Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients.

OBJECTIVE: In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE. METHODS: Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible. RESULTS: In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm. CONCLUSION: Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis. TRIAL REGISTRATION NUMBER AND DATE: BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .

Long-term follow-up of protective effects on salivary and swallowing structures and improvement of late xerostomia and dysphagia by level IIb optimisation in clinical target volume of nasopharyngeal carcinoma.

BACKGROUND: This study aimed to assess the long-term effect of level IIb clinical target volume (CTV) optimisation on survival, xerostomia, and dysphagia in patients with nasopharyngeal carcinoma (NPC). METHODS: Clinical data of 415 patients with NPC treated with intensity-modulated radiotherapy between December 2014 and October 2018 were retrospectively analysed. The patients were categorised into modified and comparison groups. Late xerostomia and dysphagia were evaluated using Radiation Therapy Oncology Group/European Organisation for Research and Treatment of Cancer scoring. Survival analysis was performed using the Kaplan-Meier method. Differences in late toxicity and dose parameters between both groups were compared. Prognostic factors for survival and late toxicity were assessed using regression analyses. RESULTS: Patients in the modified group developed late xerostomia and dysphagia less frequently than those in the comparison group did (P < 0.001). The mean dose (Dmean) and V26 of parotid glands; Dmean and V39 of submandibular glands; and Dmean of sublingual glands, oral cavity, larynx, and superior, middle, and lower pharyngeal constrictor muscles were lower in the modified group than those in the comparison group (all P < 0.001). Both groups had no significant differences in overall, local recurrence-free, distant metastasis-free, or progression-free survival. The Dmean of the parotid and sublingual glands was a risk factor for xerostomia. The Dmean of the parotid and sublingual glands and middle pharyngeal constrictor muscle was a risk factor for dysphagia. CONCLUSIONS: Level IIb optimisation in NPC patients who meet certain criteria specially the exclusion of positive retropharyngeal nodes treated with intensity-modulated radiotherapy has the potential to better protect the salivary and swallowing structures, decreasing the development of late radiation-induced xerostomia and dysphagia while maintaining long-term survival.

Measurement of the distance between tumor micro-foci and gross tumor in rectal cancer pathological specimens: implication on margin distance of clinical target volume treated with high-dose radiotherapy for rectal cancer.

PURPOSE: To measure the micro-foci distance away from gross tumor and to provide reference to create the clinical target volume (CTV) margin for boost radiotherapy in rectal adenocarcinoma. METHODS: Twenty-eight rectal cancer surgical specimens of only total mesorectal excision were collected. The pathological specimens were retrospectively measured, and the nearest distance between the tumor micro-foci and gross tumor was microscopically measured. The "in vivo-in vitro" retraction factor was calculated as the ratio of the deepest thickness laterally and the vertical height superior/inferiorly of the rectal tumor measured in MRI and those measured in immediate pathological specimens. The retraction factor during pathological specimen processing was calculated as the distance ratio before and after dehydration in the lateral, superior, and inferior sides by the "knot marking method." The distances of tumor micro-foci were individually corrected with these two retraction factors. RESULTS: The mean "in vivo-in vitro" tumor retraction factors were 0.913 peripherally and 0.920 superior/inferiorly. The mean tumor specimen processing retraction factors were 0.804 peripherally, 0.815 inferiorly, and 0.789 superiorly. Of 28 patients, 14 cases (50.0%) had 24 lateral micro-foci, 8 cases (28.6%) had 13 inferior micro-foci, and 7 cases (25.0%) had 19 superior micro-foci. The 95th percentiles of the micro-foci distance for 28 patients were 6.44 mm (peripheral), 5.54 mm (inferior), and 5.42 mm (superior) after retraction correction. CONCLUSION: The micro-foci distances of 95% of rectal adenocarcinoma patients examined were within 6.44 mm peripherally, 5.54 mm inferiorly, and 5.42 mm superiorly. These findings provide reference to set the boost radiotherapy CTV margin for rectal cancer.

Microinvasion in hepatocellular carcinoma: predictive factor and application for definition of clinical target volume for radiotherapy.

