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Abstract Background Complex high-precision radiotherapy, such as stereotactic body radiotherapy (SBRT), should only be offered to patients with sufficiently long survival. In the context of bone metastases radiotherapy, low rates of treatment close to the end of life, e.g. last 30 days (RT30), may serve as a quality of care indicator. While traditional, pain-relieving short-course regimens have been studied comprehensively, real-world SBRT results are still limited. Methods Retrospective analysis (2010–2023, n = 1117 episodes) of patients with bone metastases treated with traditional single-fraction (8 Gy × 1) or multi-fraction regimens (often 4 Gy × 5 or 3 Gy × 10) compared to stereotactic single-fraction (12–16 Gy × 1) or multi-fraction regimens. Results Except for gender, almost all baseline variables were uneven distributed. Failure to complete fractionated radiotherapy was uncommon in the stereotactic (4%) and non-stereotactic group (3%), p = 1.0. With regard to RT30, relevant differences emerged (19% for 8-Gy single-fraction versus 0% for stereotactic single-fraction, p = 0.01). The corresponding figures were 11% for multi-fraction non-stereotactic and 2% for multi-fraction stereotactic, p = 0.08. Median overall survival was shortest after 8-Gy single-fraction irradiation (4.2 months) and longest after stereotactic multi-fraction treatment (13.9 months). Neither stereotactic radiotherapy nor multi-fraction treatment improved survival in multivariate Cox regression analysis. Factors significantly associated with longer survival included better performance status, lower LabBM score (5 standard blood test results), stable disease outside of irradiated area(s), metachronous distant metastases, longer time interval from metastatic disease to bone irradiation, and outpatient status. Conclusion The implementation of SBRT for selected patients has resulted in low rates of non-completion and RT30. Optimal selection criteria remain to be determined, but in current clinical practice we exclude patients with poor performance status, unfavorable blood test results (high LabBM score) and progressive disease sites not amenable to SBRT. Established, guideline-endorsed short-course regimens, especially 8-Gy single-fraction treatment, continue to represent an important palliative approach.

Abstract Objective This study aims to evaluate the efficacy and safety of 3D printing technology in brachytherapy for cervical cancer, comparing its outcomes with conventional free hand implantation brachytherapy. Methods A total of 50 cervical cancer patients treated at the First Affiliated Hospital of Gannan Medical College from January 2019 to July 2023 were included in this study. Patients were divided into two groups: 25 patients received intensity-modulated radiotherapy (IMRT) combined with 3D-printed brachytherapy, and 25 patients underwent IMRT combined with free hand brachytherapy implantation. Key indicators analyzed included short-term therapeutic effects, survival outcomes, operation times, the number of CT scans, the number of needles inserted, dosimetric parameters, and complications. Results The use of 3D-printed brachytherapy significantly improved the safety of radiation therapy operations, especially for large tumors (≥ 30 mm), by providing more precise dose distribution and reducing the radiation doses received by critical organs such as the bladder and rectum. Compared to the artificial implant group (88% prevalence), the 3D-printed brachytherapy group showed a significantly lower incidence of radiation enteritis (29.2% prevalence, p

Abstract Background Postoperative progressive cerebral edema and hemorrhage (PPCEH) are major complications after meningioma resection, yet their preoperative predictive studies are limited. The aim is to develop and validate a multiparametric MRI machine learning model to predict PPCEH after meningioma resection. Methods This retrospective study included 148 patients with meningioma. A stratified three-fold cross-validation was used to split the dataset into training and validation sets. Radiomics features from the tumor enhancement (TE) and peritumoral brain edema (PTBE) regions were extracted from T1WI, T2WI, and ADC maps. Support vector machine constructed different radiomics models, and logistic regression explored clinical risk factors. Prediction models, integrating clinical and radiomics features, were evaluated using the area under the curve (AUC), visualized in a nomogram. Results The radiomics model based on TE and PTBE regions (training set mean AUC: 0.85 (95% CI: 0.78–0.93), validation set mean AUC: 0.77 (95%CI: 0.63–0.90)) outperformed the model with TE region solely (training set mean AUC: 0.83 (95% CI: 0.76–0.91), validation set mean AUC: 0.73 (95% CI: 0.58–0.87)). Furthermore, the combined model incorporating radiomics features, and clinical features of preoperative peritumoral edema and tumor boundary adhesion, had the best predictive performance, with AUC values of 0.87 (95% CI: 0.80–0.94) and 0.84 (95% CI: 0.72–0.95) for the training and validation set. Conclusions We developed a novel model based on clinical characteristics and multiparametric radiomics features derived from TE and PTBE regions, which can accurately and non-invasively predict PPCEH after meningioma resection. Additionally, our findings suggest the crucial role of PTBE radiomics features in understanding the potential mechanisms of PPCEH.

Abstract Background and purpose Magnetic resonance imaging is indispensable for the preoperative diagnosis of glioma. This study aimed to investigate the role of the apparent diffusion coefficient values as predictors of survival in patients with gliomas. Methods and materials A retrospective analysis was conducted on 101 patients with gliomas who underwent surgery between 2015 and 2020. Diffusion-weighted MRI was performed before the surgery. The regions of interest were categorized into parenchymal area, non-enhancing peritumoral area, and necrotic or cystic area. All the patients were divided into three subgroups: the parenchyma group, the non-enhancing peritumoral signal abnormality group, and the necrosis or cyst group. Univariate and multivariate analyses were performed using COX regression. Results In the parenchymal group, Ki67, P53, IDH, and the high or low ADC values were identified as independent prognosticators for disease-free survival, while Ki67, IDH, and the high or low ADC values for overall survival. In the non-enhancing peritumoral signal abnormality group, Ki67, P53, IDH, and the ADC parenchymal area/ADC non−enhancing peritumoral area ratio were identified as independent prognostic factors for disease-free survival, while Ki67, IDH, and the ADC parenchymal area/ADC non−enhancing peritumoral area ratio for overall survival. In the necrosis or cyst group, Ki67 was significantly associated with disease-free survival, while Ki67 and the ADC value of the necrotic or cystic area for overall survival. Conclusions The ADC values, including the ADC value in the parenchymal area, the ADC parenchymal area/ADC non−enhancing peritumoral area ratio, and the ADC value in the necrotic or cystic area, can serve as an efficient and potential index for predicting the survival of patients with glioma.

Abstract Background Head and neck squamous cell carcinoma (HNSCC) negative for Human Papillomavirus (HPV) has remained a difficult to treat entity, whereas tumors positive for HPV are characterized by radiosensitivity and favorable patient outcome. On the cellular level, radiosensitivity is largely governed by the tumor cells` ability to repair radiation-induced DNA double-strand breaks (DSBs), but no biomarker is established that could guide clinical decision making. Therefore, we tested the impact of the expression levels of ATM, the central kinase of the DNA damage response as well as DNA-PKcs and Ku80, two major factors in the main DSB repair pathway non-homologous end joining (NHEJ). Methods A tissue microarray of a single center HNSCC cohort was stained for ATM, DNA-PKcs and Ku80 and the expression scored based on staining intensity and the percentages of tumor cells stained. Scores were correlated with clinicopathological parameters and survival. Results Samples from 427 HNSCC patients yielded interpretable stainings and were scored following an established algorithm. The majority of tumors showed strong expression of both NHEJ factors, whereas the expression of ATM varied more. The expression scores of ATM and DNA-PKcs were not associated with patient survival. For HPV-negative HNSCC, the minority of tumors without strong Ku80 expression trended towards superior survival when treatment included radiotherapy. Focusing stronger on staining intensity to define the subgroup with lowest and therefore potentially insufficient expression levels in the HPV-negative subgroup, we observed significantly better overall survival for patients treated with radiotherapy but not with surgery alone. Conclusions Our data suggest that HPV-negative HNSCC with particularly low Ku80 expression represent a highly radiosensitive subpopulation. Confirmation in independent cohorts is required.

Abstract Follicular cell-derived thyroid carcinomas constitute the majority of thyroid malignancies. This heterogeneous group of tumours includes well differentiated, poorly differentiated, and undifferentiated forms, which have distinct pathological features, clinical behaviour, and prognosis. Positron emission tomography with 2-[18F]fluoro-2-deoxy-D-glucose combined with computed tomography ([18F]FDG PET/CT) is an imaging modality used in routine clinical practice for oncological patients. [18F]FDG PET/CT has emerged as a valuable tool for identifying patients at high risk of poor clinical outcomes and for facilitating individualized clinical decision-making. The aim of this comprehensive review is to summarize current knowledge regarding the role of [18F]FDG PET/CT in primary diagnosis, treatment, and follow-up of follicular cell-derived thyroid carcinomas considering the degree of differentiation. Controversial issues, including significance of accidentally detected [18F]FDG uptake in the thyroid, the role of [18F]FDG PET/CT in the early assessment of response to molecular targeted therapies, and its prognostic value are discussed in detail.

