Image-guided Radiotherapy Research Articles

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.
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.
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.
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.

Investigation of pelvic floor influence on prostate displacement in image-guided radiotherapy.

The uncertainty of target location during prostate cancer radiotherapy plays an important role in accurate dose delivery and radiation toxicity in adjacent organs. This study analyzed displacement correlations between the prostate and pelvic floor. We retrospectively analyzed registration results from 467 daily cone-beam computed tomography (CT) in 12 patients with prostate cancer who received radiation therapy. We analyzed prostate displacement and the pelvic floor relative to the pelvic bone's anatomy in the translational and rotational directions and identified statistical correlations. The systematic (Σ) and random (σ) displacements of the prostate in the three translational directions, anterior-posterior (AP), superior-inferior (SI), and right-left (RL), were 1.49 ± 1.45, 2.10 ± 1.40, and 0.24 ± 0.53 mm, respectively, and in the rotational directions of the pitch, roll, and yaw were 2.10 ± 2.02°, 0.42 ± 0.74°, and 0.42 ± 0.64°, respectively. The pelvic floor displacements were 2.37 ± 1.96, 2.71 ± 2.28, and 0.47 ± 0.84 mm in the AP, SI, and RL directions, respectively, and 0.93 ± 1.49°, 0.98 ± 1.28 °, and 0.87 ± 0.94° in the pitch, roll, and yaw directions, respectively. Additionally, there were statistically significant correlations between the displacement of the prostate and pelvic floor in the AP and SI directions, with correlation coefficients (r) of 0.74 (p < 0.001) and 0.69 (p < 0.001), respectively. The movement of the pelvic floor may be an important factor that causes prostate displacement, affecting the accuracy of radiotherapy. Therefore, it is necessary to take appropriate measures to ensure that the pelvic floor muscle tension is as consistent as possible in the treatment' CT scan and daily treatment.

Radio-opaque contrast agents for liver cancer targeting with KIM during radiation therapy (ROCK-RT): an observational feasibility study.

This observational study aims to establish the feasibility of using x-ray images of radio-opaque chemoembolisation deposits in patients as a method for real-time image-guided radiation therapy of hepatocellular carcinoma. This study will recruit 50 hepatocellular carcinoma patients who have had or will have stereotactic ablative radiation therapy and have had transarterial chemoembolisation with a radio-opaque agent. X-ray and computed tomography images of the patients will be analysed retrospectively. Additionally, a deep learning method for real-time motion tracking will be developed. We hypothesise that: (i) deep learning software can be developed that will successfully track the contrast agent mass on two thirds of cone beam computed tomography (CBCT) projection and intra-treatment images (ii), the mean and standard deviation (mm) difference in the location of the mass between ground truth and deep learning detection are ≤ 2mm and ≤ 3mm respectively and (iii) statistical modelling of study data will predict tracking success in 85% of trial participants. Developing a real-time tracking method will enable increased targeting accuracy, without the need for additional invasive procedures to implant fiducial markers. Registered to ClinicalTrials.gov (NCT05169177) 12th October 2021.

Long-term performance monitoring of a-Si 1200 electronic portal imaging device for dosimetric applications.

Recently, dosimetri applications of the electronic portal imaging device (EPID) in radiotherapy have gained popularity. Confidence in the robust and reliable dosimetric performance of EPID detectors is essential for their clinical use. This study aimed to evaluate the dosimetric performance of the a-Si 1200 EPID and assess the long-term stability of its response. Weekly measurements were performed on two clinically used TrueBeam linear accelerators (linacs) equipped with a-Si 1200 EPID detectors over a 2-year period. They included dark and flood calibration fields, and EPID response to an open field corrected for the long-term machine output drift measured with the secondary absolute dosimeters: an ion chamber and an ion chamber array. All measurements were performed using five photon beam energies and two imaging modes: continuous and dosimetry. The measurements were analyzed for constancy and the presence of long-term trends. Comparisons were made between the two linacs for each beam energy. Pixel sensitivity matrices (PSM) were determined semi-annually and analyzed for long-term constancy for both treatment machines. The long-term variation of the dark and flood field signals, integrated across the EPID plane, over the entire observation period did not exceed 0.17% and 0.79%, respectively. The output-corrected EPID response showed long-term variation from 0.28% to 0.36%, depending on beam energy, while the short-term variation was 0.04%-0.07% for EPID and 0.02%-0.06% for secondary dosimeters. The long-term variation of secondary dosimeters was 0.2%-0.3%. PSMs were found to be stable to within 1% for 97.8% of pixels and 2% for 100% of pixels. Techniques to monitor and assess the long-term performance of the a-Si 1200 EPID as a dosimeter were developed and implemented using two TrueBeam linacs. The long-term variation of the EPID response was within clinical tolerance indicated in AAPM TG-142 report, and the detector was shown to be stable and reproducible for routine clinical dosimetry.