BACKGROUND: To investigate the correlation between microinvasion and various features of hepatocellular carcinoma (HCC), and to clarify the microinvasion distance from visible HCC lesions to subclinical lesions, so as to provide clinical basis for the expandable boundary of clinical target volume (CTV) from gross tumor volume (GTV) in the radiotherapy of HCC. METHODS: HCC patients underwent hepatectomy of liver cancer in our hospital between July 2019 and November 2021 were enrolled. Data on various features and tumor microinvasion distance were collected. The distribution characteristics of microinvasion distance were analyzed to investigate its potential correlation with various features. Tumor size compared between radiographic and pathologic samples was analyzed to clarify the application of pathologic microinvasion to identify subclinical lesions of radiographic imaging. RESULTS: The average microinvasion distance was 0.6 mm, with 95% patients exhibiting microinvasion distance less than 3.0 mm, and the maximum microinvasion distance was 4.0 mm. A significant correlation was found between microinvasion and liver cirrhosis (P = 0.036), serum albumin level (P = 0.049). Multivariate logistic regression analysis revealed that HCC patients with cirrhosis had a significantly lower risk of microinvasion (OR = 0.09, 95%CI = 0.02 ~ 0.50, P = 0.006). Tumor size was overestimated by 1.6 mm (95%CI=-12.8 ~ 16.0 mm) on radiographic size compared to pathologic size, with a mean %Δsize of 2.96% (95%CI=-0.57%~6.50%). The %Δsize ranged from - 29.03% to 34.78%. CONCLUSIONS: CTV expanding by 5.4 mm from radiographic GTV could include all pathologic microinvasive lesions in the radiotherapy of HCC. Liver cirrhosis was correlated with microinvasion and were independent predictive factor of microinvasion in HCC.

Landmark-based auto-contouring of clinical target volumes for radiotherapy of nasopharyngeal cancer.

BACKGROUND: The delineation of clinical target volumes (CTVs) for radiotherapy for nasopharyngeal cancer is complex and varies based on the location and extent of disease. PURPOSE: The current study aimed to develop an auto-contouring solution following one protocol guidelines (NRG-HN001) that can be adjusted to meet other guidelines, such as RTOG-0225 and the 2018 International guidelines. METHODS: The study used 2-channel 3-dimensional U-Net and nnU-Net framework to auto-contour 27 normal structures in the head and neck (H&N) region that are used to define CTVs in the protocol. To define the CTV-Expansion (CTV1 and CTV2) and CTV-Overall (the outer envelope of all the CTV contours), we used adjustable morphological geometric landmarks and mimicked physician interpretation of the protocol rules by partially or fully including select anatomic structures. The results were evaluated quantitatively using the dice similarity coefficient (DSC) and mean surface distance (MSD) and qualitatively by independent reviews by two H&N radiation oncologists. RESULTS: The auto-contouring tool showed high accuracy for nasopharyngeal CTVs. Comparison between auto-contours and clinical contours for 19 patients with cancers of various stages showed a DSC of 0.94 ± 0.02 and MSD of 0.4 ± 0.4 mm for CTV-Expansion and a DSC of 0.83 ± 0.02 and MSD of 2.4 ± 0.5 mm for CTV-Overall. Upon independent review, two H&N physicians found the auto-contours to be usable without edits in 85% and 75% of cases. In 15% of cases, minor edits were required by both physicians. Thus, one physician rated 100% of the auto-contours as usable (use as is, or after minor edits), while the other physician rated 90% as usable. The second physician required major edits in 10% of cases. CONCLUSIONS: The study demonstrates the ability of an auto-contouring tool to reliably delineate nasopharyngeal CTVs based on protocol guidelines. The tool was found to be clinically acceptable by two H&N radiation oncology physicians in at least 90% of the cases.

A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer.