Abstract Background Recurrent and locally advanced gynecological malignancies have a poor prognosis. In particularly, pelvic local recurrence after previous radiotherapy and/or positive resection margins during surgical treatment for recurrent disease result in low survival rates. Consequently, locoregional control is of utmost importance in this cohort of patients. The aim of this study was to analyze treatment outcomes and determine prognostic factors for patients treated with surgery and intraoperative radiotherapy (IORT) for recurrent and locally advanced gynecological malignancies. Methods 40 patients who underwent surgical treatment and IORT between 2010 and 2022 were eligible for inclusion. The median follow-up time was 22 months. The outcomes measured were locoregional control (LRC), overall survival (OS), and survival without distant metastases (DMFS). The Cox proportional hazards model was used for univariate and multivariate analysis to assess the impact of patient variables and treatment factors on the endpoints mentioned. The following variables were analyzed: age at surgical treatment and IORT and initial diagnosis (13 Gy) and technique (high dose radiotherapy (HDR) vs. IORT using electrons, (IOERT)). Survival curves were generated using the Kaplan-Meier method. Results The mean IORT dose was 13.8 Gy (range 10–18 Gy). Cervical carcinoma was most frequently found in 27.5% of patients followed by endometrial carcinoma and vulvar carcinoma in 25% respectively. The final histopathologic results after surgery with IORT showed no residual tumour in 24 patients (60%), microscopic residual disease in 5 patients (12.5%), resection status could not be evaluated in three patients (7.5%) and the resection status was unknown in eight patients (20%). Subsequently, 27.5% of patients also received adjuvant radiotherapy of the local recurrence bed. However, after IORT, 65% of the women suffered a recurrence. Of these, the recurrences were localized: in-field 32.5%, out-of-field 22.5% and margin-of-field 12.5%. The 3- and 5-year OS was 69% and 55% respectively. The 3- and 5-year LRC was 56% respectively. The 3- and 5-year DMFS was 66% and 49%. Whereas the comparison between groups by IORT dose level (≤ 13 vs. >13 Gy) showed a non-significant trend in favor of the higher dose only for OS (p = 0.094), but not in LRC and DMFS (p > 0.05). OS and DMFS, but not LRC, differed significantly between the HDR-IORT and IOERT groups (p = 0.06 and p = 0.03,) in favor of the HDR-IORT technique. For HDR-IORT technique a trend towards superior OS and LRC was observed in the univariate analysis: HR 3.76, CI 95%: 0.95–14.881, p = 0.059 and HR 2.165 CI 95%: 0.916–5.114, p = 0.078 Conclusions The survival rate for pelvic recurrence in gynecological malignancies remains poor and comparable with historical data from the last two decades. Particularly HDR-IORT, appears to provide a long-term oncological benefit in carefully selected patients.

Abstract Background and introduction Increasing evidence suggests that a subgroup of patients with oligometastatic cancer might achieve a prolonged disease-free survival through local therapy for all active cancer lesions. Our aims are to investigate the impact of brain metastases on the classification, treatment, and outcome in these patients. Materials and methods We analyzed a total of 7,000 oncological positron emission tomography scans to identify patients with extracranial oligometastatic disease (defined as ≤ 5 intra- or extra-cranial metastases). Concurrent magnetic resonance imaging brain was assessed to quantify intracranial tumor burden. We investigated the impact of brain metastases on oligometastatic disease state, therapeutic approaches, and outcome. Predictors for transitioning from oligo- to polymetastatic states were evaluated using regression analysis. Results A total of 106 patients with extracranial oligometastases and simultaneous brain metastases were identified, primarily originating from skin or lung/pleura cancers (90%, n = 96). Brain metastases caused a transition from an extracranial oligometastatic to a whole-body polymetastatic state in 45% (n = 48) of patients. While oligometastatic patients received systemic therapy (55% vs. 35%) more frequently and radiotherapy for brain metastases was more often prescribed to polymetastatic patients (44% vs. 26%), the therapeutic approach did not differ systematically between both sub-groups. The oligometastatic sub-group had a median overall survival of 28 months compared to 10 months in the polymetastatic sub-group (p

Abstract Background This study aims to assess the clinical efficacy of elective neck irradiation (ENI) in patients with esthesineuroblastoma (ENB), a rare malignant neoplasm, who are clinically node-negative. Methods We conducted a retrospective analysis of 178 patients newly diagnosed with ENB at our institution between 2009 and 2021. Propensity score matching (PSM) was employed to compare node-negative patients treated with and without ENI. We extensively examined survival outcomes and treatment failure. Results Of the 178 participants, 149 (83.7%) were lymph node-negative and staged in Modified Kadish A-C. 96 patients underwent ENI treatment, while 53 did not. At baseline, patients who received ENI differed from those who did not in terms of radiotherapy technique, staging, orbital invasion, surgical mode, and chemotherapy. After PSM, 43 pairs were available for analysis. ENI was observed to extend overall survival (OS, 5-year 73.9% vs. 84.0%; 3-year 76.9% vs. 97.1%, p = 0.022), progression-free survival (PFS, 5-year 38.5% vs. 84.6%; 3-year 50.5% vs. 94.5%, p

Abstract Purpose To conduct a head-to-head comparison between deep learning (DL) and radiomics models across institutions for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and to investigate the model robustness and generalizability through rigorous internal and external validation. Methods This retrospective study included 2304 preoperative images of 576 HCC lesions from two centers, with MVI status determined by postoperative histopathology. We developed DL and radiomics models for predicting the presence of MVI using B-mode ultrasound, contrast-enhanced ultrasound (CEUS) at the arterial, portal, and delayed phases, and a combined modality (B + CEUS). For radiomics, we constructed models with enlarged vs. original regions of interest (ROIs). A cross-validation approach was performed by training models on one center’s dataset and validating the other, and vice versa. This allowed assessment of the validity of different ultrasound modalities and the cross-center robustness of the models. The optimal model combined with alpha-fetoprotein (AFP) was also validated. The head-to-head comparison was based on the area under the receiver operating characteristic curve (AUC). Results Thirteen DL models and 25 radiomics models using different ultrasound modalities were constructed and compared. B + CEUS was the optimal modality for both DL and radiomics models. The DL model achieved AUCs of 0.802–0.818 internally and 0.667–0.688 externally across the two centers, whereas radiomics achieved AUCs of 0.749–0.869 internally and 0.646–0.697 externally. The radiomics models showed overall improvement with enlarged ROIs (P 0.05 for all modalities, 1.6–2.1% differences in AUC for the optimal modality), whereas the radiomics models had relatively limited robustness across the two centers (12% drop-off in AUC for the optimal modality). Adding AFP improved the DL models (P 0.05). Conclusion Cross-institutional validation indicated that DL demonstrated better robustness than radiomics for preoperative MVI prediction in patients with HCC, representing a promising solution to non-standardized ultrasound examination procedures.

Abstract Background To explore the value of dual-energy computed tomography (DECT) in differentiating pathological subtypes and the expression of immunohistochemical markers Ki-67 and thyroid transcription factor 1 (TTF-1) in patients with non-small cell lung cancer (NSCLC). Methods Between July 2022 and May 2024, patients suspected of lung cancer who underwent two-phase contrast-enhanced DECT were prospectively recruited. Whole-tumor volumetric and conventional spectral analysis were utilized to measure DECT parameters in the arterial and venous phase. The DECT parameters model, clinical-CT radiological features model, and combined prediction model were developed to discriminate pathological subtypes and predict Ki-67 or TTF-1 expression. Multivariate logistic regression analysis was used to identify independent predictors. The diagnostic efficacy was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong’s test. Results This study included 119 patients (92 males and 27 females; mean age, 63.0 ± 9.4 years) who was diagnosed with NSCLC. When applying the DECT parameters model to differentiate between adenocarcinoma and squamous cell carcinoma, ROC curve analysis indicated superior diagnostic performance for conventional spectral analysis over volumetric spectral analysis (AUC, 0.801 vs. 0.709). Volumetric spectral analysis exhibited higher diagnostic efficacy in predicting immunohistochemical markers compared to conventional spectral analysis (both P

Abstract Background Directly-injected therapies (DIT) include a broad range of agents within a developing research field in cancer immunotherapy, with encouraging clinical trial results in various tumour subtypes. Currently, the majority of such therapies are only available within clinical trials; however, more recently, talimogene laherparepvec (T-VEC, Imlygic) has been approved as the first oncolytic virus therapy in the USA and Europe. Our institution contributes to multiple different trials exploring the efficacy of DIT, the majority of which are performed by oncologists in clinic. However, specific, challenging cases – mainly neck tumours – require image-guided administration. Main body This review article addresses the technical and logistical factors relevant to the incorporation of image-guided DIT into an established ultrasound service. Image-guidance (usually with ultrasound) is frequently needed for certain targets that cannot be palpated or are in high-risk locations, e.g. adjacent to blood vessels. A multi-disciplinary approach is essential to facilitate a safe and efficient service, including careful case-selection. Certain protocols and guidance need to be followed when incorporating such a service into an established ultrasound practice to enhance efficiency and optimise safety. Key learning points are drawn from the literature and from our early experience at a tertiary cancer centre following image guided DIT for an initial cohort of 22 patients (including 11 with a neck mass), addressing trial protocols, pre-procedure work-up, organisation, planning, consent, technical aspects, procedure tolerability, technical success, and post-procedure considerations. Conclusion With appropriate planning and coordination, and application of the learning points discussed herein, image-guided administration of DIT can be safely and efficiently incorporated into an established procedural ultrasound list. This has relevance to cancer centres, radiology departments, individual radiologists, and other team members with a future role in meeting the emerging need for these procedures. This paper provides advice on developing such an imaging service, and offers certain insights into the evolving remit of radiologists within cancer care in the near future.

