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Abstract Background Commissioning of treatment planning systems (TPS) and beam delivery for scanned light ion beams is an important quality assurance task. This requires measurement of large sets of high quality dosimetric data in anthropomorphic phantoms to benchmark the TPS and dose delivery under realistic conditions. Method A novel measurement setup is described, which allows for an efficient collection of a large set of accurate dose data in complex phantom geometries. This setup allows dose measurements based on a set of 24 small volume ionization chambers calibrated in dose to water and mounted in a holder, which can be freely positioned in a water phantom with various phantoms mounted in front of the water tank. The phantoms can be scanned in a CT and a CT-based treatment planning can be performed for a direct benchmark of the dose calculation algorithm in various situations. Results The system has been used for acceptance testing in scanned light ion beam therapy at Heidelberg Ion Beam Therapy Center for scanned proton and carbon ion beams. It demonstrated to be useful to collect large amounts of high quality data for comparison with the TPS calculation using various phantom geometries. Conclusion The setup is an efficient tool for commissioning and verification of treatment planning systems. It is especially suited for dynamic beam delivery, as many data points can be obtained during a single plan delivery, but can be adapted also for other dynamic therapies, like rotational IMRT.

Purpose: Recent papers suggested a correlation between the risk of distant metastasis (DM) and dose outside the PTV, though conclusions in different publications conflicted. This study resolves these conflicts and provides a compelling explanation of prognostic factors. Materials and methods: A dataset of 478 NSCLC patients treated with SBRT (IMRT or VMAT) was analyzed. We developed a deep learning model for DM prediction and explainable AI was used to identify the most significant prognostic factors. Subsequently, the prognostic power of the extracted features and clinical details were analyzed using conventional statistical methods. Results: Treatment technique, tumor features, and dosiomic features in a 3 cm wide ring around the PTV (PTV3cm) were identified as the strongest predictors of DM. The Hazard Ratio (HR) for Dmean,PTV3cm was significantly above 1 (p < 0.001). There was no significance of the PTV3cm dose after treatment technique stratification. However, the dose in PTV3cm was found to be a highly significant DM predictor (HR > 1, p = 0.004) when analyzing only VMAT patients with small and spherical tumors (i.e., sphericity > 0.5). Conclusions: The main reason for conflicting conclusions in previous papers was inconsistent datasets and insufficient consideration of confounding variables. No causal correlation between the risk of DM and dose outside the PTV was found. However, the mean dose to PTV3cm can be a significant predictor of DM in small spherical targets treated with VMAT, which might clinically imply considering larger PTV margins for smaller, more spherical tumors (e.g., if IGTV > 2 cm, then margin ≤ 7 mm, else margin > 7 mm). [ABSTRACT FROM AUTHOR]

Background: This paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image segmentation.Methods: Relevant studies were systematically searched in PubMed, Embase, The Cochrane Library, and Web of science. The literature on DLs for cervical cancer CT image segmentation were included, a meta-analysis was performed on the dice similarity coefficient (DSC) of the segmentation results of the included DLs models. We also did subgroup analyses according to the size of the sample, type of segmentation (i.e., two dimensions and three dimensions), and three organs at risk (i.e., bladder, rectum, and femur). This study was registered in PROSPERO prior to initiation (CRD42022307071).Results: A total of 1893 articles were retrieved and 14 articles were included in the meta-analysis. The pooled effect of DSC score of clinical target volume (CTV), bladder, rectum, femoral head were 0.86(95%CI 0.84 to 0.87), 0.91(95%CI 0.89 to 0.93), 0.83(95%CI 0.79 to 0.88), and 0.92(95%CI 0.91to 0.94), respectively. For the performance of segmented CTV by two dimensions (2D) and three dimensions (3D) model, the DSC score value for 2D model was 0.87 (95%CI 0.85 to 0.90), while the DSC score for 3D model was 0.85 (95%CI 0.82 to 0.87). As for the effect of the capacity of sample on segmentation performance, no matter whether the sample size is divided into two groups: greater than 100 and less than 100, or greater than 150 and less than 150, the results show no difference (P > 0.05). Four papers reported the time for segmentation from 15 s to 2 min.Conclusion: DLs have good accuracy in automatic segmentation of CT images of cervical cancer with a less time consuming and have good prospects for future radiotherapy applications, but still need public high-quality databases and large-scale research verification. [ABSTRACT FROM AUTHOR]

Background: Approximately 25–50% of patients undergoing radiotherapy (RT) experience psychological distress and anxiety, which can detrimentally affect both their quality of life and treatment outcomes. While previous research has demonstrated that relaxation exercises can enhance the tolerability of RT and alleviate associated stress and anxiety, the specific needs for such therapies in radiation oncology remain under-explored. This study aims to investigate the demand for and preferences toward relaxation exercises among radiotherapy patients, addressing a critical gap in patient-centered care. Methods: A prospective pseudonymized survey study using a one-time paper-based questionnaire was conducted from 2022 to 2023 among patients undergoing curative-intent RT for breast cancer or patients undergoing palliative RT for bone metastases. Patients were asked in a 11-item questionnaire about their anxiety, pre-existing practice of relaxation exercises/interventions, their interest in relaxation exercises, and preferences on the type and format of instruction. Data were analyzed descriptively. Results: 100 patients (74 female and 26 male) responded, of whom 68 received curative-intent adjuvant RT and 32 palliative RT. Median age was 62 years. 78% of patients indicated a desire to be actively involved in their radiotherapy, but only 27% had used relaxation exercises prior to RT. 44.8% of both curatively and palliatively treated patients who wanted to be actively involved in their therapy desired to learn how to best relax. 56.4% of respondents were willing to spend extra time learning offered exercises. Conclusion: The survey indicates that patients undergoing RT, both for curative or palliative intent, desire relaxation exercises to relieve stress and anxiety from RT. It is therefore important to assess the need for relaxation interventions in individual patients and to develop suitable programs or collaborate with other healthcare professionals to meet these needs. [ABSTRACT FROM AUTHOR]