Comparison of online adaptive and non-adaptive magnetic resonance image-guided radiation therapy in prostate cancer using dose accumulation

Background and purposeConventional image-guided radiotherapy (conv-IGRT) is standard in prostate cancer (PC) but does not account for inter-fraction anatomical changes. Online-adaptive magnetic resonance-guided RT (OA-MRgRT) may improve organ-at-risk (OARs) sparing and clinical target volume (CTV) coverage. The aim of this study was to analyze accumulated OAR and target doses in PC after OA-MRgRT and conv-IGRT in comparison to pre-treatment reference planning (refPlan). Material and methodsTen patients with PC, previously treated with OA-MRgRT at the 1.5 T MR-Linac (20x3Gy), were included. Accumulated OA-MRgRT doses were determined by deformably registering all fraction’s MR-images. Conv-IGRT was simulated through rigid registration of the planning computed tomography with each fraction’s MR-image for dose mapping/accumulation. Dose-volume parameters (DVPs), including CTV D50% and D98%, rectum, bladder, urethra, Dmax and V56Gy for OA-MRgRT, conv-IGRT and refPlan were compared using the Wilcoxon signed-rank test. Clinical relevance of accumulated dose differences was analyzed using a normal-tissue complication-probability model. ResultsCTV-DVPs were comparable, whereas OA-MRgRT yielded decreased median OAR-DVPs compared to conv-IGRT, except for bladder V56Gy. OA-MRgRT demonstrated significantly lower median rectum Dmax over conv-IGRT (59.1/59.9 Gy, p = 0.006) and refPlan (60.1 Gy, p = 0.012). Similarly, OA-MRgRT yielded reduced median bladder Dmax compared to conv-IGRT (60.0/60.4 Gy, p = 0.006), and refPlan (61.2 Gy, p = 0.002). Overall, accumulated dose differences were small and did not translate into clinically relevant effects. ConclusionDeformably accumulated OA-MRgRT using 20x3Gy in PC showed significant but small dosimetric differences comparted to conv-IGRT. Feasibility of a dose accumulation methodology was demonstrated, which may be relevant for evaluating future hypo-fractionated OA-MRgRT approaches.

A Study on the Evaluation of Image-Guided Treatment Use in Radiotherapy Centers in Türkiye

This study presents a preliminary investigation into the use of image-guided radiation therapy (IGRT) in radiotherapy centers in Türkiye, based on survey data. Radiation therapy technologists were administered a 67-item Internet-based questionnaire. The first five items focused on demographic data, while the remaining items pertained to IGRT applications in the clinics where the technicians worked. Statistical data of the answers obtained were used in SPSS 28.0. While evaluating the study data, descriptive statistical methods (frequency, percentage) were used. A total of 314 individuals participated in the survey, with 45.9% (n=144) being female and 54.1% (n=170) being male. The study focused on patients with stomach (20.6%), rectum (18.9%), prostate (17.6%), head and neck (14.5%), lung (14.3%), and breast (13.9%) cancers. It was observed that megavoltage (MV) ports (35.7%) were used more frequently during daily checks. It has been stated that 1-25 MV ports are drawn daily. This is followed by Cone Beam Computer Tomography (CBCT) and kilovoltage (kV) port checks. In our country, it is seen that important steps have been taken in IGRT and its use is quite common. It has been observed that the technical infrastructure and manpower in the clinics are sufficient. It is predicted that the development of systems that reduce the doses received by patients and employees with IGRT and the development of wage policies will increase the use of IGRT. We hope that this result will be supported by future large-scale studies. Although we think that the use of IGRT is at an adequate level, there are differences in practices between clinics. It is thought that the establishment of national protocols for the use of IGRT will be in favour of patients and technicians.