Abstract Objective This study aims to develop and validate a predictive model that integrates clinical features, MRI radiomics, and nutritional-inflammatory biomarkers to forecast progression-free survival (PFS) in cervical cancer (CC) patients undergoing concurrent chemoradiotherapy (CCRT). The goal is to identify high-risk patients and guide personalized treatment. Methods We performed a retrospective analysis of 188 patients from two centers, divided into training (132) and validation (56) sets. Clinical data, systemic inflammatory markers, and immune-nutritional indices were collected. Radiomic features from three MRI sequences were extracted and selected for predictive value. We developed and evaluated five models incorporating clinical features, nutritional-inflammatory indicators, and radiomics using C-index. The best-performing model was used to create a nomogram, which was validated through ROC curves, calibration plots, and decision curve analysis (DCA). Results Model 5, which integrates clinical features, Systemic Immune-Inflammation Index (SII), Prognostic Nutritional Index (PNI), and MRI radiomics, showed the highest performance. It achieved a C-index of 0.833 (95% CI: 0.792–0.874) in the training set and 0.789 (95% CI: 0.679–0.899) in the validation set. The nomogram derived from Model 5 effectively stratified patients into risk groups, with AUCs of 0.833, 0.941, and 0.973 for 1-year, 3-year, and 5-year PFS in the training set, and 0.812, 0.940, and 0.944 in the validation set. Conclusions The integrated model combining clinical features, nutritional-inflammatory biomarkers, and radiomics offers a robust tool for predicting PFS in CC patients undergoing CCRT. The nomogram provides precise predictions, supporting its application in personalized patient management.

Abstract Tumor vascular physiology is an important determinant of disease progression as well as the therapeutic outcome of cancer treatment. Angiogenesis or the lack of it provides crucial information about the tumor’s blood supply and therefore can be used as an index for cancer growth and progression. While standalone anti-angiogenic therapy demonstrated limited therapeutic benefits, its combination with chemotherapeutic agents improved the overall survival of cancer patients. This could be attributed to the effect of vascular normalization, a dynamic process that temporarily reverts abnormal vasculature to the normal phenotype maximizing the delivery and intratumor distribution of chemotherapeutic agents. Longitudinal monitoring of vascular changes following antiangiogenic therapy can indicate an optimal window for drug administration and estimate the potential outcome of treatment. This review primarily focuses on the status of various imaging modalities used for the longitudinal characterization of vascular changes before and after anti-angiogenic therapies and their clinical prospects.

Abstract Background Using dose-painted intensity-modulated radiation therapy, specific dose volume constraints or implantation of tissue expanders prior to radiotherapy are validated options for reducing radiation dose on the bowel and therefore minimizing acute gastrointestinal toxicity during chemoradiation for anorectal malignancies. We describe the rare case of a female patient with a locally advanced anal carcinoma where a large myomatous uterus served as a natural spacer to protect the bowel during radiation therapy. Case presentation Initially the patient presented with anal pain, proctoscopy followed by an excisional biopsy confirmed the diagnosis of a squamous cell carcinoma of the anus. Imaging examination showed a locally advanced tumor and in addition a large uterus with typical leiomyomas up to 11.5 cm in diameter. The patient underwent chemoradiation; because of the large leiomyomas there was almost no dose burden for the small intestine and therefore practically no gastrointestinal toxicity. Conclusion As we know, this report describes the situation that a large myomatous uterus served as a natural spacer during radiation therapy in a way that is unique to date.

Abstract Background To investigate the impact of using contrast-enhanced computed tomography (CHCT) in the dosimetry of stereotactic body radiation therapy (SBRT) for liver metastases treated with MR-Linac. Methods A retrospective study was conducted on 21 liver cancer patients treated with SBRT (50 Gy in 5 fractions) using a 1.5 Tesla Unity MR-Linac. The clinical treatment plans optimised on plain computed tomography (pCT) were used as reference. The electronic density (ED) of regions of interest (ROIs) including the liver, duodenum, esophagus, spinal cord, heart, ribs, and lungs, from pCT and CHCT, was analysed. The average ED of each ROI from CHCT was used to generate synthetic CT (sCT) images by assigning the average ED value from the CHCT to the pCT. Clinical plans were recalculated on sCT images. Dosimetric comparisons between the original treatment plan (TPpCT) and the sCT plan (TPsCT) were performed using dose-volume histogram (DVH) parameters, and gamma analysis. Results Significant ED differences (p

Abstract Purpose To explore the application value of a multimodal deep learning radiomics (MDLR) model in predicting the risk status of postoperative progression in solid stage I non-small cell lung cancer (NSCLC). Materials and Methods A total of 459 patients with histologically confirmed solid stage I NSCLC who underwent surgical resection in our institution from January 2014 to September 2019 were reviewed retrospectively. At another medical center, 104 patients were reviewed as an external validation cohort according to the same criteria. A univariate analysis was conducted on the clinicopathological characteristics and subjective CT findings of the progression and non-progression groups. The clinicopathological characteristics and subjective CT findings that exhibited significant differences were used as input variables for the extreme learning machine (ELM) classifier to construct the clinical model. We used the transfer learning strategy to train the ResNet18 model, used the model to extract deep learning features from all CT images, and then used the ELM classifier to classify the deep learning features to obtain the deep learning signature (DLS). A MDLR model incorporating clinicopathological characteristics, subjective CT findings and DLS was constructed. The diagnostic efficiencies of the clinical model, DLS model and MDLR model were evaluated by the area under the curve (AUC). Results Univariate analysis indicated that size (p = 0.004), neuron-specific enolase (NSE) (p = 0.03), carbohydrate antigen 19 − 9 (CA199) (p = 0.003), and pathological stage (p = 0.027) were significantly associated with the progression of solid stage I NSCLC after surgery. Therefore, these clinical characteristics were incorporated into the clinical model to predict the risk of progression in postoperative solid-stage NSCLC patients. A total of 294 deep learning features with nonzero coefficients were selected. The DLS in the progressive group was (0.721 ± 0.371), which was higher than that in the nonprogressive group (0.113 ± 0.350) (p

Abstract Background To compare the performance between one-slice two-dimensional (2D) and whole-volume three-dimensional (3D) computed tomography (CT)-based radiomics models in the prediction of lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC). Methods Two hundred twenty-four patients with ESCC (158 LVI-absent and 66 LVI-present) were enrolled in this retrospective study. The enrolled patients were randomly split into the training and testing sets with a 7:3 ratio. The 2D and 3D radiomics features were derived from the primary tumors’ 2D and 3D regions of interest (ROIs) using 1.0 mm thickness contrast-enhanced CT (CECT) images. The 2D and 3D radiomics features were screened using inter-/intra-class correlation coefficient (ICC) analysis, Wilcoxon rank-sum test, Spearman correlation test, and the least absolute shrinkage and selection operator, and the radiomics models were built by multivariate logistic stepwise regression. The performance of 2D and 3D radiomics models was assessed by the area under the receiver operating characteristic (ROC) curve. The actual clinical utility of the 2D and 3D radiomics models was evaluated by decision curve analysis (DCA). Results There were 753 radiomics features from 2D ROIs and 1130 radiomics features from 3D ROIs, and finally, 7 features were retained to construct 2D and 3D radiomics models, respectively. ROC analysis revealed that in both the training and testing sets, the 3D radiomics model exhibited higher AUC values than the 2D radiomics model (0.930 versus 0.852 and 0.897 versus 0.851, respectively). The 3D radiomics model showed higher accuracy than the 2D radiomics model in the training and testing sets (0.899 versus 0.728 and 0.788 versus 0.758, respectively). In addition, the 3D radiomics model has higher specificity and positive predictive value, while the 2D radiomics model has higher sensitivity and negative predictive value. The DCA indicated that the 3D radiomics model provided higher actual clinical utility regarding overall net benefit than the 2D radiomics model. Conclusions Both 2D and 3D radiomics features can be employed as potential biomarkers to predict the LVI in ESCC. The performance of the 3D radiomics model is better than that of the 2D radiomics model for the prediction of the LVI in ESCC.

