Radiotherapy For Cervical Cancer Research Articles

Correlation of Post-Treatment Biopsy and Fluorodeoxyglucose PET/CT Findings Following Definitive Chemotherapy and Radiation for Cervical Cancer

Concurrent chemotherapy and external beam radiation with brachytherapy boost is considered standard of care for treatment of locally advanced cervical cancer. Post treatment surveillance fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) imaging is recommended 3-6 months after completion of therapy. Persistent FDG avidity is commonly observed at the cervix on surveillance scans, indeterminate for residual malignancy versus post treatment inflammatory change. To better understand the clinical significance of residual hypermetabolic activity, we performed an analysis of surveillance FDG-PET/CT images, correlating findings with post treatment cervical biopsy results after completion of therapy. The medical records of all patients treated with definitive chemotherapy and radiation for locally advanced (FIGO IB3 to IVA) cervical cancer at a single academic medical center between 2017 and 2022 were reviewed. Patients were treated with curative intent using a combination of pelvic external beam radiation with concurrent cisplatin chemotherapy followed by intracavitary or combined intracavitary/interstitial brachytherapy boost. Patients underwent FDG-PET/CT imaging at 3-6 months upon completion of therapy, followed by biopsy either for suspected residual disease or equivocal findings on physical exam or FDG-PET/CT scans. Biopsies were obtained within 100 days of FDG-PET/CT imaging (median, 14 days). Twenty-three patients met inclusion criteria. One patient was excluded from analysis due to lack of FDG avidity on her pre-treatment FDG-PET/CT. Among the 22 evaluable scans, median pre-treatment FDG- PET/CT SUVmax of the cervix was 16.3 (range, 4.9-55). Median post-treatment SUVmax was 4.4 (range, 2.1-7.4). Median change in SUVmax from pre-treatment to post-treatment was 11.8 (range, 1.1 to 50.6). Twenty patients had a post-treatment SUVmax of greater than 3. Among post treatment scans, eight showed no residual uptake; two showed uptakes equal to the liver; eleven showed uptakes moderately higher than liver; and one showed uptake markedly increased relative to liver. None of the biopsy specimens showed evidence of residual malignancy, instead showing fibroinflammatory necrosis and reactive changes. None of the patients developed clinical evidence of disease progression at the cervix within one year of treatment completion. Residual hypermetabolic activity at the cervix is common following definitive chemotherapy and radiation for cervical cancer. This is unlikely to represent residual viable malignancy. Post treatment FDG-PET/CT imaging remains valuable for detecting locoregional or distant disease progression/persistence following therapy.

The Role of Radiation Therapy for Metastatic Cervical Cancer

Survival rates for women with metastatic cervical cancer (CC) are low, with limited management options. Radiation therapy (RT) for metastatic disease has led to prolonged survival in other malignancies, however, the data are scarce in CC. Herein, we evaluated the effect of RT for metastatic CC. A total of 58 patients with metastatic CC between September 2019 and January 2023 were retrospectively analyzed. All the patients were treated with platinum-based chemotherapy combined with targeted therapy or immunotherapy followed with or without RT (NRT). The recent efficacy, survival status and prognostic factors were analyzed statistically. Objective response rate (ORR) was 63.6% with one complete and twenty partial responses in RT group (n = 33) and 40.0% with two complete and eight partial responses in NRT group (n = 25), respectively (p = 0.074). Disease control rate (DCR) of the RT and NRT groups were 79.4% vs 80.0%, respectively (p = 0.861). Median follow-up time was 17 months (3-39months). In RT group, 11(33.3%) patients experienced local regional or distant failure and 9 (27.3%) patients were dead. In NRT group, 15(60%) patients had progression and 8 (32%) patients dead. There was no significant difference between the two groups in overall survival (OS); however, RT group displayed superior progression-free survival (PFS) (1-year OS: 72.7% vs. 68.0%, p = 0.460; 1-year PFS: 66.7% vs. 40.0%, p = 0.039). The multivariate analysis showed that RT, immunotherapy, lymph node metastasis only relevant predictor of superior PFS but not OS. In subgroup analysis, patients treated with RT appeared to have a better PFS in some specific cohorts, such as age>45 years (72.0% vs 36.4% P = 0.015), squamous carcinoma histology (71.0% vs 40.9% P = 0.017), metastatic at diagnosis (75.0% vs 47.6% P = 0.012), non-targeted therapy (72.4% vs 43.8% P = 0.040). No significant increase in treatment-related toxicity was observed in the RT group compared with the NRT group. RT provided superior PFS in metastatic CC patients compared to NRT, and well tolerated. Moreover, RT, immunotherapy, lymph node metastasis only were independent significant prognostic factors for PFS. Subgroup analysis showed that combination of RT and chemotherapy obtained favorable PFS in metastatic CC patients with age>45 years, squamous carcinoma histology, metastatic at diagnosis, non-targeted therapy. Studies with a larger sample size and longer follow-up are warranted.