OBJECTIVE: Adaptive planning to accommodate anatomic changes during treatment often requires repeated segmentation. In this study, prior patient-specific data was integrateda into a registration-guided multi-channel multi-path (Rg-MCMP) segmentation framework to improve the accuracy of repeated clinical target volume (CTV) segmentation. METHODS: This study was based on CT image datasets for a total of 90 cervical cancer patients who received two courses of radiotherapy. A total of 15 patients were selected randomly as the test set. In the Rg-MCMP segmentation framework, the first-course CT images (CT1) were registered to second-course CT images (CT2) to yield aligned CT images (aCT1), and the CTV in the first course (CTV1) was propagated to yield aligned CTV contours (aCTV1). Then, aCT1, aCTV1, and CT2 were combined as the inputs for 3D U-Net consisting of a channel-based multi-path feature extraction network. The performance of the Rg-MCMP segmentation framework was evaluated and compared with the single-channel single-path model (SCSP), the standalone registration methods, and the registration-guided multi-channel single-path (Rg-MCSP) model. The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) were used as the metrics. RESULTS: The average DSC of CTV for the deformable image DIR-MCMP model was found to be 0.892, greater than that of the standalone DIR (0.856), SCSP (0.837), and DIR-MCSP (0.877), which were improvements of 4.2%, 6.6%, and 1.7%, respectively. Similarly, the rigid body DIR-MCMP model yielded an average DSC of 0.875, which exceeded standalone RB (0.787), SCSP (0.837), and registration-guided multi-channel single-path (0.848), which were improvements of 11.2%, 4.5%, and 3.2%, respectively. These improvements in DSC were statistically significant (p < 0.05). CONCLUSION: The proposed Rg-MCMP framework achieved excellent accuracy in CTV segmentation as part of the adaptive radiotherapy workflow.

Optimization of supraclavicular lymph node clinical target volume delineation in high-risk breast cancer: a single center experience and recommendation.

BACKGROUND: Prophylactic irradiation of supraclavicular lymph node drainage areas can improve the regional control rate of lymph node-positive or lymph node-negative disease but a locally-advanced stage breast cancer, and it can reduce breast cancer-related mortality. However, many controversies exist in the clinical target volume delineation of supraclavicular lymph node drainage in patients with breast cancer. METHODS: We retrospectively analyzed 42 patients with breast cancer and supraclavicular lymph node metastasis at our hospital between January 2017 and December 2021. Among these cases, 32 were locally advanced and 10 were stage IV at initial treatment. A patient with breast cancer who did not undergo dissection of the supraclavicular and infraclavicular lymph nodes at our hospital was selected as a standard patient. A contrast-enhanced computed tomography (CT) scan for positioning was used as a template image, and blood vessels, muscles, and bony landmarks were used as references for positioning. The metastatic supraclavicular lymph nodes were identified in all enrolled patients and projected into the template CT images. RESULTS: The metastastic pattern of supraclavicular lymph node in breast cancer was proposed: distribution along the posterolateral border of the internal jugular vein (medial supraclavicular group) and along the transverse jugular vein (lateral supraclavicular group). We theorized that the lateral and posterior borders of the clinical target volume in the supraclavicular region should include the lymph nodes in the posterior triangle of the neck (level V) in high-risk individuals. If the metastatic axillary lymph node is extensive, then the superior border of the supraclavicular region should be moved upward appropriately. CONCLUSIONS: This study analyzed patients with breast cancer and supraclavicular lymph node metastasis at initial treatment, explored the metastastic pattern of supraclavicular lymph node, and applied anatomical knowledge to further optimize the target volume delineation of supraclavicular lymph node drainage area in high-risk breast cancer.

Involved site radiation therapy in stage I-III nasopharyngeal carcinoma with limited lymph node burden (ISRT-NPC) or elective region irradiation: a study protocol for a multicenter non-inferiority randomized controlled phase III clinical trial.

BACKGROUND: Current radiotherapy guidelines and consensus statements uniformly recommend elective region irradiation (ERI) as the standard strategy for nasopharyngeal carcinoma (NPC). However, given the scarcity of skip-metastasis, the improved assessment accuracy of nodal involvement, and the striking advancements in chemotherapy for NPC, a one-fits-all delineation scheme for clinical target volumes of the nodal region (CTVn) may not be appropriate anymore, and modifications of the CTVn delineation strategy may be warranted. Involved site irradiation (ISI) covering merely the initially involved nodal site and potential extranodal extension has been confirmed to be as effective as ERI with decreased radiation-related toxicities in some malignancies, but has not yet been investigated in NPC. This study aims to compare the regional control, survival outcomes, radiation-related toxicities, and quality of life (QoL) of ISI with conventional ERI in NPC patients with a limited nodal burden. METHODS: ISRT-NPC is a prospective, multicenter, open-label, noninferiority, phase III randomized controlled trial. A total of 414 patients will be randomly assigned in a 1:1 ratio to receive ISI or ERI. Randomization will be stratified by institution scale and N stage. Generally, in the ISI group, the high-risk CTV1 (dose: 60 Gy) includes a 1-cm expansion of the positive LN as well as the VIIa and the retrostyloid space above the bilateral transverse process of the atlantoaxial spine (C1), regardless of N status. The low-risk CTV2 (dose: 50 Gy) covers the cervical nodal region with a 3-cm caudal expansion below the transverse process of C1 for N0 disease and a 3-cm expansion below the positive LN for positive LNs. DISCUSSION: The results of this trial are expected to confirm that ISI is a non-inferior strategy to ERI in stage I-III patients with low LN burden, enabling the minimization of treatment-related toxicity and improvement of long-term QoL without compromising regional control. TRIAL REGISTRATION: ClinicalTrails.gov, NCT05145660. Registered December 6, 2021.