Abstract Objective To analyze the characteristics of high-frame-rate contrast-enhanced ultrasound (H-CEUS) in solid renal tumors using qualitative and quantitative methods. Methods Seventy-five patients who underwent preoperative conventional ultrasound (US), conventional contrast-enhanced ultrasound (C-CEUS), and H-CEUS examination of renal tumors were retrospectively analyzed, with a total of 89 renal masses. The masses were divided into the benign (30 masses) and malignant groups (59 masses) based on the results of enhanced computer tomography and pathology. The location, diameter, shape, border, calcification, and color doppler blood flow imaging (CDFI) of the lesions were observed by US, and the characteristics of the C-CEUS and H-CEUS images were qualitatively and quantitatively analyzed. The χ² test or Fisher’s exact probability method was used to compare the US image characteristics between the benign and malignant groups, and the image characteristics of C-CEUS and H-CEUS between the benign and malignant groups. Moreover, the nonparametric Mann-Whitney test was used to compare the differences in C-CEUS and H-CEUS time-intensity curve (TIC) parameters. Results Significant differences in gender, surgical approach, echogenicity, and CDFI were observed between the malignant and benign groups (p = 0.003,

Abstract Purpose The aim was to study the potential for an online fully automated daily adaptive radiotherapy (RT) workflow for bladder cancer, employing a focal boost and fiducial markers. The study focused on comparing the geometric and dosimetric aspects between the simulated automated online adaptive RT (oART) workflow and the clinically performed workflow. Methods Seventeen patients with muscle-invasive bladder cancer were treated with daily Cone Beam CT (CBCT)-guided oART. The bladder and pelvic lymph nodes (CTVelective) received a total dose of 40 Gy in 20 fractions and the tumor bed received an additional simultaneously integrated boost (SIB) of 15 Gy (CTVboost). During the online sessions a CBCT was acquired and used as input for the AI-network to automatically delineate the bladder and rectum, i.e. influencers. These influencers were employed to guide the algorithm utilized in the delineation process of the target. Manual adjustments to the generated contours are common during this clinical workflow prior to plan reoptimization and RT delivery. To study the potential for an online fully automated workflow, the oART workflow was repeated in a simulation environment without manual adjustments. A comparison was made between the clinical and automatic contours and between the treatment plans optimized on these clinical (Dclin) and automatic contours (Dauto). Results The bladder and rectum delineated by the AI-network differed from the clinical contours with a median Dice Similarity Coefficient of 0.99 and 0.92, a Mean Distance to Agreement of 1.9 mm and 1.3 mm and a relative volume of 100% and 95%, respectively. For the CTVboost these differences were larger, namely 0.71, 7 mm and 78%. For the CTVboost the median target coverage was 0.42% lower for Dauto compared to Dclin. For CTVelective this difference was 0.03%. The target coverage of Dauto met the clinical requirement of the CTV-coverage in 65% of the sessions for CTVboost and 95% of the sessions for the CTVelective. Conclusions While an online fully automated daily adaptive RT workflow shows promise for bladder treatment, its complexity becomes apparent when incorporating a focal boost, necessitating manual checks to prevent potential underdosage of the target.

Abstract Background 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. Methods 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 ≤ 2 mm and ≤ 3 mm respectively and (iii) statistical modelling of study data will predict tracking success in 85% of trial participants. Discussion Developing a real-time tracking method will enable increased targeting accuracy, without the need for additional invasive procedures to implant fiducial markers. Trial registration Registered to ClinicalTrials.gov (NCT05169177) 12th October 2021.

Abstract Background Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced, inoperable non-small cell lung cancer (NSCLC). Previous studies have mainly focused on examining local failure and recurrence patterns after surgery and the principles of lymph node metastasis (LNM) in surgical candidates with NSCLC. However, these studies were just only able to guide postoperative radiotherapy (PORT) and the patterns of LNM in patients with resected NSCLC was inadequate to represent that in locally advanced inoperable NSCLC patients for guiding target volume delineation of CCRT. In this study, we aimed to analyze the metastasis regularities and establish the correlations between different lymph node levels in NSCLC patients without any intervention using positron emission tomography/computed tomography (PET/CT) images. Methods Overall, 358 patients with N1–N3 NSCLC admitted in our hospital between 2018 and 2022 were retrospectively analyzed. The diagnosis of metastatic lymph nodes was reviewed and determined using the European Organization for Research and Treatment of Cancer standard and the standardized value of the PET/CT examination. Univariate and multivariate analysis were performed to investigate the correlations between the different levels were evaluated by using of the chi-square test and logistic regression model. Results The lymph nodes with the highest metastasis rates in patients with left lung cancer were in order as follows: 10L, 4L, 5, 4R, and 7; while in those with right lung cancer they were 10R, 4R, 7, 2R, and 1R. Notably, we found left lung patients were more likely to have contralateral hilar, mediastinal and supraclavicular lymph nodes involved, and the right lung group exhibited a higher propensity for ipsilateral mediastinum and supraclavicular lymph node invasion. Furthermore, correlation analysis revealed there were significant correlative patterns in the LNM across different levels. Conclusions This study elucidated the patterns of primary LNM in patients with NSCLC who had not undergone surgery (without any treatment interventions) and the correlations between lymph node levels. These findings were expected to provide useful reference for target volume delineation in definitive concurrent chemoradiotherapy in locally advanced NSCLC patients.

Abstract Background Volumetric modulated arc therapy (VMAT) planning optimization involves iterative adjustment of numerous parameters, and hence requires repeatedly dose recalculation. In this study, we used the deep learning method to develop a fast and accurate dose calculation method for VMAT. Methods The classical 3D UNet was adopted and trained to learn the physics principle of dose calculation. The inputs included the projected fluence map (FM), computed tomography (CT) images, the radiological depth and the source-to-voxel distance (SVD). The projected FM was generated by projecting the accumulated FM between two consecutive control points (CPs) onto the patient’s anatomy. The accumulated FM was calculated by simulating the movement of the multi-leaf collimator (MLC) from one CP to the next. The dose, calculated by the treatment planning system (TPS), was used as ground truth. 51 head and neck VMAT plans were used, with 43, 1 and 7 cases as training, validation, and testing datasets, respectively. Correspondingly, 7182, 180 and 1260 CP samples were included in the training, validation, and testing datasets. Results This presented method was evaluated by comparing the derived dose distribution to the TPS calculated dose distribution. The dose profiles coincided for both the single CP and the entire plan (summation of all CPs). But the network derived dose was smoother than the TPS calculated dose. Gamma analysis was performed between the network derived dose and the TPS calculated dose. The average gamma pass rate was 96.56%, 98.75%, 98.03% and 99.30% under the criteria of 2% (tolerance) -2 mm (distance to agreement, DTA). 2%-3 mm, 3%-2 mm and 3%-3 mm. No significant difference was observed on the critical indices including the max, mean dose, and the relative volume covered by the 2000 cGy, 4000 cGy and the prescription dose. For one CP, the average computational time of the network and TPS was 0.09s and 0.53s. And for one patient, the average time was 16.51s and 95.60s. Conclusion The dose distribution derived by the network showed good agreement with the TPS calculated dose distribution. The computational time was reduced to approximate one-sixth of its original duration. Therefore the presented deep learning-based dose calculation method has the potential to be used for planning optimization.

Abstract Background and objectives The purpose of this study was to investigate the survival benefit of Stereotactic Body Radiotherapy (SBRT) versus lenvatinib as first-line therapy in the treatment of hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT). Materials and methods 147 HCC patients with PVTT were included in this retrospective study, 70 were treated with SBRT and 77 of were treated with lenvatinib. Propensity score matching (PSM) analysis was employed to balance the differences in baseline characteristics between the two groups. Overall survival (OS), progression-free survival (PFS) and objective response rate (ORR) were compared between the two groups. In addition, the safety of patients in both groups was also evaluated. Results After PSM, 38 patients were matched in each of the two groups. The median OS was 14.5 (95% CI: 10.1–18.9) and 11.1 (95% CI: 9.3–12.9) months in the SBRT and lenvatinib groups, respectively (P = 0.014). The median PFS was 6.8 (95% CI: 5.1–8.5) and 5.0 (95% CI: 3.0–7.0) months, respectively (P = 0.010). The 1-, 2-years OS rates in the two groups were 65.8% vs. 39.5% and 31.6% vs. 10.5%, respectively. The 6-, 12-months PFS rates in the two groups were 57.9% vs. 44.7% and 28.9% vs. 10.5%, respectively. In addition, the SBRT group had a better ORR than the lenvatinib group (52.6% vs. 23.7%, P = 0.009). Patients with good response to SBRT had better survival. Cox proportional hazard model showed that SBRT was an important prognostic factor for OS and PFS. The incidence of hypertension (34.2% vs. 0%) was higher in the LEN group, however, both treatment modalities were well tolerated in the two groups of patients. Conclusion In HCC patients with PVTT, SBRT had a better survival benefit than Lenvatinib treatment as first-line therapy.