Pseudo CT Synthesis Using Cone-Beam CT of Cervical Cancer with GAN-Based Neural Network Model

Cervical cancer (CC) is a tumor disease that threatens the health of women. As an important treatment of CC, radiotherapy has been widely used in clinic. With the rapid development of radiotherapy technology, adaptive radiotherapy has received much attention. Adaptive radiotherapy means more accurate radiation dose and more accurate radiation area, which can effectively protect normal tissue. It is significant to improve the local control rate of tumor and the quality of life of patients. However, the Cone-Beam CT (CBCT) images collected during radiotherapy are of poor quality and cannot provide real-time radiation effect information, resulting in timely and effective adjustment of radiation dose and radiation area in the process of radiotherapy for cervical cancer. To alleviate this issue, this study will establish a model to leverage CC CBCT images to synthetize pseudo computed tomography (CT) images with high quality, so as to achieve the purpose of quality improvement. This study included the data of 20 patients with CC in ** hospital. The planning CT and CBCT scan data of each patient before radiotherapy were collected, and the interval between the two kinds of image data was required to be less than one week. After data preprocessing, a total of 1206 pairs of images were trained and tested. The generative adversarial network (GAN) is constructed. In order to ensure the similarity between the input image and the output image, the L1 loss function is leveraged. And the full supervision method is used to train the model to achieve a better effect of image synthesis and improve the quality of CBCT image. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were used as evaluation indexes. Using five-fold cross-validation, the values of PSNR between the pseudo-CT (sCT) and the planning CT (pCT) image and between the CBCT and the pCT image are calculated. The results are 26.9 and 22.6, respectively. The sCT obtained from the GAN model increases the peak signal-to-noise ratio by 19% compared with the original CBCT, which means that the proposed model built in this study can improve the useful information of the CBCT image. The SSIM values between sCT and pCT and between CBCT and pCT are also calculated, and the average values of them are 0.89 and 0.63, respectively. Therefore, in this experiment, the structure of the sCT obtained by the proposed model is closer to pCT. And the SSIM increases by 41.2% compared with the original CBCT, which means that the sCT by the proposed model is more similar to the pCT in structure. These results could make a more accurate judgment on the effect of radiotherapy. In this study, the pseudo-CT synthesis method based on GAN can improve the quality of CC CBCT image. The results show this method makes the structure clearer and could assist doctors to adjust the radiation dose and radiation area in time. This study is able to facilitate the development of adaptive radiotherapy for CC.

Dosimetric Advantages of Online Adaptative Radiotherapy for Cervical Cancer on 1.5T MR-Linac

Online adaptative radiotherapy (ART) strategy can be applied to account for inter-fraction organ motion while limiting organ at risk (OAR) dose. This study aims to evaluate tumor target and OARs inter- and intrafraction motion using online MRI during the full course of MR-Linac radiotherapy fractions. Furthermore, quantify the dosimetric consequences of online adaptative compared with non-adaptative radiotherapy (non-ART) in cervical cancer. Six cervix cancer patients were treated with 150 fractions on the 1.5 T Unity MR-Linac. Each fraction, pre-treatment MRI scans were obtained at the start of every treatment session, and post-treatment MRI scans were obtained at the end of every treatment session. A total 300 MR images were included in this study and the CTV, bladder and rectum were delineated on each MRI by the same radiation oncologist. The inter-fraction and intrafraction changes of contours were evaluated by dice similarity coefficient (DSC), Hausdorff distance (HD), volume difference (ΔV). The reference treatment plans were generated using step-and-shoot IMRT and utilized 9 beam groups on original CT. Then, the online adaptative treatment plans were obtained by re-optimizing based on the contours on daily pre-treatment MRI by "adapt to shape" workflow using the same beam parameters and optimization objectives from the reference plans. Non-ART plans for each patient were generated by recalculating the dose from the reference plans on daily online MRI by "adapt to position" workflow. CTV coverage and OARs constraints were used to compare ART and non-ART plans. The results showed that large inter-fraction anatomical changes limited the efficacy of radiation therapy (CTV: DSC: 0.89±0.03, HD: 20.83±5.05mm, ΔV: 1.21%±5.44%; Bladder: DSC: 0.68±0.18, HD: 30.58±15.75mm, ΔV: -10.17%±61.19%; Rectum: DSC: 0.69±0.09, HD: 22.98±12.03mm, ΔV: 21.01%±20.59%).The intrafraction anatomical changes were smaller (CTV: DSC: 0.96±0.01, HD: 8.85±3.54mm, ΔV: -0.64%±1.90%; Bladder: DSC: 0.90±0.07, HD: 14.62±9.56mm, ΔV: 19.83%±21.71%; Rectum: DSC: 0.98±0.04, HD: 2.90±4.27mm, ΔV: 0.13%±5.04%) . Non-ART showed inadequate primary CTV coverage in 30% of the daily fractions. Online adaptative plans improved CTV coverage significantly (p<0.001) to 99%. Compared with non-ART, online ART decreased the fraction dose to bladder and rectum indicated by significant (p<0.001) improvements for daily D50%, D2% and Dmean. In cervical cancer radiotherapy, a non-adaptive strategy led to inadequate target coverage for individual patients. Online adaptative radiotherapy corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to rectum and bladder was decreased significantly when applying online adaptative radiotherapy.