Fully automated clinical target volume segmentation for glioblastoma radiotherapy using a deep convolutional neural network.

Purpose: Target volume delineation is a crucial step prior to radiotherapy planning in radiotherapy for glioblastoma. This step is performed manually, which is time-consuming and prone to intra- and inter-rater variabilities. Therefore, the purpose of this study is to evaluate a deep convolutional neural network (CNN) model for automatic segmentation of clinical target volume (CTV) in glioblastoma patients. Material and methods: In this study, the modified Segmentation-Net (SegNet) model with deep supervision and residual-based skip connection mechanism was trained on 259 glioblastoma patients from the Multimodal Brain Tumour Image Segmentation Benchmark (BraTS) 2019 Challenge dataset for segmentation of gross tumour volume (GTV). Then, the pre-trained CNN model was fine-tuned with an independent clinical dataset (n = 37) to perform the CTV segmentation. In the process of fine-tuning, to generate a CT segmentation mask, both CT and MRI scans were simultaneously used as input data. The performance of the CNN model in terms of segmentation accuracy was evaluated on an independent clinical test dataset (n = 15) using the Dice Similarity Coefficient (DSC) and Hausdorff distance. The impact of auto-segmented CTV definition on dosimetry was also analysed. Results: The proposed model achieved the segmentation results with a DSC of 89.60 ± 3.56% and Hausdorff distance of 1.49 ± 0.65 mm. A statistically significant difference was found for the Dmin and Dmax of the CTV between manually and automatically planned doses. Conclusions: The results of our study suggest that our CNN-based auto-contouring system can be used for segmentation of CTVs to facilitate the brain tumour radiotherapy workflow.

Necessity of external iliac lymph nodes and inguinal nodes radiation in rectal cancer with anal canal involvement.

BACKGROUND AND PURPOSE: We aimed to explore the necessity of the external iliac lymph nodes (EIN) along with inguinal nodes (IN) region in clinical target volume (CTV) for rectal carcinomas covering the anal canal region. MATERIALS AND METHODS: This research premise enrolled 399 patients who had primary low rectal cancer detected below the peritoneal reflection via magnetic resonance imaging (MRI) and were treated with neoadjuvant radiotherapy (NRT), without elective EIN along with IN irradiation. We stratified the patients into two groups based on whether the lower edge of the rectal tumor extended to the anal canal (P group, n = 109) or not (Rb group, n = 290). Comparison of overall survival (OS), locoregional recurrence-free survival (LRFS), disease-free survival (DFS), as well as distant metastasis-free survival (DMFS) were performed via inverse probability of treatment weighting (IPTW) along with multivariable analyses. We compared the EIN and IN failure rates between the two groups via the Fisher and Gray's test. RESULTS: P group showed a similar adjusted proportion along with five-year cumulative rate of EIN failure compared with the Rb group. The adjusted proportion and five-year cumulative rate of IN failure in the P group was higher in comparison to the Rb group. There were no remarkable differences in the adjusted five-year OS, DFS, DMFS or LRFS between the two groups. Anal canal involvement (ACI) exhibited no effect on OS, LRFS, DFS, or DMFS. CONCLUSIONS: During NRT for rectal cancer with ACI, it may be possible to exclude the EIN and IN from the CTV.

RefineNet-based 2D and 3D automatic segmentations for clinical target volume and organs at risks for patients with cervical cancer in postoperative radiotherapy.