Abstract Purpose/Objective(s) Merkel cell carcinoma (MCC) radiation treatment has historically consisted of standard 1.8–2 Gy fractions treated daily over 4–6 weeks. Hypofractionated treatment regimens have demonstrated tumor control and toxicity equivalence to standard fractionation regimens for common cutaneous malignancies such as basal cell and squamous cell carcinomas. Herein we report the outcomes of hypofractionated versus standard fractionation radiotherapy for MCC at our institution. Materials/Methods The study involved a retrospective review of MCC patients treated with radiotherapy. Treatment characteristics and patient outcomes, including acute toxicities, disease recurrence and survival data were collected. The cumulative incidence of local and distant failures was estimated, with death as a competing risk. Results A total of 29 treatment courses for 24 patients were included, of which 13 involved standard fractionation with curative intent, 10 involved hypofractionated radiotherapy with curative intent, and 6 involved single fraction (8 Gy) palliative radiation. Half the patients were treated to a head/neck site. A subset of patients treated adjuvantly with curative intent included 8 standard fractionation and 8 hypofractionated radiotherapy patients. No statistically significant differences in local and/or distant failure or overall survival was observed between the patient groups. Conclusion Hypofractionated radiotherapy for MCC was associated with similar treatment outcomes relative to standard fractionation. In our limited patient sample, hypofractionated radiation treatment achieved similar results with similar toxicity and fewer treatments. Further analysis of a larger patient population with longer follow up is needed to confirm treatment tolerability and efficacy.

Abstract 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 Background Positron emission tomography/computed tomography (PET/CT) using prostate-specific membrane antigen (PSMA)-targeted radiotracers labeled with zirconium-89 (89Zr; half-life ~ 78.41 h) showed promise in localizing biochemical recurrence of prostate cancer (BCR) in pilot studies. Methods Retrospective analysis of 38 consecutive men with BCR (median [minimum–maximum] prostate-specific antigen 0.52 (0.12–2.50 ng/mL) undergoing [89Zr]Zr-PSMA-617 PET/CT post-negative [68Ga]Ga-PSMA-11 PET/CT. PET/CT acquisition 1-h, 24-h, and 48-h post-injection of a median (minimum–maximum) [89Zr]Zr-PSMA-617 tracer activity of 123 (84–166) MBq. Results [89Zr]Zr-PSMA-617 PET/CT detected altogether 57 lesions: 18 local recurrences, 33 lymph node metastases, 6 bone metastases in 30/38 men with BCR (78%) and prior negative conventional PSMA PET/CT. Lesion uptake significantly increased from 1-h to 24-h and, in a majority of cases, from 24-h to 48-h. Tumor-to-background ratios significantly increased over time, with absolute increases of 100 or more. No side effects were noted. After [89Zr]Zr-PSMA-617 PET/CT-based treatment, prostate-specific antigen concentration decreased in all patients, becoming undetectable in a third of patients. Limitations: retrospective, single center design; infrequent histopathological and imaging verification. Conclusion This large series provides further evidence that [89Zr]Zr-PSMA-617 PET/CT is a beneficial imaging modality to localize early BCR. A remarkable increase in tumor-to-background ratio over time allows localization of tumor unidentified on conventional PSMA PET/CT.

Abstract Gliomas and Glioblastomas represent a significant portion of central nervous system (CNS) tumors associated with high mortality rates and variable prognosis. In 2021, the World Health Organization (WHO) updated its Glioma classification criteria, most notably incorporating molecular markers including CDKN2A/B homozygous deletion, TERT promoter mutation, EGFR amplification, + 7/−10 chromosome copy number changes, and others into the grading and classification of adult and pediatric Gliomas. The inclusion of these markers and the corresponding introduction of new Glioma subtypes has allowed for more specific tailoring of clinical interventions and has inspired a new wave of Radiogenomic studies seeking to leverage medical imaging information to explore the diagnostic and prognostic implications of these new biomarkers. Radiomics, deep learning, and combined approaches have enabled the development of powerful computational tools for MRI analysis correlating imaging characteristics with various molecular biomarkers integrated into the updated WHO CNS-5 guidelines. Recent studies have leveraged these methods to accurately classify Gliomas in accordance with these updated molecular-based criteria based solely on non-invasive MRI, demonstrating the great promise of Radiogenomic tools. In this review, we explore the relative benefits and drawbacks of these computational frameworks and highlight the technical and clinical innovations presented by recent studies in the landscape of fast evolving molecular-based Glioma subtyping. Furthermore, the potential benefits and challenges of incorporating these tools into routine radiological workflows, aiming to enhance patient care and optimize clinical outcomes in the evolving field of CNS tumor management, have been highlighted.

Abstract Background Accurately classifying primary bone tumors is crucial for guiding therapeutic decisions. The National Comprehensive Cancer Network guidelines recommend multimodal images to provide different perspectives for the comprehensive evaluation of primary bone tumors. However, in clinical practice, most patients’ medical multimodal images are often incomplete. This study aimed to build a deep learning model using patients’ incomplete multimodal images from X-ray, CT, and MRI alongside clinical characteristics to classify primary bone tumors as benign, intermediate, or malignant. Methods In this retrospective study, a total of 1305 patients with histopathologically confirmed primary bone tumors (internal dataset, n = 1043; external dataset, n = 262) were included from two centers between January 2010 and December 2022. We proposed a Primary Bone Tumor Classification Transformer Network (PBTC-TransNet) fusion model to classify primary bone tumors. Areas under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the model’s classification performance. Results The PBTC-TransNet fusion model achieved satisfactory micro-average AUCs of 0.847 (95% CI: 0.832, 0.862) and 0.782 (95% CI: 0.749, 0.817) on the internal and external test sets. For the classification of benign, intermediate, and malignant primary bone tumors, the model respectively achieved AUCs of 0.827/0.727, 0.740/0.662, and 0.815/0.745 on the internal/external test sets. Furthermore, across all patient subgroups stratified by the distribution of imaging modalities, the PBTC-TransNet fusion model gained micro-average AUCs ranging from 0.700 to 0.909 and 0.640 to 0.847 on the internal and external test sets, respectively. The model showed the highest micro-average AUC of 0.909, accuracy of 84.3%, micro-average sensitivity of 84.3%, and micro-average specificity of 92.1% in those with only X-rays on the internal test set. On the external test set, the PBTC-TransNet fusion model gained the highest micro-average AUC of 0.847 for patients with X-ray + CT. Conclusions We successfully developed and externally validated the transformer-based PBTC-Transnet fusion model for the effective classification of primary bone tumors. This model, rooted in incomplete multimodal images and clinical characteristics, effectively mirrors real-life clinical scenarios, thus enhancing its strong clinical practicability.

Abstract Background To assess the capability of multimodal apparent diffusion (MAD) weighted magnetic resonance imaging (MRI) to distinguish between malignant and benign breast lesions, and to predict Ki-67 expression level in breast cancer. Methods This retrospective study was conducted with 93 patients who had postoperative pathology-confirmed breast cancer or benign breast lesions. MAD images were acquired using a 3.0 T MRI scanner with 16 b values. The MAD parameters, as flow (fF, DF), unimpeded (fluid) (fUI), hindered (fH, DH, and αH), and restricted (fR, DR), were calculated. The differences of the parameters were compared by Mann–Whitney U test between the benign/malignant lesions and high/low Ki-67 expression level. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). Results The fR in the malignant lesions was significantly higher than in the benign lesions (P = 0.001), whereas the fUI and DH were found to be significantly lower (P = 0.007 and P

Abstract Background Recurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI). Materials and methods 48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence. Results The parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De⊥), extra-axonal parallel diffusivity (De∥) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De⊥) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96. Conclusion Preoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De⊥ of SMI might be a valuable marker.