Modeling and prediction of set‑up errors in breast cancer image‑guided radiotherapy using the Gaussian mixture model.

The aim of the present study was to develop a prediction model for set-up error distribution in breast cancer image-guided radiotherapy (IGRT) using a Gaussian mixture model (GMM). To achieve this, the image-guided set-up errors data of 80 patients with breast cancer were selected, and the GMM was used to develop the set-up errors distribution prediction model. The predicted error center points, covariance and probability were calculated and compared with the planning target volume (PTV) margin formula. A total of 1,200 sets of set-up errors in IGRT for breast cancer were collected. The results of the Gaussian model parameters showed that the set-up errors were mainly in the direction of µ1-µ4 center points. All the raw errors in the lateral, longitudinal and vertical directions were -6.30-4.60, -5.40-1.47 and -2.70-1.70 mm, respectively. According to the probability of each center, the set-up error was most likely to shift in the µ1 direction, reaching 0.53. The set-up errors of the other three centers, µ2, µ3 and µ4, were 0.11, 0.34 and 0.12, respectively. According to the covariance parameters of the GMM, the maximum statistical standard deviation of the set-up errors reached 29.06. In conclusion, the results of the present study demonstrated that the GMM can be used to quantitatively describe and predict the distribution of set-up errors in IGRT for breast cancer, and these findings could be useful as a reference for set-up error control and tumor PTV expansion in breast cancer radiotherapy without routine, daily IGRT.

Image-Guided Superficial Radiation Therapy for Basal and Squamous Cell Carcinomas Produces Excellent Freedom from Recurrence Independent of Risk Factors

Background/Objectives: Basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) are non-melanoma skin cancers (NMSCs) and the most prevalent cancers in the United States. Image-guided superficial radiotherapy (IGSRT) is a relatively new treatment option that uses high-resolution dermal ultrasound integrated with superficial radiotherapy to improve tumor visualization. IGSRT is a clinically equivalent non-surgical alternative to Mohs micrographic surgery at 2 years of follow-up in early-stage NMSC, but larger cohort studies with longer follow-up periods that allow for analysis of patient outcomes by demographic and disease characteristics are needed. Methods: This large, retrospective cohort study was conducted to determine the effect of risk factors (tumor location, tumor stage, and sex) on 2-, 4-, and 6-year freedom from recurrence rates in 19,988 NMSC lesions treated with IGSRT, including lesions with complete treatment courses. Results: Overall freedom from recurrence rates were 99.68% at 2 years, 99.54% at 4 years, and 99.54% at 6 years; rates did not differ significantly by tumor location (head/neck versus other locations, p = 0.9) or sex (male versus female, p = 0.4). In contrast, there was a significant difference in freedom from recurrence rates when analyzed by tumor stage (p = 0.004). Conclusions: There was no significant effect of tumor location or sex on freedom from recurrence in IGSRT-treated NMSC. Although there was a significant difference according to tumor stage, freedom from recurrence rates exceeded 99% at all stages.

The accuracy of cone beam computed tomography (CBCT) technique as an image-guided radiation therapy (IGRT) technique.

To measure the setup error of the patient's positioning using cone-beam computed tomography during radiation therapy treatment fractions by finding systematic, random errors and the planned target volume errors. The observational, longitudinal cohort study was conducted at the Al-Warith International Cancer Institute, Karbala, Iraq, from January to May 2022, and comprised patients with head and neck cancer who underwent radiation therapy. The oncologist delineated and the medical physicist planned. Then the medical physicist modified the positioning system using the cone beam computed tomography option workstation. The vertical value was taken in anteroposterior site, longitudinal in superoinferior, and lateral in e mediolateral. The SPSS 25 were used to analyse data. Of the 31 patients, 17(54.8%) were females and 14(45.2%) were males. The overall mean age was 48.3 ± 10.22 (range: 4-77 years), and 22(70.96%) patients had been treated previously with chemotherapy. The lateral shifting inaccuracy 2.501mm was above the limit, whereas the vertical shifting 1.164mm was within acceptable limits (±2mm). The longitudinal shifting had the smallest displacement 0.436mm. Random error displayed longitudinal moving 1.965mm, lateral shifting 0.623mm and vertical shifting 0.276mm. The planned target volume margins were too wide in longitudinal shifting 3.333mm. Vertical shifting 0.481mm was greater than lateral 1.092mm, but both were within limits (±2mm). Radiation-induced errors in normal tissues must be reduced by reducing planned target volume margins, especially for longitudinal and lateral directions.

Online adaptive radiotherapy in stereotactic body radiotherapy for pancreatic cancer patients.

Stereotactic radiation therapy (SBRT) has emerged as a promising treatment modality for locally advanced pancreatic cancer. The aim of this study is to assess the dosimetric efficacy of online adaptive radiotherapy (ART) in comparison to image-guided radiation therapy (IGRT) for pancreatic cancer. We conducted a retrospective analysis involving 8 patients diagnosed with locally advanced pancreatic cancer. The gross tumor volume (GTV) delineates the visible extent of the tumor on imaging, while the planning tumor volume (PTV) was generated by expanding 5mm from the GTV and ensuring a 3mm distance from the small intestine, duodenum, and stomach simultaneously. Treatment planning was executed using the United Imaging Healthcare Treatment Planning System workstation. The control group underwent evaluation based on daily validated fan-beam CT (FBCT) scans, assessing both the dose delivered to actual organs at risk (OARs) and the target volume. Radiotherapy plans were developed utilizing simulation CT, and conventional radiotherapy with daily image-guided radiation therapy (IGRT) was administered using FBCT-Linac. Conversely, patients in the study group received daily validated FBCT-guided adaptive radiotherapy plans, with a focus on mean dose assessment of both the target volume and OARs. Subsequently, we compared the average outcomes of each treatment fraction between IGRT and online adaptive radiotherapy (ART). Comparison between ART and IGRT treatment plans revealed significant differences in various dosimetric parameters: For PTV: V98%: ART (96.28%) vs IGRT (89.73%), p = 0.000, V95%: ART (96.28%) vs IGRT (89.73%), p = 0.031, V90%: ART (98.58%) vs IGRT (93.65%), p = 0.000, Dmean: ART (4912.91) vs IGRT (4804.11), p = 0.000. For GTV: V100%: ART (97.96%) vs IGRT (94.85%), p = 0.314, V98%: ART (100.00%) vs IGRT (96.83%), p = 0.000, V90%: ART (100.00%) vs IGRT (97.75%), p = 0.000, Dmean: ART (4972.17) vs IGRT (4907.23), p = 0.000. For the duodenum: D0.5cc: ART (2883.92) vs IGRT (3359.35), p = 0.000, D1cc: ART (2726.32) vs IGRT (3128.66), p = 0.001, D5cc: ART (2051.96) vs IGRT (2273.93), p = 0.015, D10cc: ART (1650.73) vs IGRT (1731.74), p = 0.211. For the small bowel: D0.5cc: ART (3022.3) vs IGRT (3142.64), p = 0.037. D5cc: ART (2151.09) vs IGRT (2389.15), p = 0.043, D10cc: ART (1775.20) vs IGRT (1942.00), p = 0.079. For the stomach: D0.5cc: ART (3353.92) vs IGRT (4117.85), p = 0.000, D5cc: ART (2860.20) vs IGRT (3235.41), p = 0.000, D10cc: ART (2553.72) vs IGRT (2836.73), p = 0.000. For the Dmean of the left kidney and right kidney: Left kidney: ART (248.28) vs IGRT (239.65), p = 0.100. Right kidney: ART (314.55) vs IGRT (307.17), p = 0.345. These results suggest significant improvements in PTV coverage and sparing of OARs with ART compared to IGRT, indicating the potential of ART in optimizing treatment outcomes for pancreatic cancer patients.Compared to conventional IGRT-guided SBRT programs, ART-based SBRT for pancreatic cancer not only enhances the dose distribution to the target volume but also mitigates the radiation exposure to critical organs-at-risk (OARs) such as the duodenum, small intestine, and stomach. This approach may offer a more favorable safety profile while concurrently enhancing treatment efficacy.

Deep learning methods for 2D in-vivo dose reconstruction with EPID detector

Over the past two decades, radiotherapy has seen a steep increase in technological complexity of treatment preparation and treatment execution, calling for the development of more and better quality assurance tools and procedures. In-vivo dosimetry has emerged as a very powerful tool for treatment verification in conjunction with Electronic Portal Imaging Devices (EPIDs). However, EPIDs present several drawbacks like non-water equivalence and cumbersome calibration procedures. Artificial intelligence, specifically Deep Learning (DL), plays a crucial role in this context. A critical step is modeling the EPID response to estimate 2D dose distributions (Portal Dose, PD). This work introduces a DL-based methodology aimed at converting EPID responses into PD images. The proposed procedure is fully data driven, being based on advanced DL methods. This approach will allow bypassing the complex calibration steps needed to overcome the non-water equivalent panel.

Role of Radiology in the Diagnosis and Treatment of Breast Cancer in Women: A Comprehensive Review.

Breast cancer remains a leading cause of morbidity and mortality among women worldwide. Early detection and precise diagnosis are critical for effective treatment and improved patient outcomes. This review explores the evolving role of radiology in the diagnosis and treatment of breast cancer, highlighting advancements in imaging technologies and the integration of artificial intelligence (AI). Traditional imaging modalities such as mammography, ultrasound, and magnetic resonance imaging have been the cornerstone of breast cancer diagnostics, with each modality offering unique advantages. The advent of radiomics, which involves extracting quantitative data from medical images, has further augmented the diagnostic capabilities of these modalities. AI, particularly deep learning algorithms, has shown potential in improving diagnostic accuracy and reducing observer variability across imaging modalities. AI-driven tools are increasingly being integrated into clinical workflows to assist in image interpretation, lesion classification, and treatment planning. Additionally, radiology plays a crucial role in guiding treatment decisions, particularly in the context of image-guided radiotherapy and monitoring response to neoadjuvant chemotherapy. The review also discusses the emerging field of theranostics, where diagnostic imaging is combined with therapeutic interventions to provide personalized cancer care. Despite these advancements, challenges such as the need for large annotated datasets and the integration of AI into clinical practice remain. The review concludes that while the role of radiology in breast cancer management is rapidly evolving, further research is required to fully realize the potential of these technologies in improving patient outcomes.

Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy

Background and purposeIn online adaptive magnetic resonance image (MRI)-guided radiotherapy (MRIgRT), manual contouring of rectal tumors on daily images is labor-intensive and time-consuming. Automation of this task is complex due to substantial variation in tumor shape and location between patients. The aim of this work was to investigate different approaches of propagating patient-specific prior information to the online adaptive treatment fractions to improve deep-learning based auto-segmentation of rectal tumors. Materials and methods243 T2-weighted MRI scans of 49 rectal cancer patients treated on the 1.5T MR-Linear accelerator (MR-Linac) were utilized to train models to segment rectal tumors. As benchmark, an MRI_only auto-segmentation model was trained. Three approaches of including a patient-specific prior were studied: 1. include the segmentations of fraction 1 as extra input channel for the auto-segmentation of subsequent fractions, 2. fine-tuning of the MRI_only model to fraction 1 (PSF_1) and 3. fine-tuning of the MRI_only model on all earlier fractions (PSF_cumulative). Auto-segmentations were compared to the manual segmentation using geometric similarity metrics. Clinical impact was assessed by evaluating post-treatment target coverage. ResultsAll patient-specific methods outperformed the MRI_only segmentation approach. Median 95th percentile Hausdorff (95HD) were 22.0 (range: 6.1–76.6) mm for MRI_only segmentation, 9.9 (range: 2.5–38.2) mm for MRI+prior segmentation, 6.4 (range: 2.4–17.8) mm for PSF_1 and 4.8 (range: 1.7–26.9) mm for PSF_cumulative. PSF_cumulative was found to be superior to PSF_1 from fraction 4 onward (p = 0.014). ConclusionPatient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.

Image-guided Hypofractionated Radiotherapy as an Alternative to Radical Prostatectomy in Localized Prostate Cancer in Elderly Patients with Low Life Expectancy.

