance.

Compared with computed tomography (CT), magnetic resonance imaging (MRI) traditionally plays a very limited role in lung cancer management, although there is plenty of room for improvement in the current CT-based workflow, for example, in structures such as the brachial plexus and chest wall invasion, which are difficult to visualize with CT alone. Furthermore, in the treatment of high-risk tumors such as ultracentral lung cancer, treatment-associated toxicity currently still outweighs its benefits. The advent of MR-Linac, an MRI-guided radiotherapy (RT) that combines MRI with a linear accelerator, could potentially address these limitations. Compared with CT-based technologies, MR-Linac could offer superior soft tissue visualization, daily adaptive capability, real-time target tracking, and an early assessment of treatment response. Clinically, it could be especially advantageous in the treatment of central/ultracentral lung cancer, early-stage lung cancer, and locally advanced lung cancer. Increasing demands for stereotactic body radiotherapy (SBRT) for lung cancer have led to MR-Linac adoption in some cancer centers. In this review, a broad overview of the latest research on imaging-guided radiotherapy (IGRT) with MR-Linac for lung cancer management is provided, and development pertaining to artificial intelligence is also highlighted. New avenues of research are also discussed.

Impact of on-trial IGRT quality assurance in an international adaptive radiotherapy trial for participants with bladder cancer

Background and purposeRadiotherapy trial quality assurance (RT QA) is crucial for ensuring the safe and reliable delivery of radiotherapy trials, and minimizing inter-institutional variations. While previous studies focused on outlining and planning quality assurance (QA), this work explores the process of Image-Guided Radiotherapy (IGRT), and adaptive radiotherapy.This study presents findings from during-accrual QA in the RAIDER trial, evaluating concordance between online and offline plan selections for bladder cancer participants undergoing adaptive radiotherapy. RAIDER had two seamless stages; stage 1 assessed adherence to dose constraints of dose escalated radiotherapy (DART) and stage 2 assessed safety. The RT QA programme was updated from stage 1 to stage 2. Materials and methodsData from all participants in the adaptive arms (standard dose adaptive radiotherapy (SART) and DART) of the trial was requested (33 centres across the UK, Australia and New Zealand). Data collection spanned September 2015 to December 2022 and included the plans selected online, on Cone-Beam Computed Tomography (CBCT) data. Concordance with the plans selected offline by the independent RT QA central reviewer was evaluated. ResultsAnalysable data was received for 72 participants, giving a total of 884 CBCTs. The overall concordance rate was 83% (723/884). From stage 1 to stage 2 the concordance in the plans selected improved from 75% (369/495) to 91% (354/389). ConclusionDuring-accrual IGRT QA positively influenced plan selection concordance, highlighting the need for ongoing support when introducing a new technique. Overall, it contributes to advancing the understanding and implementation of QA measures in adaptive radiotherapy trials.

Personalized Deep Learning Model for Clinical Target Volume on Daily Cone Beam Computed Tomography in Breast Cancer Patients

PurposeHerein, we developed a deep learning algorithm to improve the segmentation of the clinical target volume (CTV) on daily cone-beam computed tomography (CBCT) scans in breast cancer radiotherapy. By leveraging the Intentional Deep Overfit Learning (IDOL) framework, we aimed to enhance personalized image-guided radiotherapy (IGRT) based on patient-specific learning. MethodsWe utilized 240 CBCT scans from 100 breast cancer patients and employed a two-stage training approach. The first stage involved training a novel general deep learning model (Swin UNETR, UNET, and SegResNET) on 90 patients. The second stage utilized intentional overfitting on the remaining 10 patients for patient-specific CBCT outputs. Quantitative evaluation was conducted using the Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), mean surface distance (MSD), and independent samples t-test with expert contours on CBCT scans from the 1st to 15th fractions. ResultsIDOL integration significantly improved CTV segmentation, particularly with the Swin UNETR model (p-values <0.05). Using patient-specific data, IDOL enhanced the DSC, HD, and MSD metrics. The average DSC for the 15th fraction improved from 0.9611 to 0.9819, the average HD decreased from 4.0118 mm to 1.3935 mm, and the average MSD decreased from 0.8723 to 0.4603. Incorporating CBCT scans from the initial treatments and 1st to 3rd fractions further improved results, with an average DSC of 0.9850, an average HD of 1.2707 mm, and an average MSD of 0.4076 for the 15th fraction, closely aligned with physician-drawn contours. ConclusionCompared with a general model, our patient-specific deep learning-based training algorithm significantly improved CTV segmentation accuracy of CBCT scans in patients with breast cancer. This approach, coupled with continuous deep learning training using daily CBCT scans, demonstrated enhanced CTV delineation accuracy and efficiency. Future studies should explore the adaptability of the IDOL framework to diverse deep learning models, datasets, and cancer sites.