Abstract Background Since it has been found that the maximum metabolic activity of a cancer lesion shifts toward the lesion edge during cancer progression, normalized distances from the hot spot of radiotracer uptake to tumor centroid (NHOC) and tumor perimeter (NHOP) have been suggested as novel F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) parameters that can reflect cancer aggressiveness. This study aimed to investigate whether NHOC and NHOP parameters could predict pathological response to neoadjuvant chemotherapy (NAC) and progression-free survival (PFS) in breast cancer patients. Methods This study retrospectively enrolled 135 female patients with breast cancer who underwent pretreatment FDG PET/CT and received NAC and subsequent surgical resection. From PET/CT images, normalized distances of maximum SUV and peak SUV-to-tumor centroid (NHOCmax and NHOCpeak) and -to-tumor perimeter (NHOPmax and NHOPpeak) were measured, in addition to conventional PET/CT parameters. Results Of 135 patients, 32 (23.7%) achieved pathological complete response (pCR), and 34 (25.2%) had events during follow-up. In the receiver operating characteristic (ROC) curve analysis, NHOCmax showed the highest area under the ROC curve value (0.710) for predicting pCR, followed by NHOCpeak (0.694). In the multivariate logistic regression analysis, NHOCmax, NHOCpeak, and NHOPmax were independent predictors for pCR (p

Abstract Introduction Anaplastic meningiomas, categorized as WHO grade 3 tumors, are rare and highly aggressive, accounting for 1-2% of all meningioma cases. Despite aggressive treatment, including surgery and Radiation, they exhibit a high recurrence rate and poor survival outcomes. The aggressive histopathological features emphasize the urgent need for effective management strategies. Methods A retrospective multi-institutional analysis was conducted on patients with recurrent anaplastic meningioma who underwent re-irradiation between 2017 and 2023. Clinical, dosimetric, and outcome data were collected and analyzed, focusing on local control, progression free survival and treatment-related adverse events. Results Thirty-four cases were analyzed, with a median follow-up 11 months after re-irradiation. Progression-free survival at 12 months was 61.9%, with higher doses correlating with better outcomes. Concomitant Bevacizumab improves progression-free survival and reduces the risk of radiation necrosis. CDKN2A homozygote deletion correlated with a higher risk of local failure. Symptomatic radiation necrosis occurred in 20.5% of cases, but its incidence was lower with concomitant Bevacizumab treatment. Conclusion Re-irradiation presents a viable option for recurrent anaplastic meningioma despite the associated risk of radiation necrosis. Higher doses with concomitant Bevacizumab improve clinical outcomes and reduce toxicity. Individualized treatment approaches are necessary, emphasizing the importance of further research to refine management strategies for this challenging disease.

Abstract Objective This report details the experience of a patient who developed a second primary glioblastoma (GB), offering insights into the treatment process and reviewing relevant literature. Case presentation A male patient, who was diagnosed with medulloblastoma at age 9, received treatment with cobalt-60 craniospinal irradiation (CSI) (36 Gy/20 fractions) and a tumor bed boost (total of 56 Gy). After 32 years, at age 41, an MRI revealed a space-occupying mass in the left cerebellar hemisphere. Surgical resection was performed, and postoperative pathology confirmed a diagnosis of radiation-induced glioblastoma (RIGB). Given the history of irradiation and the current tolerability of brainstem doses, proton beam therapy (PBT) combined with Temozolomide (75 mg/m2) was chosen. The treatment plan included 60 Gy on the gross tumor bed and 54 Gy on the clinical target volume, delivered in 30 fractions. The patient underwent regular follow-up and achieved a complete response. Clinical discussion For childhood cancer survivors, the development of a second primary tumor significantly impacts prognosis. RIGB is a rare form of secondary tumor with distinct molecular characteristics compared to primary GB and recurrent secondary GB. Molecular markers such as IDH and MGMT status can help differentiate between primary GB, recurrent secondary GB, and radiation-induced secondary GB in patients with a history of prior radiation therapy. Surgical resection remains a primary treatment option, while PBT is preferred for postoperative treatment due to its superior protection of normal tissues and the ability to deliver high-dose irradiation. Conclusion RIGB is a rare second primary tumor that requires strategic molecular profiling and individualized management. Proton beam therapy provides effective high-dose irradiation in the postoperative phase and is the preferred treatment option for such cases.

Abstract Purpose This study aimed to use propensity score matching (PSM) to explore the long-term outcomes and failure patterns in locally advanced rectal cancer (LARC) patients with positive versus negative lateral pelvic lymph node (LPLN). Materials and methods Patients with LARC were retrospectively divided into LPLN-positive and LPLN-negative groups. Clinical characteristics were compared between the groups using the chi-square test. PSM was applied to balance these differences. Progression-free survival (PFS) and overall survival (OS), and local–regional recurrence (LRR) and distant metastasis (DM) rates were compared between the groups using the Kaplan–Meier method and log-rank tests. Results A total of 651 LARC patients were included, 160 (24.6%) of whom had positive LPLN and 491 (75.4%) had negative LPLN. Before PSM, the LPLN-positive group had higher rates of lower location (53.1% vs. 43.0%, P = 0.025), T4 stage (37.5% vs. 23.2%, P = 0.002), mesorectal fascia (MRF)-positive (53.9% vs. 35.4%, P

Abstract Background We conducted a systematic review and meta-analysis to assess the risk of respiratory adverse effects in patients with solid tumors treated with immune checkpoint inhibitors (PD-1, PD-L1 and CTLA-4 inhibitors) in combination with radiation therapy. Methods We selected eligible studies through the following databases: PubMed, Embase, Cochrane Library, and Clinicaltrials ( https://clinicaltrials.gov/ ). The data was analyzed by using Rstudio. Results Among 3737 studies, 26 clinical trials, including 2670 patients, were qualified for the meta-analysis. We evaluated the incidence rates of adverse respiratory events, including cough, pneumonia, upper respiratory tract infections, and others: grades 1–5 cough, 0.176 (95%CI: 0.113–0.274, I2 = 92.36%); grades 1–5 pneumonitis, 0.118 (95%CI: 0.067–0.198, I2 = 88.64%); grades 1–5 upper respiratory tract infection, 0.064 (95%CI: 0.049–0.080, I2 = 0.98%); grades 3–5 cough, 0.050 (95%CI: 0.012–0.204, I2 = 8.90%); grades 3–5 pneumonitis, 0.052 (95%CI: 0.031–0.078, I2 = 83.86%); grades 3–5 upper respiratory tract infection, 0.040 (95%CI: 0.007–0.249, I2 = 45.31%). Conclusions Our meta-analysis demonstrated that ICI combined with radiotherapy for solid tumors can produce respiratory adverse effects. ICIs combination treatment, a tumor located in the chest, is more likely to cause adverse reactions, and SBRT treatment and synchronous treatment will bring less incidence of adverse reactions. This study provide insights for clinicians to balance the risks of radiotherapy in the course of treating oncology patients.

Abstract Background The 3-variable number-of-risk-factors (NRF) model is a prognostic tool for patients undergoing palliative radiotherapy (PRT). However, there is little research on the NRF model for patients with painful non-bone-metastasis tumours treated with PRT, and the efficacy of the NRF model in predicting survival is unclear to date. Therefore, we aimed to assess the prognostic accuracy of a 3-variable NRF model in patients undergoing PRT for bone and non- bone-metastasis tumours. Methods This was a secondary analysis of studies on PRT for bone-metastasis (BM) and PRT for miscellaneous painful tumours (MPTs), including non-BM tumours. Patients were grouped in the NRF model and survival was compared between groups. Discrimination was evaluated using a time-independent C-index and a time-dependent area under the receiver operating characteristic curve (AUROC). A calibration curve was used to assess the agreement between predicted and observed survival. Results We analysed 485 patients in the BM group and 302 patients in the MPT group. The median survival times in the BM group for groups I, II, and III were 35.1, 10.1, and 3.3 months, respectively (P

Abstract Purpose Lympho-vascular invasion (LVI) and perineural invasion (PNI) have been established as prognostic factors in various types of cancers. The preoperative prediction of LVI and PNI has the potential to guide personalized medicine strategies for patients with esophageal squamous cell cancer (ESCC). This study investigates whether radiomics features derived from preoperative contrast-enhanced CT could predict LVI and PNI in ESCC patients. Methods and materials A retrospective cohort of 544 ESCC patients who underwent esophagectomy were included in this study. Preoperative contrast-enhanced CT images, pathological results of PNI and LVI, and clinical characteristics were collected. For each patient, the gross tumor volume (GTV-T) and lymph nodes volume (GTV-N) were delineated and four categories of radiomics features (first-order, shape, textural and wavelet) were extracted from GTV-T and GTV-N. The Mann–Whitney U test was used to select significant features associated with LVI and PNI in turn. Subsequently, radiomics signatures for LVI and PNI were constructed using LASSO regression with ten-fold cross-validation. Significant clinical characteristics were combined with radiomics signature to develop two nomogram models for predicting LVI and PNI, respectively. The area under the curve (AUC) and calibration curve were used to evaluate the predictive performance of the models. Results The radiomics signature for LVI prediction consisted of 28 features, while the PNI radiomics signature comprised 14 features. The AUCs of the LVI radiomics signature were 0.77 and 0.74 in the training and validation groups, respectively, while the AUCs of the PNI radiomics signature were 0.69 and 0.68 in the training and validation groups. The nomograms incorporating radiomics signatures and significant clinical characteristics such as age, gender, thrombin time and D-Dimer showed improved predictive performance for both LVI (AUC: 0.82 and 0.80 in the training and validation group) and PNI (AUC: 0.75 and 0.72 in the training and validation groups) compared to the radiomics signature alone. Conclusion The radiomics features extracted from preoperative contrast-enhanced CT of gross tumor and lymph nodes have demonstrated their potential in predicting LVI and PNI in ESCC patients. Furthermore, the incorporation of clinical characteristics has shown additional value, resulting in improved predictive performance.