PURPOSE: An accurate and reliable target volume delineation is critical for the safe and successful radiotherapy. The purpose of this study is to develop new 2D and 3D automatic segmentation models based on RefineNet for clinical target volume (CTV) and organs at risk (OARs) for postoperative cervical cancer based on computed tomography (CT) images. METHODS: A 2D RefineNet and 3D RefineNetPlus3D were adapted and built to automatically segment CTVs and OARs on a total of 44 222 CT slices of 313 patients with stage I-III cervical cancer. Fully convolutional networks (FCNs), U-Net, context encoder network (CE-Net), UNet3D, and ResUNet3D were also trained and tested with randomly divided training and validation sets, respectively. The performances of these automatic segmentation models were evaluated by Dice similarity coefficient (DSC), Jaccard similarity coefficient, and average symmetric surface distance when comparing them with manual segmentations with the test data. RESULTS: The DSC for RefineNet, FCN, U-Net, CE-Net, UNet3D, ResUNet3D, and RefineNet3D were 0.82, 0.80, 0.82, 0.81, 0.80, 0.81, and 0.82 with a mean contouring time of 3.2, 3.4, 8.2, 3.9, 9.8, 11.4, and 6.4 s, respectively. The generated RefineNetPlus3D demonstrated a good performance in the automatic segmentation of bladder, small intestine, rectum, right and left femoral heads with a DSC of 0.97, 0.95, 091, 0.98, and 0.98, respectively, with a mean computation time of 6.6 s. CONCLUSIONS: The newly adapted RefineNet and developed RefineNetPlus3D were promising automatic segmentation models with accurate and clinically acceptable CTV and OARs for cervical cancer patients in postoperative radiotherapy.

Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network.

PURPOSE: Contouring clinical target volume (CTV) from medical images is an essential step for radiotherapy (RT) planning. Magnetic resonance imaging (MRI) is used as a standard imaging modality for CTV segmentation in cervical cancer due to its superior soft-tissue contrast. However, the delineation of CTV is challenging as CTV contains microscopic extensions that are not clearly visible even in MR images, resulting in significant contour variability among radiation oncologists depending on their knowledge and experience. In this study, we propose a fully automated deep learning-based method to segment CTV from MR images. METHODS: Our method begins with the bladder segmentation, from which the CTV position is estimated in the axial view. The superior-inferior CTV span is then detected using an Attention U-Net. A CTV-specific region of interest (ROI) is determined, and three-dimensional (3-D) blocks are extracted from the ROI volume. Finally, a CTV segmentation map is computed using a 3-D U-Net from the extracted 3-D blocks. RESULTS: We developed and evaluated our method using 213 MRI scans obtained from 125 patients (183 for training, 30 for test). Our method achieved (mean ± SD) Dice similarity coefficient of 0.85 ± 0.03 and the 95th percentile Hausdorff distance of 3.70 ± 0.35 mm on test cases, outperforming other state-of-the-art methods significantly (p-value < 0.05). Our method also produces an uncertainty map along with the CTV segmentation by employing the Monte Carlo dropout technique to draw physician's attention to the regions with high uncertainty, where careful review and manual correction may be needed. CONCLUSIONS: Experimental results show that the developed method is accurate, fast, and reproducible for contouring CTV from MRI, demonstrating its potential to assist radiation oncologists in alleviating the burden of tedious contouring for RT planning in cervical cancer.

Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.