Impact of Fractionation Regimen on Local Control Following Frameless Linear Accelerator-Based Image-Guided Stereotactic Radiosurgery and Radiotherapy for Intracranial Meningioma

ObjectivesStereotactic radiosurgery (SRS) is an established treatment for intracranial meningioma, yet this approach is often precluded by tumor size or proximity to critical structures. Fractionated radiotherapy may be employed to address these limitations. We performed a comparison of local control (LC) outcomes between three stereotactic techniques. MethodsA retrospective review was performed of 543 consecutive patients with 613 histologically-proven WHO grade I or radiographically-defined benign intracranial meningioma treated with SRS (median dose: 1250cGy) (n=211), fractionated SRS (FSRS) (2500cGy in 500cGy fractions) (n=170), or conventionally fractionated stereotactic radiotherapy (FSRT) (median dose: 5022cGy in <200cGy fractions) (n=232) in the definitive (n=475) or post-operative (n=138) setting between January 2008 and December 2021. Post-operative treatment was delivered upfront after a subtotal resection (n=43) or for recurrent disease (n=95). ResultsMedian follow-up per lesion was 8.0 years. LC for all lesions at 5/10/14 years was 97.4%/86.8%/86.8%. Base of skull location (p=0.01), tumor volume >5cc (p=0.01), and recurrent disease (p=0.02) were associated with inferior LC. No difference was observed in LC by fractionation regimen; LC at 5/10 years was 97.3%/85.7% for SRS, 97.5%/89.1% for FSRS, and 97.5%/86.3% for FSRT. Dose escalation above 1250cGy for SRS or above 5040cGy for FSRT did not result in improved LC. ConclusionsDurable LC was observed at long-term follow-up of intracranial meningioma treated with stereotactic radiosurgery and radiotherapy. LC outcomes were similar across the three fractionation regimens, suggesting that clinicians may tailor radiotherapy recommendations based on clinical factors without concern for reduced efficacy.

Proton radiation boosts the efficacy of mesothelin-targeting chimeric antigen receptor T cell therapy in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) represents a challenge in oncology, with limited treatment options for advanced-stage patients. Chimeric antigen receptor T cell (CAR T) therapy targeting mesothelin (MSLN) shows promise, but challenges such as the hostile immunosuppressive tumor microenvironment (TME) hinder its efficacy. This study explores the synergistic potential of combining proton radiation therapy (RT) with MSLN-targeting CAR T therapy in a syngeneic PDAC model. Proton RT significantly increased MSLN expression in tumor cells and caused a significant increase in CAR T cell infiltration into tumors. The combination therapy reshaped the immunosuppressive TME, promoting antitumorigenic M1 polarized macrophages and reducing myeloid-derived suppressor cells (MDSC). In a flank PDAC model, the combination therapy demonstrated superior attenuation of tumor growth and improved survival compared to individual treatments alone. In an orthotopic PDAC model treated with image-guided proton RT, tumor growth was significantly reduced in the combination group compared to the RT treatment alone. Further, the combination therapy induced an abscopal effect in a dual-flank tumor model, with increased serum interferon-γ levels and enhanced proliferation of extratumoral CAR T cells. In conclusion, combining proton RT with MSLN-targeting CAR T therapy proves effective in modulating the TME, enhancing CAR T cell trafficking, and exerting systemic antitumor effects. Thus, this combinatorial approach could present a promising strategy for improving outcomes in unresectable PDAC.

Charged Gold Nanoparticles for Target Identification-Alignment and Automatic Segmentation of CT Image-Guided Adaptive Radiotherapy in Small Hepatocellular Carcinoma.

Because of the challenges posed by anatomical uncertainties and the low resolution of plain computed tomography (CT) scans, implementing adaptive radiotherapy (ART) for small hepatocellular carcinoma (sHCC) using artificial intelligence (AI) faces obstacles in tumor identification-alignment and automatic segmentation. The current study aims to improve sHCC imaging for ART using a gold nanoparticle (Au NP)-based CT contrast agent to enhance AI-driven automated image processing. The synthesized charged Au NPs demonstrated notable in vitro aggregation, low cytotoxicity, and minimal organ toxicity. Over time, an in situ sHCC mouse model was established for in vivo CT imaging at multiple time points. The enhanced CT images processed using 3D U-Net and 3D Trans U-Net AI models demonstrated high geometric and dosimetric accuracy. Therefore, charged Au NPs enable accurate and automatic sHCC segmentation in CT images using classical AI models, potentially addressing the technical challenges related to tumor identification, alignment, and automatic segmentation in CT-guided online ART.