Purpose Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNet-DIR) method using unsupervised learning to establish correspondence between baseline pre-operative and follow-up MRI scans of patients with brain glioma. Methods This study involved multi-parametric brain MRI scans (T1, T1-contrast enhanced, T2, FLAIR) acquired at pre-operative and follow-up time for 160 patients diagnosed with glioma, representing the BraTS-Reg 2022 challenge dataset. ConvUNet-DIR, a deep learning-based deformable registration workflow using 3D U-Net style architecture as a core, was developed to establish correspondence between the MRI scans. The workflow consists of three components: (1) the U-Net learns features from pairs of MRI scans and estimates a mapping between them, (2) the grid generator computes the sampling grid based on the derived transformation parameters, and (3) the spatial transformation layer generates a warped image by applying the sampling operation using interpolation. A similarity measure was used as a loss function for the network with a regularization parameter limiting the deformation. The model was trained via unsupervised learning using pairs of MRI scans on a training data set (n=102) and validated on a validation data set (n=26) to assess its generalizability. Its performance was evaluated on a test set (n=32) by computing the Dice score and structural similarity index (SSIM) quantitative metrics. The model’s performance also was compared with the baseline state-of-the-art VoxelMorph (VM1 and VM2) learning-based algorithms. Results The ConvUNet-DIR model showed promising competency in performing accurate 3D deformable registration. It achieved a mean Dice score of 0.975±0.003 and SSIM of 0.908±0.011 on the test set (n=32). Experimental results also demonstrated that ConvUNet-DIR outperformed the VoxelMorph algorithms concerning Dice (VM1: 0.969±0.006 and VM2: 0.957±0.008) and SSIM (VM1: 0.893±0.012 and VM2: 0.857±0.017) metrics. The time required to perform a registration for a pair of MRI scans is about 1 s on the CPU. Conclusions The developed deep learning-based model can perform an end-to-end deformable registration of a pair of 3D MRI scans for glioma patients without human intervention. The model could provide accurate, efficient, and robust deformable registration without needing pre-alignment and labeling. It outperformed the state-of-the-art VoxelMorph learning-based deformable registration algorithms and other supervised/unsupervised deep learningbased methods reported in the literature. [ABSTRACT FROM AUTHOR]

Background: Ninety percent of patients receiving radiation therapy experience side effects. Busy schedules and intensive health education programs may lead to incomplete education content delivery and inaccurate patient self-care implementation. This study investigated whether multimedia health education improves the accuracy of patient self-care implementation compared with paper-based education. Methods: From March 11, 2020 to February 28, 2021, 110 patients were randomly divided into experimental and control groups, each comprising 55 participants. Paper-based materials were used along with multimedia materials. Radiology self-care awareness questionnaires were administered to both groups before the first treatment and on day 10. The differences in radiology self-care awareness between the two groups was analyzed with inferential statistics, independent t tests, categorical data, and Pearson's chi-squared test. Differences between the two groups were considered significant at a p value of < 0.05. Results: The treatment accuracy rate improved from 10.9 to 79.1% in the control group and from 24.8 to 98.5% in the experimental group, indicating an improvement in both groups. The difference was significant. These results indicate that the intervention could improve the effectiveness of self-care. Conclusions: Participants who used pretreatment multimedia health education exhibited a higher rate of having a correct understanding of treatment self-care than did the control group. These findings can inform the development of a patient-centered cancer treatment knowledge base for improved quality of care. [ABSTRACT FROM AUTHOR]

Background: At present, the implementation of intensity-modulated radiation therapy (IMRT) treatment planning for geometrically complex nasopharyngeal carcinoma (NPC) through manual trial-and-error fashion presents challenges to the improvement of planning efficiency and the obtaining of high-consistency plan quality. This paper aims to propose an automatic IMRT plan generation method through fluence prediction and further plan fine-tuning for patients with NPC and evaluates the planning efficiency and plan quality. Methods: A total of 38 patients with NPC treated with nine-beam IMRT were enrolled in this study and automatically re-planned with the proposed method. A trained deep learning model was employed to generate static field fluence maps for each patient with 3D computed tomography images and structure contours as input. Automatic IMRT treatment planning was achieved by using its generated dose with slight tightening for further plan fine-tuning. Lastly, the plan quality was compared between automatic plans and clinical plans. Results: The average time for automatic plan generation was less than 4 min, including fluence maps prediction with a python script and automated plan tuning with a C# script. Compared with clinical plans, automatic plans showed better conformity and homogeneity for planning target volumes (PTVs) except for the conformity of PTV-1. Meanwhile, the dosimetric metrics for most organs at risk (OARs) were ameliorated in the automatic plan, especially Dmax of the brainstem and spinal cord, and Dmean of the left and right parotid glands significantly decreased (P < 0.05). Conclusion: We have successfully implemented an automatic IMRT plan generation method for patients with NPC. This method shows high planning efficiency and comparable or superior plan quality than clinical plans. The qualitative results before and after the plan fine-tuning indicates that further optimization using dose objectives generated by predicted fluence maps is crucial to obtain high-quality automatic plans. [ABSTRACT FROM AUTHOR]

Background: Recent research has demonstrated that the use of artificial intelligence (AI) in radiotherapy (RT) has significantly streamlined the process for physicians to treat patients with tumors; however, bibliometric studies examining the correlation between AI and RT are not available. Providing a thorough overview of the knowledge structure and research hotspots between AI and RT was the main goal of the current study. Method: A search was conducted on the Web of Science Core Collection (WoSCC) database for publications pertaining to AI and RT between 2003 and 2023. VOSviewers, CiteSpace, and the R program "bibliometrix" were used to do the bibliometric analysis. Results: The analysis comprised 615 publications from 64 countries, with USA and China leading the pack. Since 2017, there have been more and more publications about RT and AI every year. The research center that made the biggest contribution to this topic was Maastricht University. The most articles published journal in this field was Frontiers in Oncology, while Medical Physics received the greatest number of citations. Dekker Andre is the author with the greatest number of published articles, while Philippe Lambin was the most often co-cited author. In the newly identified research hotspots, "autocontouring algorithm", "deep learning", and "machine learning" stand out as the main terms. Conclusion: In fact, our bibliometric analysis offers insightful information on current research directions and advancements pertaining to the use of AI in RT. For academics looking to understand the connection between AI and RT, this study is a great resource because it highlights current research frontiers and hot trends. [ABSTRACT FROM AUTHOR]

Background: Brachial plexopathy is a potentially serious complication from stereotactic body radiation therapy (SBRT) that has not been widely studied. Therefore, we compared datasets from two different institutions and generated a brachial plexus dose-response model, to quantify what dose constraints would be needed to minimize the effect on normal tissue while still enabling potent therapy for the tumor.Methods: Two published SBRT datasets were pooled and modeled from patients at Indiana University and the Richard L. Roudebush Veterans Administration Medical Center from 1998 to 2007, as well as the Karolinska Institute from 2008 to 2013. All patients in both studies were treated with SBRT for apically located lung tumors localized superior to the aortic arch. Toxicities were graded according to Common Terminology Criteria for Adverse Events, and a probit dose response model was created with maximum likelihood parameter fitting.Results: This analysis includes a total of 89 brachial plexus maximum point dose (Dmax) values from both institutions. Among the 14 patients who developed brachial plexopathy, the most common complications were grade 2, comprising 7 patients. The median follow-up was 30 months (range 6.1-72.2) in the Karolinska dataset, and the Indiana dataset had a median of 13 months (range 1-71). Both studies had a median range of 3 fractions, but in the Indiana dataset, 9 patients were treated in 4 fractions, and the paper did not differentiate between the two, so our analysis is considered to be in 3-4 fractions, one of the main limitations. The probit model showed that the risk of brachial plexopathy with Dmax of 26 Gy in 3-4 fractions is 10%, and 50% with Dmax of 70 Gy in 3-4 fractions.Conclusions: This analysis is only a preliminary result because more details are needed as well as additional comprehensive datasets from a much broader cross-section of clinical practices. When more institutions join the QUANTEC and HyTEC methodology of reporting sufficient details to enable data pooling, our field will finally reach an improved understanding of human dose tolerance. [ABSTRACT FROM AUTHOR]