Single-Cell and Spatial Transcriptomics Revealing the Role of IDO1 in HPV+ Cervical Cancer Tumor Immune Microenvironment and Its Implications in Radiotherapy and Immunotherapy

Persistent infection of human papillomavirus (HPV) is one major etiology of cervical cancer (CC). By now, anti-PD-1 immunotherapy is approved for advanced CC patients, but the response rate was just about 10-20%, tumor immune microenvironment (TIME) might be one factor that affect the efficacy. The indoleamine 2,3-dioxygenase (IDO), a metabolic immune checkpoint, is recently shown to have a correlation-ship with HPV carcinogenesis in CC, with unknown mechanism. This study, using the single cell transcriptomic single-cell sequencing and spatial transcription sequencing analysis/immunologic technology, aimed to exam the role of IDO1 expression in HPV+ CC TIME and explore the changes after radiotherapy. Newly diagnosed advanced HPV- CC and HPV+ CC patients were tested for the tumor and tumor immune microenvironment (TIME) heterogeneity and their changes after fractionated radiation therapy. Tumor tissues were collected, single cell suspension was made for Single-cell RNA sequencing (SCRNAseq) using the 10 × Genomics, while frozen tissue was embedded for spatial transcriptome sequencing (STRNAseq). Seurat 4.0 was used to cluster and annotate cell clusters and map SCRNAseq data to the STRNAseq data. The specific characters of cell clusters were computed by Gene Set Enrichment Analysis (GSEA). SPOTLight and CellChat were used to analyze cell location and interaction respectively. A total of 28631 cells were clustered into 31 cell subsets in HPV- CC and HPV+ CC tissues, including baseline (Pre HPV- CC and Pre HPV+ CC) and 3-week after radiotherapy (Post 3w HPV- CC and Post 3w HPV+CC). There were 10431 epithelial cells (Epi) in all these 4 tumor tissues, with heterogenous IDO1 expression, including IDO1-high Epi, IDO1-low Epi, and IDO1-neg Epi. Interestingly, more than 99% of Epi in Pre HPV- CC tissues were IDO1-neg cells, while more than 99% in Pre HPV+ CC tissue were IDO1-high. Furthermore, the proportion of IDO1-high Epi in Pre HPV+ CC patient dropped to 16.7% after radiotherapy, while the proportion of IDO1-low Epi rase to 63.3%. Using GSEA, the characters of IDO1-high Epi group was shown to have positive regulation of leukocyte chemotaxis and negative regulation of cell adhesion and differentiation. IDO1-high Epi cells also had the hallmark of interferon gamma response. These cells could mainly receive regulative information of interferon gamma pathway from exhausted CD8 T cells, which could affect the apoptosis of tumor cells. This study comprehensively analyzed the immune suppressive role of IDO1-high Epi cells in HPV+ CC TIME at the single-cell transcriptional scale and explored their functional characters in CC radiotherapy. This would be able to provide more evidence to combine with radiotherapy and immunotherapy to improve patients' prognosis.

A Comparative Analysis of Effect of HIV Infection on Outcomes of Cervical Cancer Treated with Radiotherapy