Application of low-dose CT in image-guided radiotherapy based on CT-linac

BackgroundImage-guided radiation therapy (IGRT) involves online medical imaging systems. CT-guided imaging systems not only have high image quality but also allow for direct dose calculation for radiation treatment planning, making it an ideal image guidance method. However, the imaging dose from CT images may pose additional risks to patients. Therefore, the aim of this study was to evaluate the substitutability of using low-dose CT images for IGRT. Materials and methodsThe CIRS-062 phantom, Catphan 604 phantom, CT dose index phantom were used to obtain the conversion curves of the CT values to the relative electron density (RED), image quality, and imaging dose of the low-dose CT, respectively. Catphan 604 phantom and clinical cases were used to analyze the feasibility of low-dose CT for dose calculation. ResultsNo significant differences were observed in the conversion curves of CT values to RED between low-dose and standard-dose CT scans. In terms of image quality, the geometric distortion of low-dose CT was 0.1 mm, which was the same as that of standard-dose CT. The spatial resolution of the images was 0.42–0.45 lp/mm, which was slightly better than that of standard-dose CT (0.40–0.44 lp/mm). The image uniformity was 98.4%–99.0%, slightly worse than that of standard-dose CT (99.4%–99.5%), but still met the clinical requirements. The imaging dose was 2.96–4.62 mGy, significantly lower than that of standard-dose CT (9.71–26.68 mGy), especially for head CT protocol. In terms of dose calculation, the γ passing rates were not lower than 98% for either the Catphan 604 phantom or the clinical cases. ConclusionLow-dose CT can significantly reduce the imaging dose without a significant loss of image quality and can be directly used for dose calculation in radiation treatment planning, providing a safer and more effective image guidance method for IGRT.

Small field measurements using electronic portal imaging device

Purpose/Objective. Small-field measurement poses challenges. Although many high-resolution detectors are commercially available, the EPID for small-field dosimetry remains underexplored. This study aimed to evaluate the performance of EPID for small-field measurements and to derive tailored correction factors for precise small-field dosimetry verification. Material/Methods. Six high-resolution radiation detectors, including W2 and W1 plastic scintillators, Edge-detector, microSilicon, microDiamond and EPID were utilized. The output factors, depth doses and profiles, were measured for various beam energies (6 MV-FF, 6 MV-FFF, 10 MV-FF, and 10 MV-FFF) and field sizes (10 × 10 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, 1 × 1 cm2, 0.5 × 0.5 cm2) using a Varian Truebeam linear accelerator. During measurements, acrylic plates of appropriate depth were placed on the EPID, while a 3D water tank was used with five-point detectors. EPID measured data were compared with W2 plastic scintillator and measurements from other high-resolution detectors. The analysis included percentage deviations in output factors, differences in percentage for PDD and for the profiles, FWHM, maximum difference in the flat region, penumbra, and 1D gamma were analyzed. The output factor and depth dose ratios were fitted using exponential functions and fractional polynomial fitting in STATA 16.2, with W2 scintillator as reference, and corresponding formulae were obtained. The established correction factors were validated using two Truebeam machines. Results. When comparing EPID and W2-PSD across all field-sizes and energies, the deviation for output factors ranged from 1% to 15%. Depth doses, the percentage difference beyond dmax ranged from 1% to 19%. For profiles, maximum of 4% was observed in the 100%–80% region. The correction factor formulae were validated with two independent EPIDs and closely matched within 3%. Conclusion. EPID can effectively serve as small-field dosimetry verification tool with appropriate correction factors.

Image-Guided Stereotactic Body Radiotherapy on Detectable Prostate Bed Recurrence after Prostatectomy in RT-Naïve Patients.

Eighty-six patients who underwent SBRT for macroscopic bed recurrence after prostatectomy were retrospectively included. Patients were treated based on mpMRI or choline/PSMA PET. The median time to biochemical relapse (BCR) after RP was 46 months, with a median PSA at restaging of 1.04 ng/mL. Forty-six patients were staged with mpMRI and choline/PSMA PET, while ten and thirty were treated based on PET and MRI only, respectively. Only one late G ≥ 2 GI toxicity was observed. With a median BCR follow-up of 14 months, twenty-nine patients experienced a BCR with a median PSA at recurrence of 1.66 ng/mL and a median survival free from the event of 40.1 months. The median time to BCR was 17.9 months. Twenty-seven patients had clinical relapse (CR), with a median CR follow-up of 16.27 months and a median time to CR of 23.0 months. Biochemical recurrence-free survival at one and two years was 88% and 66%, respectively, while clinical recurrence-free survival at one and two years was 92% and 82%, respectively. Regarding local relapses, seven were in the field of treatment, while eight of them were outside the field of treatment. Data showed that SBRT targeting only the macroscopic bed recurrence instead of the whole prostate bed is safe and effective. Additional data and longer follow-ups will provide a clearer indication of the appropriate treatment and staging methodology for these patients.