OBJECTIVES: Because radiotherapy is indispensible for treating cervical cancer, it is critical to accurately and efficiently delineate the radiation targets. We evaluated a deep learning (DL)-based auto-segmentation algorithm for automatic contouring of clinical target volumes (CTVs) in cervical cancers. METHODS: Computed tomography (CT) datasets from 535 cervical cancers treated with definitive or postoperative radiotherapy were collected. A DL tool based on VB-Net was developed to delineate CTVs of the pelvic lymph drainage area (dCTV1) and parametrial area (dCTV2) in the definitive radiotherapy group. The training/validation/test number is 157/20/23. CTV of the pelvic lymph drainage area (pCTV1) was delineated in the postoperative radiotherapy group. The training/validation/test number is 272/30/33. Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance (HD) were used to evaluate the contouring accuracy. Contouring times were recorded for efficiency comparison. RESULTS: The mean DSC, MSD, and HD values for our DL-based tool were 0.88/1.32 mm/21.60 mm for dCTV1, 0.70/2.42 mm/22.44 mm for dCTV2, and 0.86/1.15 mm/20.78 mm for pCTV1. Only minor modifications were needed for 63.5% of auto-segmentations to meet the clinical requirements. The contouring accuracy of the DL-based tool was comparable to that of senior radiation oncologists and was superior to that of junior/intermediate radiation oncologists. Additionally, DL assistance improved the performance of junior radiation oncologists for dCTV2 and pCTV1 contouring (mean DSC increases: 0.20 for dCTV2, 0.03 for pCTV1; mean contouring time decrease: 9.8 min for dCTV2, 28.9 min for pCTV1). CONCLUSIONS: DL-based auto-segmentation improves CTV contouring accuracy, reduces contouring time, and improves clinical efficiency for treating cervical cancer.

Clinicopathologic analysis of microscopic tumor extension in glioma for external beam radiotherapy planning.

BACKGROUND: There is no consensus regarding the clinical target volume (CTV) margins in radiotherapy for glioma. In this study, we aimed to perform a complete macropathologic analysis examining microscopic tumor extension (ME) to more accurately define the CTV in glioma. METHODS: Thirty-eight supra-total resection specimens of glioma patients were examined on histologic sections. The ME distance, defined as the maximum linear distance from the tumor border to the invasive tumor cells, was measured at each section. We defined the CTV based on the relationships between ME distance and clinicopathologic features. RESULTS: Between February 2016 and July 2020, a total of 814 slides were examined, corresponding to 162 slides for low-grade glioma (LGG) and 652 slides for high-grade glioma (HGG). The ME value was 0.69 ± 0.43 cm for LGG and 1.29 ± 0.54 cm for HGG (P < 0.001). After multivariate analysis, tumor grade, O6-methylguanine-DNA-methyltransferase promoter methylated status (MGMTm), isocitrate dehydrogenase wild-type status (IDHwt), and 1p/19q non-co-deleted status (non-codel) were positively correlated with ME distance (all P < 0.05). We defined the CTV of glioma based on tumor grade. To take into account approximately 95% of the ME, a margin of 1.00 cm, 1.50 cm, and 2.00 cm were chosen for grade II, grade III, and grade IV glioma, respectively. Paired analysis of molecularly defined patients confirmed that tumors that had all three molecular alterations (i.e., MGMTm/IDHwt/non-codel) were the most aggressive subgroups (all P < 0.05). For these patients, the margin could be up to 1.50 cm, 2.00 cm, and 2.50 cm for grade II, grade III, and grade IV glioma, respectively, to cover the subclinical lesions in 95% of cases. CONCLUSIONS: The ME was different between the grades of gliomas. It may be reasonable to recommend 1.00 cm, 1.50 cm, and 2.00 cm CTV margins for grade II, grade III, and grade IV glioma, respectively. Considering the highly aggressive nature of MGMTm/IDHwt/non-codel tumors, for these patients, the margin could be further expanded by 0.5 cm. These recommendations would encompass microscopic disease extension in 95% of cases. TRIAL REGISTRATION: The trial was registered with Chinese Clinical Trial Registry ( ChiCTR2100049376 ).

CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy.

BACKGROUND: It is very important to accurately delineate the CTV on the patient's three-dimensional CT image in the radiotherapy process. Limited to the scarcity of clinical samples and the difficulty of automatic delineation, the research of automatic delineation of cervical cancer CTV based on CT images for new patients is slow. This study aimed to assess the value of Dense-Fully Connected Convolution Network (Dense V-Net) in predicting Clinical Target Volume (CTV) pre-delineation in cervical cancer patients for radiotherapy. METHODS: In this study, we used Dense V-Net, a dense and fully connected convolutional network with suitable feature learning in small samples to automatically pre-delineate the CTV of cervical cancer patients based on computed tomography (CT) images and then we assessed the outcome. The CT data of 133 patients with stage IB and IIA postoperative cervical cancer with a comparable delineation scope was enrolled in this study. One hundred and thirteen patients were randomly designated as the training set to adjust the model parameters. Twenty cases were used as the test set to assess the network performance. The 8 most representative parameters were also used to assess the pre-sketching accuracy from 3 aspects: sketching similarity, sketching offset, and sketching volume difference. RESULTS: The results presented that the DSC, DC/mm, HD/cm, MAD/mm, ∆V, SI, IncI and JD of CTV were 0.82 ± 0.03, 4.28 ± 2.35, 1.86 ± 0.48, 2.52 ± 0.40, 0.09 ± 0.05, 0.84 ± 0.04, 0.80 ± 0.05, and 0.30 ± 0.04, respectively, and the results were greater than those with a single network. CONCLUSIONS: Dense V-Net can correctly predict CTV pre-delineation of cervical cancer patients and can be applied in clinical practice after completing simple modifications.