There is paucity of data on management of human immunodeficiency virus (HIV) positive cervical cancer and its clinical outcomes in Indian women. The primary objective of this study was to compare disease free survival (DFS) and overall survival (OS) between HIV-positive and HIV-negative patients receiving radiotherapy (RT) for cervical cancer. The secondary endpoints were toxicity and various factors affecting DFS and OS. Patients diagnosed with cervical cancer on histopathology and treated with RT with or without concomitant chemotherapy (CT) at an institution between 2015 and 2020 were included in this retrospective analysis. On the basis of HIV serology test, 70 patients were included in each arm, Arm A had HIV-negative patients and Arm B had HIV-positive patients. In both the arms, external beam radiotherapy (EBRT) in adjuvant or radical setting was given with a total dose of 46-50 Gy to whole pelvis and iliac nodes; 2 Gy/fraction daily as 5 fractions/week by conventional four-field box technique or conformal 3-dimensional radiotherapy (3DCRT) or Intensity modulated radiotherapy (IMRT). Concurrent cisplatin was administered as weekly 40mg/m2 to patients with ECOG< = 2, creatinine clearance >40mL/min in radical and adjuvant patients as indicated. CD4 counts ≥200 cells/mm3 was a prerequisite for concurrent cisplatin in Arm B. Intracavitary or interstitial brachytherapy was delivered as indicated. Statistical analysis was done using statistical software. Kaplan-Meier method used for all survival analysis. Log rank test was used to calculate statistical significance for various prognostic factors followed by Cox regression test for multivariate analysis. Median age was 46.5 years (range: 30-76). In Arm A, 62 patients (88.57%) and 5 patients (7.14%) received radical and adjuvant RT. In Arm B 61 patients (87.14%) and 2 patients (2.85%) were given radical and adjuvant RT. 66 patients (94.28%) in Arm A and 52 patients (74.28%) in Arm B received concurrent cisplatin. At a median follow up of 33.8 months (range: 1.2 to 85.4), 2-year DFS was 88.9% for Arm-A and 86.5% for Arm-B (p = 0.134) and 2-year OS was 91.4% and 82.9% for Arm-A and Arm-B (p = 0.001), respectively. Grade III/IV skin toxicity was seen in and 4 patients (5.71%) in Arm A and 12 patients (17.14%) in Arm B (p = 0.34). Grade III/IV gastrointestinal toxicity was seen in 2(2.85%) patients and 4(5.7%) patients in Arm A and Arm B respectively (p = 0.40). 14(20%) patients in Arm A and 27(38.5%) patients in Arm B had Grade III/IV hematologic toxicity (p = 0.016). On multivariate analysis, anemia (Hb≤12 gm/dl) and OTT ≥56 days were associated with unfavorable DFS (p = 0.03 and p = 0.001) and OS (p = 0.04 and p = 0.01) in Arm B. In view of comparable DFS outcomes in both the arms, HIV-positive cervical cancer patients can be managed with the standard treatment protocol as HIV-negative patients. HIV-positive patients are more likely to experience poorer DFS and OS. However, results need to be validated on prospective study.

Clinical prior Knowledge-Based One-Shot Learning for Automatic Delineation of Clinical Target Volumes in Adaptation Radiotherapy of Cervical Cancer

Rapid and accurate delineation of clinical target volumes (CTV) of cervical cancer is the crux to ensure the efficiency and benefits of adaptation radiotherapy (ART). However, contour propagation using deformation image registration (DIR) is difficult to ensure the accuracy of CTV contours due to the significant tumor recession in next fraction, and the tumor progress in each fraction is not considered by conventional automatic delineation methods based on deep learning (DL). Currently, one-shot learning (OSL) is feasible to learn the tumor progress from former fractions to improve the accuracy of automatically delineating CTV. We retrospectively collected 45 patients with cervical cancer from January 2021 to May 2022 in our department. All patients consist of a pair of planning CT and daily CT in ART. A personalized automatic delineation method based on one-shot learning was developed to delineate CTV in daily CT by learning the clinical prior knowledge from the CTV contours and images of planning CT. The performance of our proposed method was evaluated by dice similarity coefficient (DSC), 95% Harsdorff distance (95HD) and average surface distance (ASD) with human experts, and its automatic delineation performance were compared with DIR and DL in daily CT. Our automatic delineation method OSL performed the best results in all evaluation metrics (denoted by mean ± standard deviation) as shown in Table 1, it is superior to method DL: 0.92 & 0.90 of DSC, 2.33 mm & 2.68 mm of HD95, 0.68 mm & 0.82 mm of ASD, P < 0.05 for DSC and ASD. Specifically, our method is significantly superior to the automatic delineation results by method DIR: 0.92 & 0.84 of DSC, 2.33 mm & 4.11 mm of HD95, 0.68 mm & 1.52 mm of ASD, P < 0.05 for all. In addition, OSL can significantly overcome the delineation problems in fuzzy boundary and delineation missing and perform better generalization for some unusual images, compared with DIR and DL. We proposed an automatic delineation method based on one-shot learning for CTV of cervical cancer in ART, the results demonstrated that the proposed method could improve the precision and generalization of automatically delineating CTV compared against current popular methods. Therefore, it is potential to improve the quality and efficiency of ART for personalized patients and have a positive impact on tumor control and patient survival.

Prediction of Progression After Cervix Cancer Radiotherapy Using a Machine-Learning Model on Pre-Treatment MRI