Abstract Purpose Recent papers suggested a correlation between the risk of distant metastasis (DM) and dose outside the PTV, though conclusions in different publications conflicted. This study resolves these conflicts and provides a compelling explanation of prognostic factors. Materials and methods A dataset of 478 NSCLC patients treated with SBRT (IMRT or VMAT) was analyzed. We developed a deep learning model for DM prediction and explainable AI was used to identify the most significant prognostic factors. Subsequently, the prognostic power of the extracted features and clinical details were analyzed using conventional statistical methods. Results Treatment technique, tumor features, and dosiomic features in a 3 cm wide ring around the PTV (PTV3cm) were identified as the strongest predictors of DM. The Hazard Ratio (HR) for Dmean,PTV3cm was significantly above 1 (p 1, p = 0.004) when analyzing only VMAT patients with small and spherical tumors (i.e., sphericity > 0.5). Conclusions The main reason for conflicting conclusions in previous papers was inconsistent datasets and insufficient consideration of confounding variables. No causal correlation between the risk of DM and dose outside the PTV was found. However, the mean dose to PTV3cm can be a significant predictor of DM in small spherical targets treated with VMAT, which might clinically imply considering larger PTV margins for smaller, more spherical tumors (e.g., if IGTV > 2 cm, then margin ≤ 7 mm, else margin > 7 mm).

Background: Prostate cancer can be treated with several different modalities, including radiation treatment. Various prognostic tools have been developed to aid decision making by providing estimates of the probability of different outcomes. Such tools have been demonstrated to have better prognostic accuracy than clinical judgment alone.Methods: A systematic review was undertaken to identify papers relating to the prediction of clinical outcomes (biochemical failure, metastasis, survival) in patients with prostate cancer who received radiation treatment, with the particular aim of identifying whether published tools are adequately developed, validated, and provide accurate predictions. PubMed and EMBASE were searched from July 2007. Title and abstract screening, full text review, and critical appraisal were conducted by two reviewers. A review protocol was published in advance of commencing literature searches.Results: The search strategy resulted in 165 potential articles, of which 72 were selected for full text review and 47 ultimately included. These papers described 66 models which were newly developed and 31 which were external validations of already published predictive tools. The included studies represented a total of 60,457 patients, recruited between 1984 and 2009. Sixty five percent of models were not externally validated, 57% did not report accuracy and 31% included variables which are not readily accessible in existing datasets. Most models (72, 74%) related to external beam radiation therapy with the remainder relating to brachytherapy (alone or in combination with external beam radiation therapy).Conclusions: A large number of prognostic models (97) have been described in the recent literature, representing a rapid increase since previous reviews (17 papers, 1966-2007). Most models described were not validated and a third utilised variables which are not readily accessible in existing data collections. Where validation had occurred, it was often limited to data taken from single institutes in the US. While validated and accurate models are available to predict prostate cancer specific mortality following external beam radiation therapy, there is a scarcity of such tools relating to brachytherapy. This review provides an accessible catalogue of predictive tools for current use and which should be prioritised for future validation. [ABSTRACT FROM AUTHOR]

Background: Surgical resection with adjuvant concurrent radiochemotherapy is the standard of care for stage III-IV oral cavity cancer. In some cases, the dynamic course of the disease is out of the prepared schedule of treatment. In that event, a stereotactic radiosurgery boost might be the only chance for disease control.Case Presentation: Here, we present a case study of a patient with oral cancer who underwent surgery. During adjuvant radiotherapy, a metastatic cervical lymph node was diagnosed based on fine-needle aspiration biopsy. To increase the total dose to the metastatic tumor, a stereotactic radiosurgery boost of 1 × 18 Gy was performed two days after the last fraction of conventional radiotherapy. The early and late tolerance of this treatment were positive. During the 18-month follow-up, locoregional recurrence was not detected. The patient died due to secondary malignancy.Conclusions: This paper shows that a stereotactic radiosurgery boost added to adjuvant conventional radiotherapy is an effective approach permitting the maintenance of good local control in well-selected patients. [ABSTRACT FROM AUTHOR]

Background: This paper describes the development of a predicted electronic portal imaging device (EPID) transmission image (TI) using Monte Carlo (MC) and deep learning (DL). The measured and predicted TI were compared for two-dimensional in vivo radiotherapy treatment verification.Methods: The plan CT was pre-processed and combined with solid water and then imported into PRIMO. The MC method was used to calculate the dose distribution of the combined CT. The U-net neural network-based deep learning model was trained to predict EPID TI based on the dose distribution of solid water calculated by PRIMO. The predicted TI was compared with the measured TI for two-dimensional in vivo treatment verification.Results: The EPID TI of 1500 IMRT fields were acquired, among which 1200, 150, and 150 fields were used as the training set, the validation set, and the test set, respectively. A comparison of the predicted and measured TI was carried out using global gamma analyses of 3%/3 mm and 2%/2 mm (5% threshold) to validate the model's accuracy. The gamma pass rates were greater than 96.7% and 92.3%, and the mean gamma values were 0.21 and 0.32, respectively.Conclusions: Our method facilitates the modelling process more easily and increases the calculation accuracy when using the MC algorithm to simulate the EPID response, and has potential to be used for in vivo treatment verification in the clinic. [ABSTRACT FROM AUTHOR]

Abstract Background Ninety percent of patients receiving radiation therapy experience side effects. Busy schedules and intensive health education programs may lead to incomplete education content delivery and inaccurate patient self-care implementation. This study investigated whether multimedia health education improves the accuracy of patient self-care implementation compared with paper-based education. Methods From March 11, 2020 to February 28, 2021, 110 patients were randomly divided into experimental and control groups, each comprising 55 participants. Paper-based materials were used along with multimedia materials. Radiology self-care awareness questionnaires were administered to both groups before the first treatment and on day 10. The differences in radiology self-care awareness between the two groups was analyzed with inferential statistics, independent t tests, categorical data, and Pearson’s chi-squared test. Differences between the two groups were considered significant at a p value of