Dosimetric impact on changes in target volumes during intensity-modulated radiotherapy for nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To assess anatomic changes during intensity modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC) and to determine its dosimetric impact. PATIENTS AND METHODS: Twenty patients treated with IMRT for NPC were enrolled in this study. A second CT was performed at 38 Gy. Manual contouring of the macroscopic tumor volumes (GTV) and the planning target volumes (PTV) were done on the second CT. We recorded the volumes of the different structures, D98 %, the conformity, and the homogeneity indexes for each PTV. Volume percent changes were calculated. RESULTS: We observed a significant reduction in tumor volumes (58.56 % for the GTV N and 29.52 % for the GTV T). It was accompanied by a significant decrease in the D98 % for the 3 PTV (1.4 Gy for PTV H, p = 0.007; 0.3 Gy for PTV I, p = 0.03 and 1.15 Gy for PTV L, p = 0 0.0066). In addition, we observed a significant reduction in the conformity index in the order of 0.02 (p = 0.001) and 0.01 (p = 0.007) for PTV H and PTV I, respectively. The conformity variation was not significant for PTV L. Moreover, results showed a significant increase of the homogeneity index for PTV H (+ 0.03, p = 0.04) and PTV L (+ 0.04, p = 0.01). CONCLUSION: Tumor volume reduction during the IMRT of NPC was accompanied by deterioration of the dosimetric coverage for the different target volumes. It is essential that a careful adaptation of the treatment plan be considered during therapy for selected patients.

Radiotherapy for the treatment of pituitary adenomas: A dosimetric comparison of three planning techniques.

AIM: Our goal was to compare conformal 3D (C3D) radiotherapy (RT), modulated intensity RT (IMRT), and volumetric modulated arc therapy (VMAT) planning techniques in treating pituitary adenomas. BACKGROUND: RT is important for managing pituitary adenomas. Treatment planning advances allow for higher radiation dosing with less risk of affecting organs at risk (OAR). MATERIALS AND METHODS: We conducted a 5-year retrospective review of patients with pituitary adenoma treated with external beam radiation therapy (C3D with flattening filter, flattening filter-free [FFF], IMRT, and VMAT). We compared dose-volume histogram data. For OARs, we recorded D2%, maximum, and mean doses. For planning target volume (PTV), we registered V95%, V107%, D95%, D98%, D50%, D2%, minimum dose, conformity index (CI), and homogeneity index (HI). RESULTS: Fifty-eight patients with pituitary adenoma were included. Target-volume coverage was acceptable for all techniques. The HI values were 0.06, IMRT; 0.07, VMAT; 0.08, C3D; and 0.09, C3D FFF (p < 0.0001). VMAT and IMRT provided the best target volume conformity (CI, 0.64 and 0.74, respectively; p < 0.0001). VMAT yielded the lowest doses to the optic pathway, lens, and cochlea. The position of the neck in extreme flexion showed that it helps in planning mainly with VMAT by allowing only one arc to be used and achieving the desired conformity, decreasing the treatment time, while allowing greater protection to the organs of risk using C3D, C3DFFF. CONCLUSIONS: Our results confirmed that EBRT in pituitary adenomas using IMRT, VMAT, C3D, C3FFF provide adequate coverage to the target. VMAT with a single arc or incomplete arc had a better compliance with desired dosimetric goals, such as target coverage and normal structures dose constraints, as well as shorter treatment time. Neck extreme flexion may have benefits in treatment planning for better preservation of organs at risk. C3D with extreme neck flexion is an appropriate treatment option when other treatment techniques are not available.