MRI may be useful to identify women with cervical cancer at high risk of disease progression to test strategies of treatment intensification. The purpose of this study was to determine the value of a machine-learning model built on pre-treatment MRI for prediction of risk of progression after radiation therapy. MagneticResonance Imaging (MRI) data for women with cervical cancer was collected from The Cancer Genome Atlas Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma Collection (TCGA-CESC) on the Cancer Imaging Archive (TCIA), which reported clinical, treatment, and imaging data from a single institution. 27 patients who had received radiation for cervical cancer were selected for input into a custom 3-D Residual Neural Network (ResNet) model with added custom layers specific to DICOM data in tensorflow python package. One T2 MRI per patient was used to predict recurrence free survival after radiation treatment, where patients were predicted to be "high risk" or "low risk" for disease recurrence as the output of the model. All slices of the T2 MRI were used. The model was validated using five-fold cross validation; 80% of the data was used to train each fold and 20% was used for testing. Final model statistical significance was confirmed through shuffle test at the p < 0.01 level. The clinical outcomes of patients and the model's "low-risk" and "high-risk" prediction were compared. There were 27 patients in the study with mean age of 51 years (range 29-79). 20 patients had squamous cell carcinoma and 7 patients had adenocarcinoma. The stage breakdown consisted of 9 women IB, 2 IIA, 9 IIB, 2 IIIA, 2 IIIB, and 3 stage IV. 10 women were treated with radiation alone and 17 with chemo-radiation. 5 women received surgery in addition to radiation or chemoradiation. 21 patients received brachytherapy. Median follow-up of patients was 29 months (range 3-64). The model predicted 7 patients as "high risk" for recurrence; all 7 developed a recurrence during follow up. None of the 20 patients predicted to be "low risk" developed disease recurrence. Among all patients in the study, the two-year progression free survival (PFS) was 82.0%. Patients identified as "low risk" and "high risk" by model had two-year PFS of 100% and 43%, respectively. Among patients with recurrence, 3 developed local recurrence and 4 developed distant metastases. The ResNet model achieved cross-validated accuracy of 92% for prediction of progression-free survival (p<0.01). A 3-D ResNet machine-learning model using pretreatment MRI image data can accurately predict clinical outcomes for cervical cancer following radiation therapy. Future work to confirm generalizability should focus on validation with a larger clinical dataset.

Recent Advances and Adaptive Strategies in Image Guidance for Cervical Cancer Radiotherapy.

The standard of care for locally advanced cervical cancer is external beam radiotherapy (EBRT) with simultaneous chemotherapy followed by an internal radiation boost. New imaging methods such as positron-emission tomography and magnetic resonance imaging have been implemented into daily practice for better tumor delineation in radiotherapy planning. The method of delivering radiation has changed with technical advances in qualitative imaging and treatment delivery. Image-guided radiotherapy (IGRT) plays an important role in minimizing treatment toxicity of pelvic radiation and provides a superior conformality for sparing the organs at risk (OARs) such as bone marrow, bowel, rectum, and bladder. Similarly, three-dimensional image-guided adaptive brachytherapy (3D-IGABT) with computed tomography (CT) or magnetic resonance imaging (MRI) has been reported to improve target coverage and reduce the dose to normal tissues. Brachytherapy is a complementary part of radiotherapy treatment for cervical cancer and, over the past 20 years, 3D-image-based brachytherapy has rapidly evolved and established itself as the gold standard. With new techniques and adaptive treatment in cervical cancer, the concept of personalized medicine is introduced with an enhanced comprehension of the therapeutic index not only in terms of volume (three-dimensional) but during treatment too (four-dimensional). Current data show promising results with integrated IGRT and IGABT in clinical practice and, therefore, better local control and overall survival while reducing treatment-related morbidity. This review gives an overview of the substantial impact that occurred in the progress of image-guided adaptive external beam radiotherapy and brachytherapy.

Changes of brain network in patients with insomnia following radiotherapy for cervical cancer and their correlation with IT-TMS treatment efficacy: a graph-theory analysis

To analyze the changes of brain small-world and node function network properties in patients with insomnia following radiotherapy for cervical cancer based on graph theory analysis and explore the correlation between functional networks and the clinical efficacy of individual-target transcranial magnetic stimulation (IT-TMS) for treatment of insomnia. The resting state functional magnetic resonance imaging (rs-fMRI) data were collected from 30 patients with insomnia following radiotherapy for cervical cancer and 30 matched healthy individuals. All the patients received accelerated intelligent neuromodulation TMS therapy. Using graph theory analysis and GRETNA software, the functional connectivity matrices were constructed and the attribute features were extracted. The scores on the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) of the participants were collected before and after IT-TMS, and the correlation between improvement in insomnia and the functional network was investigated. The two groups matched for age, gender, and education level (P>0.05) showed significant differences in PSQI, ISI, SAS and SDS scores (P<0.05). Both groups showed attributes of the small-world network. Compared with the healthy individuals, the patients showed significantly decreased σ, EI, Cp and Lp (P<0.05) and increased Eg (P<0.05) at baseline, which, along with insomnia symptoms, were all improved after IT-TMS treatment. The patients showed reduced functional connections of the node network at follow-up compared with the baseline, and the low functional connectivity between the right insula and left superior frontal gyrus was correlated with the improvement of ISI scores. The patients with insomnia following radiotherapy for cervical cancer have impaired information integration ability of the brain network, IT-TMS can significantly improve insomnia symptoms by reducing the hyperconnectivity between the default mode network and the salience network.