Abstract Background With the increasing incidence of renal lesions, pretreatment differentiation between benign and malignant lesions is crucial for optimized management. This study aimed to develop a machine learning model utilizing radiomic features extracted from various regions of interest (ROIs), intratumoral ecological diversity features, and clinical factors to classify renal lesions. Methods CT images (arterial phase) of 1,795 renal lesions with confirmed pathology from three hospital sites were split into development (1184, 66%) and test (611, 34%) cohorts by surgery date. Conventional radiomic features were extracted from eight ROIs of arterial phase images. Intratumoral ecological diversity features were derived from intratumoral subregions. The combined model incorporating these features with clinical factors was developed, and its performance was compared with radiologists’ interpretation. Results Combining intratumoral and peritumoral radiomic features, along with ecological diversity features yielded the highest AUC of 0.929 among all combinations of features extracted from CT scans. After incorporating clinical factors into the features extracted from CT images, our combined model outperformed the interpretation of radiologists in the whole (AUC = 0.946 vs 0.823, P

Abstract Background Total body irradiation (TBI)-based allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative treatment for selected patients with acute myeloid leukemia (AML). Yet, secondary malignancies contribute to long-term morbidity and mortality with TBI potentially influencing these risks. Methods This retrospective study analyzed the cumulative incidences of secondary solid malignancies and precancerous lesions of 89 consecutive AML patients after TBI-based conditioning before 1st allo-HSCT between 2000 and 2016. TBI was performed with an average dose rate of 4 cGy/min and a twice-daily fractionation. Cause-specific hazard models analyzed risk factors for secondary malignancies/precancerous lesions and the competing risks of dying before developing secondary malignancies/precancerous lesions. Results The median patient age at TBI was 42.5 years (interquartile range, 32.5–51.2), while the median follow-up was 15.2 years (interquartile range, 13.0-18.2). Most patients received a myeloablative conditioning (MAC) containing 8 Gy (n = 47) and 12 Gy TBI (n = 11). Reduced-intensity regimens (RIC, 4 Gy TBI) were applied in 31 patients. Of note, patients receiving RIC were older than patients receiving MAC. The most common cancer types were non-squamous cell carcinomas (n = 14) after exclusion of a patient diagnosed with sarcoma within less than a year after TBI. The cumulative incidences of secondary malignancies and precancerous lesions were 8% (95%CI, 4–16), 14% (95%CI, 7–23), and 17% (95%CI, 9–27) at 10, 15 and 20 years, while the cumulative incidences of premature deaths were 59% (95%CI, 48–69), 59% (95%CI, 48–69), and 64% (95%CI, 49–76). In multivariate analyses, higher patient age at TBI was associated with lower rates of secondary malignancies/precancerous lesions, while higher patient age translated into a trend towards premature deaths (before patients could develop malignancies). Higher TBI doses, mainly applied in younger patients, translated into lower rates of secondary malignancies/precancerous lesions while lacking associations with mortality. Chronic GVHD requiring systemic immunosuppression was associated with premature deaths. Conclusions Although this study indicates an inverse relationship between TBI doses applied and treatment-related malignancies, confounding by competing risks is present. The age dependency may be explained by the fact that older patients had a lower life expectancy independent of malignancies, illustrating the pitfalls of competing risks. Trial registration The study was retrospectively registered.

Abstract Background Accelerated partial breast irradiation (APBI) is an accepted treatment option for early breast cancer. Treatment delivered on the Magnetic Resonance integrated Linear Accelerator (MRL) provides the added assurance of improved soft tissue visibility, important in the delivery of APBI. This technique can be delivered in both the supine and prone positions, however current literature suggests that prone treatment on the MRL is infeasible due to physical limitations with bore size. This study aims to investigate the feasibility of positioning patients on a custom designed prone breast board compared with supine positioning on a personalised vacuum bag. Geometric distortion, the relative position of Organs at Risk (OAR) to the tumour bed and breathing motion (intrafraction motion) will be compared between the supine and prone positions. The study will also investigate the positional impact on dosimetry, patient experience, and position preference. Methods Up to 30 patients will be recruited over a 12-month period for participation in this Human Research Ethics Committee approved exploratory cohort study. Patients will be scanned on the magnetic resonance imaging (MRI) Simulator in both the supine and prone positions as per current standard of care for APBI simulation. Supine and prone positioning comparisons will all be assessed on de-identified MRI image pairs, acquired using appropriate software. Patient experience will be explored through completion of a short, anonymous electronic survey. Descriptive statistics will be used for reporting of results with categorical, parametric/non-parametric tests applied (data format dependent). Survey results will be interpreted by comparison of percentage frequencies across the Likert scales. Thematic content analysis will be used to interpret qualitative data from the open-ended survey questions. Discussion The results of this study will be used to assess the feasibility of treating patients with APBI in the prone position on a custom designed board on the MRL. It may also be used to assist with identification of patients who would benefit from this position over supine without the need to perform both scans. Patient experience and technical considerations will be utilised to develop a tool to assist in this process. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN1262400067583. Registered 28th of May 2024. https://www.anzctr.org.au/ACTRN12624000679583.aspx

Abstract Introduction Biology-guided radiotherapy (BgRT) is a novel radiation delivery approach utilizing fluorodeoxyglucose (FDG) activity on positron emission tomography (PET) imaging performed in real-time to track and direct RT. Our institution recently acquired the RefleXion X1 BgRT system and sought to assess the feasibility of targeting metastatic sites in various organs, including the liver. However, in order for BgRT to function appropriate, adequate contrast in FDG activity between the tumor and the background tissue, referred to as the normalized SUV (NSUV), is necessary for optimal functioning of BgRT. Methods We reviewed the charts of 50 lung adenocarcinoma patients with liver metastases. The following variables were collected: SUVmax and SUVmean for each liver metastasis, SUVmean and SUVmax at 5 and 10 mm radially from the lesion, and NSUV at 5 mm and 10 mm (SUVmax of the liver metastasis divided by SUV mean at 5 mm at 10 mm respectively). Results 82 measurable liver metastases were included in the final analysis. The average SUVbackground of liver was 2.26 (95% confidence interval [CI] 2.17–2.35); average SUVmean for liver metastases was 5.31 (95% CI 4.87–5.75), and average SUVmax of liver metastases was 9.19 (95% CI 7.59–10.78). The average SUVmean at 5 mm and 10 mm radially from each lesion were 3.08 (95% CI 3.00-2.16) and 2.60 (95% CI 2.52–2.68), respectively. The mean NSUV at 5 mm and 10 mm were 3.13 (95% CI 2.53–3.73) and 3.69 (95% CI 3.00-4.41) respectively. Furthermore, 90% of lesions had NSUV greater than 1.45 at 5 mm and greater than 1.77 at 10 mm. Conclusions This is the first study to comprehensively characterize FDG contrast between the liver tumor and background, referred to as NSUV. Due to the high background SUV normally found in the liver, this work will be valuable for guiding optimization of BgRT for treating liver metastases in the future using the RefleXion® X1 and potentially other similar BgRT platforms.

Abstract Background To investigate the prognosis of longitudinal health-related quality of life (HRQOL) during concurrent chemoradiotherapy (CCRT) on survival outcomes in patients with advanced nasopharyngeal carcinoma (NPC). Methods During 2012–2014, 145 adult NPC patients with stage II-IVb NPC were investigated weekly using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORCT QLQ-C30) during their CCRT period. The effects of longitudinal trends of HRQOL on survival outcomes were estimated using joint modeling, and hazard ratios (HRs) with 95% confidence intervals (95% CIs) were reported as a 10-point increase in HRQOL scores. Results After a median follow-up of 83.4 months, the multivariable models showed significant associations of longitudinal increasing scores in fatigue and appetite loss during the CCRT period with distant metastasis-free survival: 10-point increases in scores of fatigue and appetite loss domains during CCRT period were significantly associated with 75% (HR: 1.75, 95% CI: 1.01, 3.02; p = 0.047) and 59% (HR: 1.59, 95% CI: 1.09, 2.59; p = 0.018) increase in the risk of distant metastasis, respectively. The prognostic effects of the longitudinal HRQOL trend on overall survival and progress-free survival were statistically non-significant. Conclusion Increases in fatigue and appetite loss of HRQOL during the CCRT period are significantly associated with high risks of distant metastasis in advanced NPC patients. Nutritional support and psychological intervention are warranted for NPC patients during the treatment period.