Transitioning from conformal radiotherapy to intensity-modulated radiotherapy after radical prostatectomy: Clinical benefit, oncologic outcomes and incidence of gastrointestinal and urinary toxicities.

AIM: The purpose of this study was to review genitourinary (GU) and gastrointestinal (GI) toxicity associated with high-dose radiotherapy (RT) delivered with 3-dimensional conformal radiotherapy (3D-CRT) and intensity-modulated radiotherapy (IMRT) or volumetric arc therapy (VMAT) following radical prostatectomy (RP). BACKGROUND: RP is a therapeutic option for the management of prostate cancer (PrCa). When assessing postoperative RT techniques for PrCa, the published literature focuses on patients treated with 2-dimensional conventional methods without reflecting the implementation of 3D-CRT, IMRT, or VMAT. MATERIALS AND METHODS: A total of 83 patients were included in this analysis; 30 patients received 3D-CRT, and 53 patients received IMRT/VMAT. Acute and late symptoms of the GU and lower GI tract were retrospectively graded according to the Radiation Therapy Oncology Group and the European Organization for Research and Treatment of Cancer radiation toxicity grading systems. The relapse failure-free rate and overall survival were also evaluated. RESULTS: The rate of acute GU toxicity was 9.4% vs. 13.3% for the IMRT/VMAT and 3D-CRT groups (p = 0.583). The 5-year actuarial rates of late GI toxicity for IMRT/VMAT and 3D-CRT treatments were 1.9% and 6.7%, respectively. The rate of late GU toxicity for the IMRT/VMAT and 3D-CRT treatment groups was 7.5% and 16.6%, respectively (p = 0.199). We found no association between acute or late toxicity and the RT technique in univariate and multivariate analyses. CONCLUSION: Postprostatectomy IMRT/VMAT and 3D-CRT achieved similar morbidity and cancer control outcomes. The clinical benefit of highly conformal techniques in this setting is unclear although formal analysis is needed.

[Automated Pre-delineation of CTV in Patients with Cervical Cancer Using Dense V-Net].

We use a dense and fully connected convolutional network with good feature learning in small samples, to automatically pre-deline CTV of cervical cancer patients based on CT images and evaluate the effect. The CT data of stage IB and IIA postoperative cervical cancer with similar delineation scope were selected to be used to evaluate the pre-sketching accuracy from three aspects:sketching similarity, sketching offset and sketching volume difference. It has been proved that the 8 most representative parameters are superior to those with single network and reported internationally before. Dense V-Net can accurately predict CTV pre-delineation of cervical cancer patients, which can be used clinically after simple modification by doctors.

Advantages of using reduced-volume intensity modulated radiation therapy for the treatment of nasopharyngeal carcinoma: a retrospective paired study.

BACKGROUND: The definition of clinical target volume (CTV) in intensity modulated radiation therapy (IMRT) for nasopharyngeal carcinoma (NPC) has not been addressed. We performed this study to assess the feasibility and efficacy of using IMRT with reduced-volume CTV for the treatment of nasopharyngeal carcinoma. METHODS: We retrospectively reviewed 293 non-metastatic NPC patients treated with IMRT from 2002 to 2013. A total of 180 matched cases finally included with 90 received conventional-volume IMRT (CV-IMRT) and 90 received reduced-volume IMRT (RV-IMRT). Kaplan-Meier method and log-rank tests were used to compare NPC-specific survival. Multivariate analyses using the Cox proportional hazards model were conducted to detect independent predictors. RESULTS: With a median follow-up of 70 months, the 3-year overall survival, progression-free survival, distant metastasis-free survival, local recurrence-free survival, regional recurrence-free survival, locoregional recurrence-free survival rates were 88.9, 84.4, 92.2, 91.1, 98.9, 91.1% for the CV-IMRT arm and 92.2, 85.6, 90.0, 93.3, 98.9, 93.3% for the RV-IMRT arm, respectively. None significant survival difference was observed. Additionally, RV-IMRT was associated with reduced risk of late xerostomia (P = 0.039) and hearing loss (P = 0.008), compared versus CV-IMRT. CONCLUSIONS: The use of RV-IMRT for the treatment of NPC led to comparable survival condition and truly reduced toxicity reactions compared versus CV-IMRT.