Dosimetric Evaluation of the Benefits of Intensity Modulated Techniques in Cervical Cancer Radiotherapy

"External beam radiotherapy for cervical cancer using 3D conformal radiotherapy (3D-CRT) is a standard procedure in Romania. A dosimetric planning comparison between 3D-CRT and intensity modulated techniques evaluating both target parameters and organs at risk could justify the implementation of the latter techniques in clinical settings. 50 cervical cancer patients were treated with 3D-CRT, and equivalent plans simulated with IMRT and VMAT for a comparative dosimetric assessment. In addition to providing better compliance and homogeneity, intensity modulated techniques provide superior protection for organs at risk, especially for bowel bag, influencing patients’ quality of life. "

Effect of bladder filling status on positioning errors in post-hysterectomy cervical cancer radiotherapy

Objective: To investigate the effect of different bladder filling states on positioning errors in radiotherapy for cervical cancer and obtain the reference range of bladder filling consistency during radiotherapy. Methods: Patients who underwent postoperative radiotherapy for cervical cancer in Nantong Tumor Hospital from October 2018 to December 2019 were selected. According to the bladder filling deviation, they were divided into group A1 (deviation < 20%) and group B1 (deviation ≥ 20%). The bladder filling variations of the two groups were compared with different positioning errors. Group A2 has a positioning error of <0.4 cm, and group B2 has a positioning error of ≥0.4 cm. The reference range of bladder filling consistency during radiotherapy is obtained by analyzing the composition ratio of different positioning errors of bladder filling deviation. Results: This study included 195 patients with cervical cancer. The error of longitudinal and vertical position in group B1 was significantly higher than that in group A1 (0.50 ± 0.34 vs. 0.26 ± 0.22 cm, p < 0.001, and 0.22 ± 0.17 vs. 0.16 ± 0.12 cm, p < 0.001). Compared with group B2, the absolute deviation of bladder filling in group A2 (54.1% ± 54.4% vs. 25.6% ± 22.7%, p < 0.001) was slight. The chi-square test showed significant differences in the proportion of the positioning state of different bladder filling forms (χ 2 = 31.006, p < 0.001). In addition, there was a significant difference in the proportion of stability errors in patients with poor stability in different directions (χ 2 = 118.551, p < 0.001). Conclusion: In patients with cervical cancer fixed in the supine position, a bladder capacity deviation <20% is easier to achieve excellent positioning with, and it can better control the positioning error of radiotherapy and ensure the positioning accuracy of dose distribution to the target area. It can also achieve good tumor treatment effects. This range can be used as a reference for bladder filling consistency in patients with cervical cancer undergoing radiotherapy.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation. Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer radiotherapy. A comprehensive search of optimal hyperparameters for all models was conducted by varying the initial learning rate, image normalization methods, and (when appropriate) convolutional kernel size, the number of learnable parameters via network depth and the number of feature maps per convolution, and nonlinear activation functions. This yielded over 1700 unique models, which were all trained until performance converged and then tested on a separate dataset. Of all hyperparameters, the choice of initial learning rate was most consistently significant for improved performance on the test set, with all top-performing models using learning rates of 0.0001. The optimal image normalization was not consistent across architectures. High overlap (mean Dice similarity coefficient=0.98) and surface distance agreement (mean surface distance<2mm) were achieved between the treatment field apertures for all architectures using the identified best hyperparameters. Overlap Dice similarity coefficient (DSC) and distance metrics (mean surface distance and Hausdorff distance) indicated that DeepLabv3+ and D-LinkNet architectures were least sensitive to initial hyperparameter selection. DeepLabv3+ and D-LinkNet are most robust to initial hyperparameter selection. Learning rate, nonlinear activation function, and kernel size are also important hyperparameters for improving performance.

3D Laparoscopic Ureterolysis for Retroperitoneal Fibrosis Secondary to Radical Hysterectomy and Radiation Treatment for Cervical Cancer: Results from the Oncological Institute, Cluj Napoca.

Ureterolysis represents the surgical treatment for retroperitoneal fibrosis. The aim of the study was to review the outcomes of patients who had undergone radical hysterectomy and radiotherapy for cervical cancer that later developed retroperitoneal fibrosis, for whom 3D laparoscopic ureterolysis was performed in our department and to review current published studies. We present a series of cases consisting of 6 patients with secondary retroperitoneal fibrosis. In all cases, the intervention was performed by the same surgeon from the Oncological Institute "Prof. Dr. Ion Chiricuță" Cluj-Napoca, Romania. We carried out a literature review, searching in the PubMed and MEDLINE studies published between 2000 and 2021 relevant to the matter and a total of 12 papers were selected. We reviewed the functional outcomes of patients that underwent minimally invasive ureterolysis. 3D laparoscopic ureterolysis was performed in 6 patients. Mean operative time was 166 minutes and mean blood loss was 203 mL. No surgery required conversion. Five patients showed good functional results after ureteral stent removal. In one case, the patient developed acute pyelonephritis and the ureteral stents were kept. Laparoscopic ureterolysis for retroperitoneal fibrosis secondary to operated and radiation-treated cervical cancer represents one of the most complex and challenging surgeries in the urological field. From personal experience we conclude that in oncological centers with vast experience in laparoscopy this minimally invasive approach is feasible and safe. Published data, even though scarce, strengthens our results and the need for this surgery in patients with retroperitoneal fibrosis with urological impact. The laparoscopic approach comes with good functional results and with the advantages of faster post-operative recovery comparing to open surgery and comparable results with the precision and dexterity offered by the robotic approach, but with lower economic burden.