Radical prostatectomy is appropriate for any patient whose cancer appears clinically localised to prostate. However because of potential perioperative morbidity, radical prostatectomy is generally reserved for patients whose life expectancy is more than ten years. Moderate hypofractionation for localized prostate cancer is safe and effective. There is a growing body of evidence in support of extreme hypofractionation for localized prostate cancer. Hypofractionation for prostate cancer was originally carried out in the pursuit of efficiency and convenience, but has now attracted greatly renewed interest based upon a hypothesis that prostate cancers have a higher sensitivity to fraction size, reflected in a low α/β ratio, then do late responding organs at risk such as the rectum or bladder. From January 2017 to December 2020 we treated 112 patients of localised Prostate Cancer with Image Guided Radiotherapy (IGRT). They were in range of 75-85 years. They were of stage T1-T3, N0 or N1. There were significant comborbidities. ECOG performance status was 0-1. They were given 3 months of Androgen Deprivation Therapy (ADT) before starting IGRT. Patients were immobilised with casts and subject to CT simulation. CBCT was taken daily. Dose was 70 Gy @ 250 cGy per fraction at a frequency of 5 fractions per week. Complete blood counts were done weekly for assessment of haematological toxicity. Androgen Deprivation Therapy was continued post IGRT. All the patients were able to complete the treatment. Evaluation was done at one month, three month and six months post treatment. 104 out of 112 patients achieved complete response. Other 8 had near complete response. There were no acute grade 3-4 toxicities. Grade 1-2 toxicities like skin desquamation, diarrhoea, burning micturition were managed conservatively. Late toxicity was rectal bleeding seen after one year of completion of treatment and was managed with steroid enemas. 23 patients required argon plasma laser therapy. Image guided radiotherapy is well tolerated, easy to implement and an effective alternative to radical prostatectomy in elderly patients with comorbidities and low life expectancy.

Interventional radiotherapy: CT-sim guided modern minimally invasive technique

The concept of interventional radiology was introduced in 1976 as a new diagnostic and therapeutic method, relying on image guidance, such as X-ray, ultrasound, computed tomography (CT), and magnetic resonance imaging. Its indications mainly include obstructive diseases, and to a lesser extent, malignant tumors. Radiotherapy (RT) plays a pivotal role in the comprehensive treatment of cancer. The advent of the CT simulator has significantly enhanced the precision of RT and improvement outcomes and accelerated the development of a series of diagnostic and RT modalities, including puncture biopsy, fiducial marker implantation, high-dose rate after-loading after-loading brachytherapy, and radioactive seed implantation. The innovative concept of image-guidance interventional RT, inspired by interventional radiology, extends the benefits to not only cancer diagnosis but also RT. The image-guidance interventional RT advances the field of RT by expanding its indications and connotation.

Freedom from Recurrence across Age in Non-Melanoma Skin Cancer Treated with Image-Guided Superficial Radiation Therapy.

Non-melanoma skin cancers (NMSCs) are a significant cause of morbidity and mortality; their incidence is increasing most in older patients. NMSCs have traditionally been treated with surgical excision, curettage, Mohs micrographic surgery (MMS), and superficial radiotherapy (SRT). Image-guided SRT (IGSRT) is a treatment option for poor surgical candidates or patients with low- or high-risk, early-stage NMSC who prefer to avoid surgery. This large retrospective cohort study compared 2-, 4-, and 6-year freedom from recurrence in biopsy-proven NMSC lesions treated with IGSRT (n = 20,069 lesions) between patients aged < 65 years (n = 3158 lesions) and ≥65 years (n = 16,911 lesions). Overall freedom from recurrence rates were 99.68% at 2 years, 99.57% at 4 years, and 99.57% at 6 years. Rates did not differ significantly by age (p = 0.8) nor by sex among the two age groups (p > 0.9). There was a significant difference in recurrence among older patients when analyzed by stage (p = 0.032), but no difference by stage in younger patients (p = 0.7). For early-stage NMSCs, IGSRT is a clinically equivalent alternative to MMS and statistically significant in superiority to non-image-guided SRT. This study demonstrates that there is no significant effect of age on 2-, 4-, or 6-year freedom from recurrence in patients with IGSRT-treated NMSC.