Background: In patients with nasopharyngeal cancer (NPC), radiation-induced temporal lobe injury (TLI) is the most dreaded late-stage complication following radiation therapy (RT). We currently lack a definitive algorithmic administration for this entity. In the meantime, the pathogenesis of TLI and the mechanism-based interventions to prevent or treat this adverse effect remain unknown. To better answer the aforementioned questions, it is necessary to comprehend the intellectual foundations and prospective trends of this field through bibliometric analysis. Methods: Articles were gathered from the Web of Science Core Collection (WoSCC) database between 2000 and 2022. CiteSpace was utilized to create a country/institutional co-authorship network, perform dual-map analysis, and find keywords with citation bursts. VOSviewer was used to build networks based on author co-authorship, journal citation, co-citation analysis of authors, references, and journals, and keyword co-occurrence. Results: A total of 140 articles and reviews were included in the final analysis. The number of publications has steadily increased with some fluctuations over the years. The country and institution contributing most to this field are the China and Sun Yat-Sen University. Han Fei was the most prolific author, while Lee Awm was the most frequently cited. The analysis of co-occurrence revealed three clusters, including: "radiation-induced injury or necrosis in NPC," "clinical studies on chemotherapy/radiotherapy complications and survival in recurrent NPC," and "IMRT/chemotherapy outcomes and toxicities in head and neck cancer"). Most recent keyword bursts were "volume," "temporal lobe injury," "toxicities," "model," "survival," "intensity modulated radiotherapy," "induced brain injury," "head and neck cancer," and "temporal lobe." Conclusion: This study provides some insights of the major areas of interest in the field of radiation-induced TLI in patients with NPC by bibliometric analyses. This study assists scholars in locating collaborators and significant literature in this field, provides guidance for publishing journals, and identifies research hotspots. This analysis acknowledges significant contributions to the discipline and encourages the scientific community to conduct additional research. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most common primary brain malignancy and carries with it a poor prognosis. New agents are urgently needed, however nearly all Phase III trials of GBM patients of the past 25 years have failed to demonstrate improvement in outcomes. In 2019, the National Cancer Institute Clinical Trials and Translational Research Advisory Committee (CTAC) Glioblastoma Working Group (GBM WG) identified 5 broad areas of research thought to be important in the development of new herapeutics for GBM. Among those was optimizing radioresponse for GBM in situ. One such strategy to increase radiation efficacy is the addition of a radiosensitizer to improve the therapeutic ratio by enhancing tumor sensitivity while ideally having minimal to no effect on normal tissue. Historically the majority of trials using radiosensitizers have been unsuccessful, but they provide important guidance in what is required to develop agents more efficiently. Improved target selection is essential for a drug to provide maximal benefit, and once that target is identified it must be validated through pre-clinical studies. Careful selection of appropriate in vitro and in vivo models to demonstrate increased radiosensitivity and suitable bioavailability are then necessary to prove that a drug warrants advancement to clinical investigation. Once investigational agents are validated pre-clinically, patient trials require consistency both in terms of planning study design as well as reporting efficacy and toxicity in order to assess the potential benefit of the drug. Through this paper we hope to outline strategies for developing effective radiosensitizers against GBM using as models the examples of XPO1 inhibitors and HDAC inhibitors developed from our own lab. [ABSTRACT FROM AUTHOR]

Pelvic radiotherapy is the key treatment for pelvic malignancies, usually including pelvic primary tumour lesions and lymphatic drainage areas in the pelvic region. Therefore, the intestinal tract in the radiation field is inevitably damaged, a phenomenon clinically referred to as radiation enteritis, and diarrhoea is the most common clinical symptom of radiation enteritis. Therefore, it is necessary to study the mechanism of radiation-induced diarrhoea. It has been found that the gut microbiome plays an important role in the development of diarrhoea in response to pelvic radiotherapy, and the species and distribution of intestinal microbiota are significantly altered in patients after pelvic radiotherapy. In this study, we searched for articles indexed in the Cochrane Library, Web of Science, EMBASE and PubMed databases in English and CNKI, Wanfang data and SINOMED in Chinese from their inception dates through 13 March 2020 to collect studies on the gut microbiome in pelvic radiotherapy patients. Eventually, we included eight studies: one study report on prostatic carcinoma, five studies on gynaecological carcinoma and two papers on pelvic carcinomas. All studies were designed as self-controlled studies, except for one that compared toxicity to nontoxicity. The results from all the studies showed that the diversity of intestinal flora decreased during and after pelvic radiotherapy, and the diversity of intestinal flora decreased significantly in patients with diarrhoea after radiotherapy. Five studies observed that the community composition of the gut microbiota changed at the phylum, order or genus level before, during, and after pelvic radiotherapy at different time points. In addition, the composition of the gut microbiota before radiotherapy was different between patients with postradiotherapy diarrhoea and those without diarrhoea in five studies. However, relevant studies have not reached consistent results regarding the changes in microbiota composition. Changes in the intestinal flora induced by pelvic radiotherapy and their relationship between changes in intestinal flora and the occurrence of radiation-induced diarrhoea (RID) are discussed in this study, providing a theoretical basis for the causes of RID after pelvic radiotherapy. [ABSTRACT FROM AUTHOR]

Abstract Background This paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image segmentation. Methods Relevant studies were systematically searched in PubMed, Embase, The Cochrane Library, and Web of science. The literature on DLs for cervical cancer CT image segmentation were included, a meta-analysis was performed on the dice similarity coefficient (DSC) of the segmentation results of the included DLs models. We also did subgroup analyses according to the size of the sample, type of segmentation (i.e., two dimensions and three dimensions), and three organs at risk (i.e., bladder, rectum, and femur). This study was registered in PROSPERO prior to initiation (CRD42022307071). Results A total of 1893 articles were retrieved and 14 articles were included in the meta-analysis. The pooled effect of DSC score of clinical target volume (CTV), bladder, rectum, femoral head were 0.86(95%CI 0.84 to 0.87), 0.91(95%CI 0.89 to 0.93), 0.83(95%CI 0.79 to 0.88), and 0.92(95%CI 0.91to 0.94), respectively. For the performance of segmented CTV by two dimensions (2D) and three dimensions (3D) model, the DSC score value for 2D model was 0.87 (95%CI 0.85 to 0.90), while the DSC score for 3D model was 0.85 (95%CI 0.82 to 0.87). As for the effect of the capacity of sample on segmentation performance, no matter whether the sample size is divided into two groups: greater than 100 and less than 100, or greater than 150 and less than 150, the results show no difference (P > 0.05). Four papers reported the time for segmentation from 15 s to 2 min. Conclusion DLs have good accuracy in automatic segmentation of CT images of cervical cancer with a less time consuming and have good prospects for future radiotherapy applications, but still need public high-quality databases and large-scale research verification.

Radiotherapy based on magnetic resonance imaging as the sole modality (MRI-only RT) is an area of growing scientific interest due to the increasing use of MRI for both target and normal tissue delineation and the development of MR based delivery systems. One major issue in MRI-only RT is the assignment of electron densities (ED) to MRI scans for dose calculation and a similar need for attenuation correction can be found for hybrid PET/MR systems. The ED assigned MRI scan is here named a substitute CT (sCT). In this review, we report on a collection of typical performance values for a number of main approaches encountered in the literature for sCT generation as compared to CT. A literature search in the Scopus database resulted in 254 papers which were included in this investigation. A final number of 50 contributions which fulfilled all inclusion criteria were categorized according to applied method, MRI sequence/contrast involved, number of subjects included and anatomical site investigated. The latter included brain, torso, prostate and phantoms. The contributions geometric and/or dosimetric performance metrics were also noted. The majority of studies are carried out on the brain for 5-10 patients with PET/MR applications in mind using a voxel based method. T1 weighted images are most commonly applied. The overall dosimetric agreement is in the order of 0.3-2.5%. A strict gamma criterion of 1% and 1mm has a range of passing rates from 68 to 94% while less strict criteria show pass rates > 98%. The mean absolute error (MAE) is between 80 and 200 HU for the brain and around 40 HU for the prostate. The Dice score for bone is between 0.5 and 0.95. The specificity and sensitivity is reported in the upper 80s% for both quantities and correctly classified voxels average around 84%. The review shows that a variety of promising approaches exist that seem clinical acceptable even with standard clinical MRI sequences. A consistent reference frame for method benchmarking is probably necessary to move the field further towards a widespread clinical implementation. [ABSTRACT FROM AUTHOR]

Background: Post-Therapy-Pneumonitis (PTP) is a critical side effect of both, thoracic radio(chemo)therapy (R(C)T) and immune checkpoint inhibition (ICI). However, disease characteristics and patient-specific risk factors of PTP after combined R(C)T + ICI are less understood. Given that RT-triggered PTP is strongly dependent on the volume and dose of RT [1], driven by inflammatory mechanisms, we hypothesize that combination therapy of R(C)T with ICI influences the dose-volume-effect correlation for PTP. This study focuses on the development of a method for evaluation of alterations of dosimetric parameters for PTP after R(C)T with and without ICI. Methods and materials: PTP volumes were delineated on the follow-up diagnostic Computed Tomography (CT) and deformably matched to the planning CT for patients with PTP after thoracic R(C)T + ICI or R(C)T. Dose data was converted to 2-Gy equivalent doses (EQD2) and dosimetrically analyzed. Dosimetric and volumetric parameters of the segmented PTP volumes were analyzed. The method was exemplarily tested on an internal patient cohort including 90 patients having received thoracic R(C)T + ICI (39) and R(C)T (51). Thirtytwo patients with PTP were identified for further analysis. Additional data on previous chemotherapy, RT, smoking status and pulmonary co-morbidity were conducted. A matched pair analysis with regard to planning target volumes (PTV) was conducted for curative intended (definitive) and palliative patient cohorts individually. Results: The presented method was able to quantify and compare the dosimetric parameters of PTP for the different therapies. For our study group, no significant differences between R(C)T + ICI and R(C)T only was observed. However, the dosimetric analysis revealed large volumetric fractions (55%) of the PTP volumes to be located outside of high dose (EQD2 < 40 Gy) regions for R(C)T + ICI. There was a non-significant trend towards increased area under the curve of the dose volume histogram (AUC) values for R(C)T + ICI compared to R(C)T only (3743.6 Gy∙% vs. 2848.8 Gy∙%; p-value = 0.171). In contrast to the data for the palliative intended treatment group, for definitive R(C)T + ICI, data tended towards increased volumes with higher doses. Conclusions: The proposed method was capable to quantify dosimetric differences in the dose-volume-effect relationship of PTP for patients with R(C)T + ICI and patients with R(C)T only. In this exploratory analysis, no significant dosimetric differences within PTP volumes for the different groups could be observed. However, our observations suggest, that for safe application of thoracic R(C)T + ICI, further careful investigation of dosimetric prescription and analysis concepts with larger and conformer study groups is recommendable. [ABSTRACT FROM AUTHOR]

Background: The potential of carbon ion radiation therapy (CIRT) as a curative treatment for localized prostate cancer (PCa) has garnered attention due to its characteristic dose distribution. We prospectively collected and analyzed over five years to investigate the outcomes of localized PCa treated with CIRT at our institution. Patients and methods: The study included patients with histologically confirmed prostate adenocarcinoma. CIRT treatment was administered at a total dose of 57.6 Gy (RBE) in 16 fractions over four weeks. Uroflowmetry (UFM) and residual urine measurements were performed at various time points: before CIRT treatment, one month after starting CIRT, three months after treatment, and annually for five years starting from 1 year after the completion of CIRT. Prostate volume was measured using transrectal ultrasonography (TRUS). Results: A total of 304 prostate cancer patients were analyzed. UFM parameters were significantly worsened immediately after the treatment. However, they recovered to pretreatment levels after three months and remained stable until five years post-treatment. Notably, Average flow rate showed significant improvement after three years of treatment compared to before the treatment. Prostate volume decreased to 80% of baseline in patients treated with CIRT alone and to 60–70% of baseline in those receiving combined CIRT and either short- or long-term ADT. The logistic-binomial analysis identified post-voiding residual urine volume (PVR) as a significant factor for predicting adverse events in the acute phase. Conclusions: Following CIRT treatment, the voiding parameters in PCa patients significantly deteriorated immediately. However, after three months, they returned to their pre-treatment levels and remained stable for five years. [ABSTRACT FROM AUTHOR]

Background and aim: The present study aimed to evaluate the use of 18F-2-[18F]-fluoro-2-deoxy-d-glucose (FDG) PET/MRI (Positron emission tomography-computed tomography) in predicting the pathological response to neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) compared to the use of MRI (Magnetic Resonance Imaging) alone. Methods: We searched numerous databases, including PubMed, Scopus, Embase, and Science Direct, using curated keywords. The variance of each study was determined using the binomial distribution, and STATA version 14 was used to analyze the data by performing random-effect models. Additionally, we calculated study heterogeneity using the chi-squared test and I2 index and utilized funnel plots and Egger tests to assess publication bias. Results: The current investigation analyzed 239 patients from six published studies. The pooled estimated sensitivity and specificity of 18F-FDG PET/MRI was 0.91 (95% CI = 0.90 to 0.92, I2 = 100% and P = 0.000) and 0.62 (95% CI = 0.53 to 0.72, I2 = 99.8% and P = 0.000), respectively. Pooled sensitivity and specificity of MRI were 0.78 (95%CI = 0.59 to 0.96, I2 = 100% and P = 0.000) and 0.56 (95%CI = 0.33 to 0.80, I2 = 99.8% and P = 0.000), respectively. Conclusions: Based on our findings, the combined form of 18F-FDG PET/MRI imaging is more sensitive and specific than MRI alone for predicting response to NAC in BC patients. [ABSTRACT FROM AUTHOR]

Background: Craniopharyngioma is a rare and slow-growing benign sellar or parasellar epithelial tumor. The number of patients receiving proton beam therapy (PBT) has increased. This study aimed to systematically evaluate and analyze the comprehensive evidence regarding the safety and efficacy of PBT for craniopharyngioma. Methods: We searched four databases: the Cochrane Library, PubMed, Embase, and Web of Science. The period was from their inception to February 16, 2024. Two researchers independently screened the literature and extracted data. Results: Among 486 candidate articles, eight studies were included in our study. Exactly 393 patients with craniopharyngioma underwent PBT in these studies. These studies reported data on survival and toxicity. The median sample size was 42.5 patients. The median age was 9.1–37 years; the female proportion was 48.9%, and the median follow-up time was 29–91.4 months. All patients were treated once daily, five times a week, with a fraction of 1.8 Gy (RBE) per session. The median total dose was 54.0 Gy (RBE). The local control rates at 3 and 5 years in these studies were 99% and 93%, respectively. The overall survival rates at 3 and 5 years in these studies were both 100%. The incidence of acute and late toxicities was mainly grade 1–2. The main late toxicities included vascular and visual toxicities, hypothalamic obesity, endocrinopathy, and panhypopituitarism. Conclusions: PBT for craniopharyngioma, especially in children and adolescents, has shown impressive local control and acceptable acute and late toxicities. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to evaluate the inter-fraction reproducibility and intra-fraction stability of breast radiotherapy using voluntary deep-inspiration breath hold (DIBH) and free breathing (FB) based on an optical surface imaging system (OSIS). Methods: Seventeen patients (510 breath-hold sessions) treated using a field-in-field (FiF) technique and twenty patients (600 breath-free sessions) treated with a volume-modulated arc therapy (VMAT) technique were included in this retrospective study. All the patients were positioned with the guidance of CBCT and OSIS, and also monitored with OSIS throughout the whole treatment session. Eight setup variations in three directions were extracted from the treatment reports of OSIS for all sessions and were subsequently manually introduced to treatment plans, resulting in a total of 296 perturbed plans. All perturbed plans were recalculated, and the dose volume histograms (DVH) for the target and organs at risk (OAR) were analyzed. Results: The OSIS and CBCT for both DIBH and FB treatments showed a good agreement of less than 0.30 cm in each direction. The intra-fraction respiratory motion data during DIBH were −0.06 ± 0.07 cm, 0.12 ± 0.15 cm, and 0.12 ± 0.12 cm in the lateral, longitudinal, and vertical directions, respectively; for FB, the respiratory motion data were −0.02 ± 0.12 cm, 0.08 ± 0.18 cm, and 0.14 ± 0.20 cm, respectively. For the target, DIBH plans were more sensitive to setup errors; the mean deviations in D95 for CTV were 39.78 Gy–40.17 Gy for DIBH and 38.46 Gy–40.52 Gy for FB, respectively. For the OARs, the mean deviations of V10, V20, and Dmean to the heart; V5, V20, and Dmean to the ipsilateral lung; and Dmean to the breast were lower for the FB plan compared with the DIBH plan. Conclusion: Based on OSIS, our results indicate that both DIBH and FB can provide good reproducibility in the inter-fractions and stability in the intra-fractions. When the patient respiratory motion is large, the FB technology has greater possibility for the undercoverage of the target volume, while DIBH technology is more likely to result in increases in dose to OARs (the lung, heart, and contralateral breast). [ABSTRACT FROM AUTHOR]

Background: Durvalumab, an anti-PD-L1 immune checkpoint inhibitor, after radio-chemotherapy (RCT) has changed the management of locally advanced non-small cell lung cancer (LA NSCLC). A series of retrospective studies have investigated different cut-off of lymphocyte count (LyC) and neutrophil-to-lymphocyte ratio (NLR) to predict survival in LA NSCLC. None of these studies has validated their threshold in an independent group of patients. We wanted to assess the OS prognostic value of NLR and LyC in patients with LA NSCLC treated by RCT and durvalumab, with threshold determination and their validation in an external cohort. Methods: Patients were enrolled in four institutions between Oct. 2017 and Jan. 2022. Pre durvalumab LyC, neutrophils count (NC) and NLR were collected. To define NLR and LyC cut-off value predicting survival event, time dependent Receiver Operating Characteristics (ROC) curves was performed. Survival outcomes were estimated by the Kaplan-Meier method and differences were compared using univariate and multivariate Cox proportional hazard models. Results: We included 76 patients in the training set and 85 in the test set. The best cut off were 2,94 for NLR and 0,61 G/l for LyC to predict OS in the training set. For patients with NLR > 2,94, univariate analysis showed no significant deterioration in OS in either the training set (p = 0,066) or the test set (p = 0,12). Patients with LyC > 0,61 G/L, in univariate analysis, had longer OS in training set (p = 0,030) and in test set (p = 0,0062). This OS increase was not found in multivariate analysis (p = 0,057) in training set but was confirmed in test set (0,039). Conclusion: LyC > 0,61 G/l is associated with longer OS for LA NSCLC patient's treated with RCT and durvalumab in univariate analysis. In this context, a particular expectation for organs at risk sparing during RT to avoid lymphopenia seems important. Trial registration: Retrospectively registered. [ABSTRACT FROM AUTHOR]

The advancement of precision radiotherapy techniques, such as volumetric modulated arc therapy (VMAT), stereotactic body radiotherapy (SBRT), and particle therapy, highlights the importance of radiotherapy in the treatment of cancer, while also posing challenges for respiratory motion management in thoracic and abdominal tumors. MRI-guided radiotherapy (MRIgRT) stands out as state-of-art real-time respiratory motion management approach owing to the non-ionizing radiation nature and superior soft-tissue contrast characteristic of MR imaging. In clinical practice, MR imaging often operates at a frequency of 4 Hz, resulting in approximately a 300 ms system latency of MRIgRT. This system latency decreases the accuracy of respiratory motion management in MRIgRT. Artificial intelligence (AI)-based respiratory motion prediction has recently emerged as a promising solution to address the system latency issues in MRIgRT, particularly for advanced contour prediction and volumetric prediction. However, implementing AI-based respiratory motion prediction faces several challenges including the collection of training datasets, the selection of prediction methods, and the formulation of complex contour and volumetric prediction problems. This review presents modeling approaches of AI-based respiratory motion prediction in MRIgRT, and provides recommendations for achieving consistent and generalizable results in this field. [ABSTRACT FROM AUTHOR]

Background The increase in relative biological effectiveness (RBE) of proton beams at the distal edge of the spread out Bragg peak (SOBP) is a well-known phenomenon that is difficult to quantify accurately in vivo. For purposes of treatment planning, disallowing the distal SOBP to fall within vulnerable tissues hampers sparing to the extent possible with proton beam therapy (PBT). We propose the distal RBE uncertainty may be straightforwardly mitigated with a technique we call "range modulation". With range modulation, the distal falloff is smeared, reducing both the dose and average RBE over the terminal few millimeters of the SOBP. Methods One patient plan was selected to serve as an example for direct comparison of image-guided radiotherapy plans using non-range modulation PBT (NRMPBT), and range-modulation PBT (RMPBT). An additional plan using RMPBT was created to represent a re-treatment scenario (RMPBTrt) using a vertex beam. Planning statistics regarding dose, volume of the planning targets, and color images of the plans are shown. Results: The five plans generated for this patient reveal that in all cases dosimetric and device manufacturing advantages are able to be achieved using RMPBT. Organ at risk (OAR) doses to critical structures such as the cochleae, optic apparatus, hypothalamus, and temporal lobes can be selectively spared using this method. Concerns about the location of the RBE that did significantly impact beam selection and treatment planning no longer have the same impact on the process, allowing these structures to be spared dose and subsequent associated issues. Conclusions This present study has illustrated that RMPBT can improve OAR sparing while giving equivalent coverage to target volumes relative to traditional PBT methods while avoiding the increased RBE at the end of the beam. It has proven easy to design and implement and robust in our planning process. The method underscores the need to optimize treatment plans in PBT for both traditional energy dose in gray (Gy) and biologic dose (RBE). [ABSTRACT FROM AUTHOR]

Background: Radiotherapy (RT) is part of the curative treatment of approximately 70% of breast cancer (BC) patients. Wide practice variation has been reported in RT dose, fractionation and its treatment planning for BC. To decrease this practice variation, it is essential to first gain insight into the current variation in RT treatment between institutes. This paper describes the development of the NABON Breast Cancer Audit-Radiotherapy (NBCA-R), a structural nationwide registry of BC RT data of all BC patients treated with at least surgery and RT.Methods: A working group consisting of representatives of the BC Platform of the Dutch Radiotherapy Society selected a set of dose volume parameters deemed to be surrogate outcome parameters, both for tumour control and toxicity. Two pilot studies were carried out in six RT institutes. In the first pilot study, data were manually entered into a secured web-based system. In the second pilot study, an automatic Digital Imaging and Communications in Medicine (DICOM) RT upload module was created and tested.Results: The NBCA-R dataset was created by selecting RT parameters describing given dose, target volumes, coverage and homogeneity, and dose to organs at risk (OAR). Entering the data was made mandatory for all Dutch RT departments. In the first pilot study (N = 1093), quite some variation was already detected. Application of partial breast irradiation varied from 0 to 17% between the 6 institutes and boost to the tumour bed from 26.5 to 70.2%. For patients treated to the left breast or chest wall only, the average mean heart dose (MHD) varied from 0.80 to 1.82 Gy; for patients treated to the breast/chest wall only, the average mean lung dose (MLD) varied from 2.06 to 3.3 Gy. In the second pilot study 6 departments implemented the DICOM-RT upload module in daily practice. Anonymised data will be available for researchers via a FAIR (Findable, Accessible, Interoperable, Reusable) framework.Conclusions: We have developed a set of RT parameters and implemented registration for all Dutch BC patients. With the use of an automated upload module registration burden will be minimized. Based on the data in the NBCA-R analyses of the practice variation will be done, with the ultimate aim to improve quality of BC RT. Trial registration Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: Cervical and upper thoracic esophageal cancer (ESCA) presents treatment challenges due to limited clinical evidence. This multi-center study (ChC&UES) explores radical radio(chemo)therapy efficacy and safety, especially focusing on radiation dose. Method: We retrospectively analyzed clinical data from 1,422 cases across 8 medical centers. According to the radiation dose for primary gross tumor, patients were divided into standard dose radiotherapy (SD, 50–55 Gy) or high dose (HD, > 55 Gy) radiotherapy. HD was further subdivided into conventional- high-dose group (HD-conventional, 55–63 Gy) and ultra-high-dose group (HD-ultra, ≥ 63 Gy). Primary outcome was Overall Survival (OS). Results: The median OS was 33.0 months (95% CI: 29.401–36.521) in the whole cohort. Compared with SD, HD shown significant improved survival in cervical ESCA in Kaplan-Meier (P = 0.029) and cox multivariate regression analysis (P = 0.024) while shown comparable survival in upper thoracic ESCA (P = 0.735). No significant difference existed between HD-conventional and HD-ultra in cervical (P = 0.976) and upper thoracic (P = 0.610) ESCA. Incidences of radiation esophagitis and pneumonia from HD were comparable to SD (P = 0.097, 0.240), while myosuppression risk was higher(P = 0.039). The Bonferroni method revealed that, for both cervical and upper thoracic ESCA, HD-ultra enhance the objective response rate (ORR) compared to SD (P < 0.05). Conclusion: HD radiotherapy benefits cervical but not upper thoracic ESCA, while increasing bone marrow suppression risk. Further dose escalating (≥ 63 Gy) doesn't improve survival but enhances ORR. [ABSTRACT FROM AUTHOR]

Objective: To identify variables associated with a patients' ability to reproducibly hold their breath for deep-inspiration breath-hold (DIBH) radiotherapy (RT) and to develop a predictive model for DIBH eligibility. Methods: This prospective, single-institution, IRB-approved observational study included women with left-sided breast cancer treated between January 2023 and March 2024. Patients underwent multiple breath-hold sessions over 2–3 consecutive days. DIBH waveform metrics and clinical factors were recorded and analysed. Logistic mixed modelling was used to predict DIBH eligibility, and a temporal validation cohort was used to assess model performance. Results: In total, 253 patients were included, with 206 in the model development cohort and 47 in the temporal validation cohort. The final logistic mixed model identified increasing average breath-hold duration (OR, 95% CI: 0.308, 0.104–0.910. p = 0.033) and lower amplitude (OR, 95% CI: 0.737, 0.641–0.848. p < 0.001) as significant predictors of DIBH eligibility. Increasing age was associated with higher odds of being ineligible for DIBH (OR, 95% CI: 1.040, 1.001–1.081. p = 0.044). The model demonstrated good discriminative performance in the validation cohort with an AUC of 80.9% (95% CI: 73.0-88.8). Conclusion: The identification of variables associated with DIBH eligibility and development of a predictive model has the potential to serve as a decision-support tool. Further external validation is required before its integration into routine clinical practice. [ABSTRACT FROM AUTHOR]

Background: Local therapies may benefit patients with oligometastatic cancer. However, there were limited data about pancreatic cancer. Here, we compared the efficacy and safety of stereotactic body radiation therapy (SBRT) to the primary tumor and all oligometastases with SBRT to the primary tumor alone in patients with metastatic pancreatic cancer. Methods: A retrospective review of patients with synchronous oligometastatic pancreatic cancer (up to 5 lesions) receiving SBRT to all lesions (including all oligometastases and the primary tumor) were performed. Another comparable group of patients with similar baseline characteristics, including metastatic burden, SBRT doses, and chemotherapy regimens, receiving SBRT to the primary tumor alone were identified. The primary endpoint was overall survival (OS). The secondary endpoints were progression frees survival (PFS), polyprogression free survival (PPFS) and adverse events. Results: There were 59 and 158 patients receiving SBRT to all lesions and to the primary tumor alone. The median OS of patients with SBRT to all lesions and the primary tumor alone was 10.9 months (95% CI 10.2–11.6 months) and 9.3 months (95% CI 8.8–9.8 months) (P < 0.001). The median PFS of two groups was 6.5 months (95% CI 5.6–7.4 months) and 4.1 months (95% CI 3.8–4.4 months) (P < 0.001). The median PPFS of two groups was 9.8 months (95% CI 8.9–10.7 months) and 7.8 months (95% CI 7.2–8.4 months) (P < 0.001). Additionally, 14 (23.7%) and 32 (20.2%) patients in two groups had grade 3 or 4 treatment-related toxicity. Conclusions: SBRT to all oligometastases and the primary tumor in patients with pancreatic cancer may improve survival, which needs prospective verification. [ABSTRACT FROM AUTHOR]