Metachronous Ovarian Cancer after a Radical Hysterectomy with Ovarian Conservation for Early-Stage Cervical Cancer: A Case Report

Introduction: Cervical cancer is the fourth most common disease in women worldwide and the leading cause in Tanzania, with 9,772 new cases and 6,695 deaths annually. Surgery is better than radiation or chemotherapy for early-stage cervical cancer (stages IA2–IIA1). Due to the risks of oophorectomy in young women, ovarian conservation is crucial. Metachronous ovarian cancer is understudied, however, ovarian conservation does not enhance cervical cancer mortality. Clinical presentation: We report a rare case of recurrent metachronous ovarian cancer in a 42-year-old female, Para 3, Living 3, who had her ovaries conserved following a radical hysterectomy and bilateral lymph node dissection for stage IB2 cervical cancer at 37 years old in April 2017. The final biopsy showed a well-differentiated, invasive cervical adenocarcinoma. Stage IV ovarian cancer with significant ascites and pleural effusion was detected in July 2018, 14 months post-surgery. Six chemotherapy treatments and total tumor debulking succeeded. Despite the most effective cytoreduction surgery, the patient experienced two further recurrences in 2020 and 2022. After additional surgeries and chemotherapy, she is currently in complete remission and will be followed up. Conclusion: Young women undergoing radical hysterectomy for early-stage cervical cancer must preserve their ovaries, but metachronous ovarian cancer is a risk. Thus, metachronous ovarian cancer risks, challenges, and outcomes must be understood.

PAX1 hypomethylation as a prognostic biomarker for radioresistance of cervical cancer

BackgroundPAX1 gene methylation plays an important role in the development of cervical cancer. However, its prognostic value after radiotherapy for locally advanced cervical cancer is unknown, so this study aimed to investigate the value of PAX1 gene methylation for predicting the sensitivity of radiotherapy for cervical cancer.MethodsWe selected 125 patients with primary cervical cancer who underwent concurrent chemo-radiotherapy as the study population, quantitative methylation-specific polymerase chain reaction (QMSP) was used for detecting PAX1 methylation status of cervical exfoliated cells. Logistic regression model was used to analyze the risk factors associated with the short-term efficacy and to establish a prediction model of radiotherapy sensitivity based on PAX1 gene methylation. Cell viability after radiation of Hela and SiHa cells transfected with PAX1 or control vector was evaluated by CCK8. Furthermore, RNA-Seq analyses identified different expressed genes (DEGs) in PAX1 overexpressed SiHa cells. Gene Ontology (GO) and pathway enrichment analysis was carried out to determine the biological function of DEGs.ResultsPAX1 methylation level was associated with HPV16/18-positive rate. PAX1 hypomethylation was found to be a risk factor for tumor residual after chemo-radiotherapy. A nomogram containing the risk factors for PAX1 methylation status, lymph node metastasis, pathological type and tumor size was further constructed to predict the probability of tumor residual after chemo-radiotherapy (AUC = 0.823, 95% CI 0.736–0.910). High PAX1 protein level was more likely to cause radioresistance in both Hela and SiHa cells. Transcriptomic sequencing of PAX1 overexpressed and control cells identified 615 differentially expressed genes, and GO enrichment analysis suggested that PAX1 may be involved in the regulation of signaling receptor activity and response to viruses.ConclusionPAX1 hypomethylation status could be used as a promising biomarker to predict radioresistance in cervical cancer. This further provides a new idea for the individualized treatment strategy of simultaneous radiotherapy for cervical cancer.

CBCT-based deformable dose accumulation of external beam radiotherapy in cervical cancer

Background: Delivered radiotherapy doses do not exactly match those planned for a course of treatment, largely due to inter-fraction changes in anatomy. In this study, accumulated delivered dose was calculated for a sample of cervical cancer patients, by deformably registering daily cone beam computed tomography (CBCT) images to the planning computed tomography (CT) scan. Planned and accumulated doses were compared for the clinical target volume (CTV), bladder, and rectum. Material and Methods: For 10 patients receiving 45 Gy in 25 fractions of external beam radiotherapy, daily dose distributions were calculated on CBCT. These images were deformed onto the planning CT and the dose was accumulated using Velocity 4.1 (Varian Medical Systems, Palo Alto, USA). The quality of deformable image registration was evaluated visually and by calculating Dice similarity coefficients and mean distance to agreement. Results: V95%>99% was achieved for the primary CTV in 9/10 patients for the planned dose distribution and 7/10 patients for the accumulated dose distribution. Primary CTV coverage by 95% of the prescription dose was reduced in one patient, due to an increase in anterior-posterior separation. Comparison of planned and accumulated dose volume histograms (DVHs) for the bladder and rectum found agreement within 5% at low and intermediate doses, but differences exceeded 20% at higher doses. Direct addition of CBCT DVHs was seen to be a poor estimate for the accumulated DVH at higher doses. Conclusion: Computation of delivered radiotherapy dose that accounts for inter-fraction anatomical changes is important for establishing dose-effect relationships. Updating delivered dose distributions after each fraction would support informed clinical decision making on any potential treatment interventions.