Abstract Background Direct comparisons between [18F]FDG PET/CT findings and clinical occurrence of immune-related adverse events (irAEs) based on independent assessments of clinical and imaging features in patients receiving immune checkpoint inhibitors (ICIs) are missing. Our aim was to estimate sites, frequency, and timing of immune-related PET findings during ICIs treatment in patients with melanoma and NSCLC, and to assess their correlation with clinical irAEs. Prognostic implications of immune-related events were also investigated. Methods Fifty-one patients with melanoma (47%) or NSCLC (53%) undergoing multiple PET examinations during anti-PD1/PDL1 treatment were retrospectively included. Clinical irAEs were graded according to CTCAE v.5.0. Abnormal PET findings suggestive of immune activation were described by two readers blinded to the clinical data. Progression-free survival (PFS) and overall survival (OS) were analyzed with the Kaplan-Meier method in patients stratified according to the presence of irAEs, immune-related PET findings or both. Results Twenty-one patients showed clinical irAEs only (n = 6), immune-related PET findings only (n = 6), or both (n = 9). In patients whose imaging findings corresponded to clinical irAEs (n = 7), a positive correlation between SUVmax and the severity of the clinical event was observed (rs=0.763, p = 0.046). Clinical irAEs occurred more frequently in patients without macroscopic disease than in metastatic patients (55% vs. 23%, p = 0.039). Patients who developed clinical irAEs had a significantly longer PFS than patients who remained clinically asymptomatic, both in the overall cohort (p = 0.011) and in the subgroup of (n = 35) patients with metastatic disease (p = 0.019). The occurrence of immune-related PET findings significantly stratified PFS in the overall cohort (p = 0.040), and slightly missed statistical significance in patients with metastatic disease (p = 0.08). The best stratification of PFS was achieved when all patients who developed immune-related events, either clinically relevant or detected by PET only, were grouped together both in the overall cohort (p = 0.002) and in patients with metastatic disease (p = 0.004). In the whole sample, OS was longer in patients who developed any immune-related events (p = 0.032). Conclusion Patients with melanoma or NSCLC under ICI treatment can develop clinical irAEs, immune-related PET findings, or both. The occurrence of immune-related events has a prognostic impact. Combining clinical information with PET assessment improved outcome stratification.

Abstract Background Prostate-specific membrane antigen positron emission tomography (PSMA-PET) is an essential tool for patient selection before radioligand therapy (RLT). Interim-staging with PSMA-PET during RLT allows for therapy monitoring. However, its added value over post-treatment imaging is poorly elucidated. The aim of this study was to compare early treatment response assessed by post-therapeutic whole-body scans (WBS) with interim-staging by PSMA-PET after 2 cycles in order to prognosticate OS. Methods Men with metastasized castration-resistant PC (mCRPC) who had received at least two cycles of RLT, and interim PSMA-PET were evaluated retrospectively. PROMISE V2 framework was used to categorize PSMA expression and assess response to treatment. Response was defined as either disease control rate (DCR) for responders or progression for non-responders. Results A total of 188 men with mCRPC who underwent RLT between February 2015 and December 2021 were included. The comparison of different imaging modalities revealed a strong and significant correlation with Cramer V test: e.g. response on WBS during second cycle compared to interim PET after two cycles of RLT (cφ = 0.888, P

Abstract Purpose We aimed to develop and externally validate a CT-based deep learning radiomics model for predicting overall survival (OS) in clear cell renal cell carcinoma (ccRCC) patients, and investigate the association of radiomics with tumor heterogeneity and microenvironment. Methods The clinicopathological data and contrast-enhanced CT images of 512 ccRCC patients from three institutions were collected. A total of 3566 deep learning radiomics features were extracted from 3D regions of interest. We generated the deep learning radiomics score (DLRS), and validated this score using an external cohort from TCIA. Patients were divided into high and low-score groups by the DLRS. Sequencing data from the corresponding TCGA cohort were used to reveal the differences of tumor heterogeneity and microenvironment between different radiomics score groups. What’s more, univariate and multivariate Cox regression were used to identify independent risk factors of poor OS after operation. A combined model was developed by incorporating the DLRS and clinicopathological features. The SHapley Additive exPlanation method was used for interpretation of predictive results. Results At multivariate Cox regression analysis, the DLRS was identified as an independent risk factor of poor OS. The genomic landscape of different radiomics score groups was investigated. The heterogeneity of tumor cell and tumor microenvironment significantly varied between both groups. In the test cohort, the combined model had a great predictive performance, with AUCs (95%CI) for 1, 3 and 5-year OS of 0.879(0.868–0.931), 0.854(0.819–0.899) and 0.831(0.813–0.868), respectively. There was a significant difference in survival time between different groups stratified by the combined model. This model showed great discrimination and calibration, outperforming the existing prognostic models (all p values

Abstract Multimodal imaging unfolds as an innovative approach that synergistically employs a spectrum of imaging techniques either simultaneously or sequentially. The integration of computed tomography (CT), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and optical imaging (OI) results in a comprehensive and complementary understanding of complex biological processes. This innovative approach combines the strengths of each method and overcoming their individual limitations. By harmoniously blending data from these modalities, it significantly improves the accuracy of cancer diagnosis and aids in treatment decision-making processes. Nanoparticles possess a high potential for facile functionalization with radioactive isotopes and a wide array of contrast agents. This strategic modification serves to augment signal amplification, significantly enhance image sensitivity, and elevate contrast indices. Such tailored nanoparticles constructs exhibit a promising avenue for advancing imaging modalities in both preclinical and clinical setting. Furthermore, nanoparticles function as a unified nanoplatform for the co-localization of imaging agents and therapeutic payloads, thereby optimizing the efficiency of cancer management strategies. Consequently, radiolabeled nanoparticles exhibit substantial potential in driving forward the realms of multimodal imaging and theranostic applications. This review discusses the potential applications of molecular imaging in cancer diagnosis, the utilization of nanotechnology-based radiolabeled materials in multimodal imaging and theranostic applications, as well as recent advancements in this field. It also highlights challenges including cytotoxicity and regulatory compliance, essential considerations for effective clinical translation of nanoradiopharmaceuticals in multimodal imaging and theranostic applications. Graphical Abstract

Abstract Background Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains challenging. This study aims to develop a predictive model for progression-free survival (PFS) in LC patients with IO based on clinical features and advanced imaging biomarkers. Materials and methods A retrospective analysis was conducted on a cohort of 206 LC patients receiving IO treatment. Pre-treatment computed tomography images were used to extract advanced imaging biomarkers, including intratumoral and peritumoral-vasculature radiomics. Clinical features, including age, gene status, hematology, and staging, were also collected. Key radiomic and clinical features for predicting IO outcomes were identified using a two-step feature selection process, including univariate Cox regression and chi-squared test, followed by sequential forward selection. The DeepSurv model was constructed to predict PFS based on clinical and radiomic features. Model performance was evaluated using the area under the time-dependent receiver operating characteristic curve (AUC) and concordance index (C-index). Results Combining radiomics of intratumoral heterogeneity and peritumoral-vasculature with clinical features demonstrated a significant enhancement (p

Abstract Background The stiffness of the tumor microenvironment (TME) directly influences cellular behaviors. Radiotherapy (RT) is a common treatment for solid tumors, but the TME can impact its efficacy. In the case of liver cancer, clinical observations have shown that tumors within a cirrhotic, stiffer background respond less to RT, suggesting that the extracellular matrix (ECM) stiffness plays a critical role in the development of radioresistance. Methods This study explored the effects of ECM stiffness and the inhibition of lysyl oxidase (LOX) isoenzymes on the radiation response of liver cancer in a millimeter-sized three-dimensional (3D) culture. We constructed a cube-shaped ECM-based millimeter-sized hydrogel containing Huh7 human liver cancer cells. By modulating the collagen concentration, we produced two groups of samples with different ECM stiffnesses to mimic the clinical scenarios of normal and cirrhotic livers. We used a single-transducer system for shear-wave-based elasticity measurement, to derive Young’s modulus of the 3D cell culture to investigate how the ECM stiffness affects radiosensitivity. This is the first demonstration of a workflow for assessing radiation-induced response in a millimeter-sized 3D culture. Results Increased ECM stiffness was associated with a decreased radiation response. Moreover, sonoporation-assisted LOX inhibition with BAPN (β-aminopropionitrile monofumarate) significantly decreased the initial ECM stiffness and increased RT-induced cell death. Inhibition of LOX was particularly effective in reducing ECM stiffness in stiffer matrices. Combining LOX inhibition with RT markedly increased radiation-induced DNA damage in cirrhotic liver cancer cells, enhancing their response to radiation. Furthermore, LOX inhibition can be combined with sonoporation to overcome stiffness-related radioresistance, potentially leading to better treatment outcomes for patients with liver cancer. Conclusions The findings underscore the significant influence of ECM stiffness on liver cancer’s response to radiation. Sonoporation-aided LOX inhibition emerges as a promising strategy to mitigate stiffness-related resistance, offering potential improvements in liver cancer treatment outcomes.

Abstract 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