Background: Adaptive therapy has been enormously improved based on the art of generating adaptive computed tomography (ACT) from planning CT (PCT) and the on-board image used for the patient setup. Exploiting the ACT, this study evaluated the dose delivered to patients with non-small-cell lung cancer (NSCLC) patients treated with stereotactic ablative radiotherapy (SABR) and derived relationship between the delivered dose and the parameters obtained through the evaluation procedure. Methods: SABR treatment records of 72 patients with NSCLC who were prescribed a dose of 60 Gy (Dprescribed) to the 95% volume of the planning target volume (PTV) in four fractions were analysed in this retrospective study; 288 ACTs were generated by rigid and deformable registration of a PCT to a cone-beam computed tomography (CBCT) per fraction. Each ACT was sent to the treatment planning system (TPS) and treated as an individual PCT to calculate the dose. Delivered dose to a patient was estimated by averaging four doses calculated from four ACTs per treatment. Through the process, each ACT provided the geometric parameters, such as mean displacement of the deformed PTV voxels (Warpmean) and Dice similarity coefficient (DSC) from deformation vector field, and dosimetric parameters, e.g. difference of homogeneity index (ΔHI, HI defined as (D2%-D98%)/Dprescribed*100) and mean delivered dose to the PTV (Dmean), obtained from the dose statistics in the TPS. Those parameters were analyzed using multiple linear regression and one-way-ANOVA of SPSS® (version 27). Results: The prescribed dose was confirmed to be fully delivered to internal target volume (ITV) within maximum difference of 1%, and the difference between the planned and delivered doses to the PTV was agreed within 6% for more than 95% of the ACT cases. Volume changes of the ITV during the treatment course were observed to be minor in comparison of their standard deviations. Multiple linear regression analysis between the obtained parameters and the dose delivered to 95% volume of the PTV (D95%) revealed four PTV parameters [Warpmean, DSC, ΔHI between the PCT and ACT, Dmean] and the PTV D95% to be significantly related with P-values < 0.05. The ACT cases of high ΔHI were caused by higher values of the Warpmean and DSC from the deformable image registration, resulting in lower PTV D95% delivered. The mean values of PTV D95% and Warpmean showed significant differences depending on the lung lobe where the tumour was located. Conclusions: Evaluation of the dose delivered to patients with NSCLC treated with SABR using ACTs confirmed that the prescribed dose was accurately delivered to the ITV. However, for the PTV, certain ACT cases characterised by high HI deviations from the original plan demonstrated variations in the delivered dose. These variations may potentially arise from factors such as patient setup during treatment, as suggested by the statistical analyses of the parameters obtained from the dose evaluation process. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the relationship between delivered radiation (RT) and post-RT inversion-recovery ultrashort-echo-time (IR-UTE) MRI signal-intensity (SI) in gynecologic cancer patients treated with high-dose-rate (HDR) brachytherapy (BT). Methods: Seven patients underwent whole-pelvis RT (WPRT) followed by BT to the high-risk clinical target volume (HR-CTV). MR images were acquired at three time-points; pre-RT, post-WPRT/pre-BT, and 3–6 months post-BT. Diffuse-fibrosis (FDiffuse) was imaged with a non-contrast dual-echo IR (inversion time [TI] = 60 ms) UTE research application, with image-subtraction of the later echo, only retaining the ultrashort-echo SI. Dense-fibrosis (FDense) imaging utilized single-echo Late-Gadolinium-Enhanced IR-UTE, acquired ∼ 15 min post-Gadavist injection. Resulting FDiffuse and FDense SI were normalized to the corresponding gluteal-muscle SI. Images were deformably registered between time-points based on normal tissue anatomy. The remnant tumor at both time-points was segmented using multi-parametric MRI. Contours corresponding to the 50%, 100%, 150%, and 200% isodose lines (IDLs) of the prescription BT-dose were created. Mean FDiffuse and FDense SI within (i) each IDL contour and (ii) the remnant tumor were calculated. Post-BT FDiffuse and FDense SI were correlated with prescribed BT-dose. To determine the relationship between BT-dose and IR-UTE SI, the differences in the post-BT FDense across IDLs was determined using paired t-tests with Bonferroni correction. Results: FDense was higher in regions of higher dose for 6/7 patients, with mean ± SD values of 357 ± 103% and 331 ± 97% (p =.03) in the 100% and 50% IDL, respectively. FDense was higher in regions of higher dose in the responsive regions with mean ± SD values of 380 ± 122% and 356 ± 135% (p =.03) in the 150% and 50% IDL, respectively. Within the segmented remnant tumor, an increase in prescribed dose correlated with an increase in FDense post-BT (n = 5, r =.89, p =.04). Post-BT FDiffuse inversely correlated (n = 7, r = -.83, p =.02) with prescribed BT-dose within the 100% IDL. Conclusions: Results suggest that FDense SI 3–6 months post-BT is a sensitive measure of tissue response to heterogeneous BT radiation-dose. Future studies will validate whether FDiffuse and FDense are accurate biomarkers of fibrotic radiation response. [ABSTRACT FROM AUTHOR]

Breast conserving treatment typically involves surgical excision of tumor and adjuvant radiotherapy targeting the breast area or tumor bed. Accurately defining the tumor bed is challenging and lead to irradiation of greater volume of healthy tissues. Preoperative stereotactic body radiotherapy (SBRT) which target tumor may solves that issues. We conducted a systematic literature review to evaluates the early toxicity and cosmetic outcomes of this promising treatment approach. Secondary we reviewed pathological complete response (pCR) rates, late toxicity, patient selection criteria and radiotherapy protocols. We retrieved literature from PubMed, Scopus, Web of Science, Cochrane, ScienceDirect, and ClinicalTrials.gov. The study adhered to the PRISMA 2020 guidelines. Ten prospective clinical trials (7 phase II, 3 phase I), encompassing 188 patients (aged 18–75 years, cT1-T3 cN0-N3 cM0, primarily with ER/PgR-positive, HER2-negative status,), were analyzed. Median follow-up was 15 months (range 3–30). Treatment involved single-fraction SBRT (15-21Gy) in five studies and fractionated (19.5–31.5Gy in 3 fractions) in the rest. Time interval from SBRT to surgery was 9.5 weeks (range 1–28). Acute and late G2 toxicity occurred in 0–17% and 0–19% of patients, respectively, G3 toxicity was rarely observed. The cosmetic outcome was excellent in 85–100%, fair in 0–10% and poor in only 1 patient. pCR varied, showing higher rates (up to 42%) with longer intervals between SBRT and surgery and when combined with neoadjuvant systemic therapy (up to 90%). Preoperative SBRT significantly reduce overall treatment time, enabling to minimalize volumes. Early results indicate excellent cosmetic effects and low toxicity. [ABSTRACT FROM AUTHOR]

Background: We report the results of a retrospective analysis of localized prostate cancer (LPCa) treated with transperineal ultrasound image-guided radiotherapy (TPUS-IGRT). Methods: A 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. Results: A 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. Conclusion: These 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. [ABSTRACT FROM AUTHOR]

Background: PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA. Methods: This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC). Results: 67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients. Conclusion: Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out. [ABSTRACT FROM AUTHOR]