CircRNF13, a novel N6-methyladenosine-modified circular RNA, enhances radioresistance in cervical cancer by increasing CXCL1 mRNA stability

BackgroundCircular RNAs (circRNAs) and N6-methyladenosine (m6A) have been shown to play an increasingly critical role in the development of different cancers. However, there is limited evidence on how circRNAs and m6A interact to affect the radiosensitivity of cervical cancer (CC). This study provides a mechanistic understanding of the novel m6A-regulated circRNF13 in enhancing radioresistance in CC.MethodsDifferentially expressed circRNAs were identified from radiosensitive and radioresistant CC tissues. Meanwhile, these circRNAs were subjected to methylated RNA immunoprecipitation (Me-RIP). Finally, the effects of these circRNAs on radiosensitivity were characterized.ResultsCircRNF13 was poorly expressed in CC patients that were sensitive to concurrent radiochemotherapy. Experiments conducted both in vitro and in vivo confirmed that the knockdown of circRNF13 potentiated the radiosensitivity of CC cells. Further mechanistic studies revealed that METTL3/YTHDF2 promoted the degradation of circRNF13 and subsequently affected the stability of CXC motif chemokine ligand 1 (CXCL1), ultimately enhancing the radiosensitivity of CC cells.ConclusionThis study identified circRNF13 as a novel m6A-modified circRNA and validated the METTL3/YTHDF2/circRNF13/CXCL1 axis as a potential target for CC radiotherapy.

Dosimetry study of Auto-VMAT planning and Manual-VMAT planning based on Pinnacle3 9.10 in radiotherapy for cervical cancer.

The purpose of this study was to compare the dose distribution characteristics of automatic volume-modulated arc therapy (Auto-VMAT) planning and manual volume-modulated arc therapy (Manual-VMAT) planning of Philips Pinnacle3 9.10 planning system, to provide a basis for optimal radiation therapy planning for cervical cancer. Ten patients with cervical cancer in our hospital from September to December 2018 were selected, and 2 treatment plans, Auto-VMAT plan and Manual-VMAT plan, were designed using Pinnacle3 9.10 planning system, respectively, to evaluate the maximum dose Dmax, mean dose Dmean, homogeneity index of the target area according to the dose volume histogram, the conformability index, plan optimization time, monitor units (MUs), organ at risk and other indicators. The results were that the Auto-VMAT plan was superior to the Manual-VMAT plan for target area Dmean, conformability index, and homogeneity index, with statistically significant differences (P < .05) and no significant difference in maximum dose Dmax (P > .05); rectal V40, V50, and Dmean in the Auto-VMAT plan, bladder V40, V50, and Dmean, small bowel V30, V40, V50 and Dmean, and right and left femoral V50 and Dmean were all lower than the Manual-VMAT plan, and the difference was statistically significant (P < .05); the mean optimization time for the Auto-VMAT and Manual-VMAT plans was 47 minutes and 35 minutes, respectively, an increase of 34%. The average number of MUs was 519 MUs and 374 MUs, respectively, an increase of 28%. This study concluded that the Pinnacle3 9.10-based Auto-VMAT plan was clinically feasible and significantly superior to the Manual-VMAT plan in terms of improved target area uniformity and conformability and reduced organ endangerment dose while reducing the impact of human factors on the quality of plan design.

Forecasting patient-specific dosimetric benefit from daily online adaptive radiotherapy for cervical cancer

Objective. Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, Requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients with the greatest benefit from ART, so resources might be properly allocated to the highest-yield patients. Approach. CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the coefficient of determination (R2) between dose and volume metrics from initial treatment plans and the dosimetric benefits to the and from adaptive radiotherapy using reduced 3 mm or 5 mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics for The three highest performing metrics were used to build multivariate models with leave-one-out validation for Main results. Patients with higher initial bowel doses were correlated with the largest decreases in Bowel from daily adaptation (linear best fit R2 = 0.77 for a 3 mm PTV margin and R2 = 0.8 for a 5 mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initial and using standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R2 of 0.66 between predicted and true adaptive benefits for both margins. Significance. The resulting models could be used to prospectively triage cervical cancer patients on or off daily adaptation to optimally manage clinical resources. Additionally, this work presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts.