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Objectives Stereotactic radiotherapy (SRT) for brain metastases (BM) allows very good local control (LC). However, approximately 20%-30% of these lesions will recur. The objective of this retrospective study was to evaluate the impact of dosimetric parameters on LC in cerebral SRT. Methods Patients treated with SRT for 1-3 BM between January 2015 and December 2018 were retrospectively included. A total of 349 patients with 538 lesions were included. The median gross tumour volume (GTV) was 2 cm3 (IQR, 0-7). The median biological effective dose with α/β = 10 (BED10) was 60 Gy (IQR, 32-82). The median prescription isodose was 71% (IQR, 70-80). Correlations with LC were examined using the Cox regression model. Results The median follow-up period was 55 months (min-max, 7-85). Median overall survival was 17.8 months (IQR, 15.2-21.9). There were 95 recurrences and LC at 1 and 2 years was 87.1% (95% CI, 84-90) and 78.1% (95% CI, 73.9-82.4), respectively. Univariate analysis showed that systemic treatment, dose to 2% and 50% of the planning target volume (PTV), BED10 > 50 Gy, and low PTV and GTV volume were significantly correlated with better LC. In the multivariate analysis, GTV volume, isodose, and BED10 were significantly associated with LC. Conclusion These results show the importance of a BED10 > 50 Gy associated with a prescription isodose <80% to optimize LC during SRT for BM. Advances in knowledge Isodose, BED, and GTV volume were significantly associated with LC. A low isodose improves LC without increasing the risk of radionecrosis. [ABSTRACT FROM AUTHOR]

Purpose: To develop a radiomic model predicting nonresponse to induction chemotherapy in laryngeal cancers, from multicenter pretherapeutic contrast‐enhanced computed tomography (CE‐CT) and evaluate the benefit of feature harmonization in such a context. Methods: Patients (n = 104) eligible for laryngeal preservation chemotherapy were included in five centers. Primary tumor was manually delineated on the CE‐CT images. The following radiomic features were extracted with an in‐house software (MIRAS v1.1, LaTIM UMR 1101): intensity, shape, and textural features derived from Gray‐Level Co‐occurrence Matrix (GLCM), Neighborhood Gray Tone Difference Matrix (NGTDM), Gray‐Level Run Length Matrix (GLRLM), and Gray‐Level Size Zone Matrix (GLSZM). Harmonization was performed using ComBat after unsupervised hierarchical clustering, used to determine labels automatically, given the high heterogeneity of imaging characteristics across and within centers. Patients with similar feature distributions were grouped with unsupervised clustering into an optimal number of clusters (2) determined with "silhouette scoring." Statistical harmonization was then carried out with ComBat on these 2 identified clusters. The cohort was split into training/validation (n = 66) and testing (n = 32) sets. Area under the receiver operating characteristics curves (AUC) were used to evaluate the ability of radiomic features (before and after harmonization) to predict nonresponse to chemotherapy, and specificity (Sp) and sensitivity (Se) were used to quantify their performance in the testing set. Results: Without harmonization, none of the features identified as predictive in the training set remained significant in the testing set. After ComBat, one textural feature identified in the training set keeps a predictive trend in the testing set—Zone Percentage, derived from the GLSZM, was predictive of nonresponse in the training set (AUC = 0.62, Se = 70%, Sp = 64%, P = 0.04) and obtained a satisfactory performance in the testing set (Se = 80%, Sp = 67%, P = 0.03), although significance was limited by the size of the testing set. These results are consistent with previously published findings in head and neck cancers. Conclusions: Radiomic features from CE‐CT could help in the selection of patients for induction chemotherapy in laryngeal cancers, with relatively good sensitivity and specificity in predicting lack of response. Statistical harmonization with ComBat and unsupervised clustering seems to improve the predictive value of features extracted in such a heterogeneous multicenter setting. [ABSTRACT FROM AUTHOR]

External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over five weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organ-at-risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient’s modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library, showing an improvement in both target coverage and OAR sparing. [ABSTRACT FROM AUTHOR]

Objectives: No study has reported clinical results of external-beam radiotherapy specifically for T3b prostate cancer. The possibility of escalating the dose to the involved seminal vesicles (ISV) while respecting the dose constraints in the organs at risk is thus so far not clearly demonstrated. The objective of the study was to analyze the dose distribution and the clinical outcome in a large series of patients who received IMRT for T3b prostate cancer. Materials and methods: This retrospective analysis included all patients who received IMRT and androgen deprivation therapy for T3b prostate cancer, between 2008 and 2017, in six French institutions, with available MRI images and dosimetric data. Results: A total of 276 T3b patients were included. The median follow-up was 26 months. The median (range) prescribed doses (Gy) to the prostate and to the ISV were 77 (70–80) and 76 (46–80), respectively. The dose constraint recommendations were exceeded in less than 12% of patients for the rectum and the bladder. The 5-year risks of biochemical and clinical recurrences and cancer-specific death were 24.8%, 21.7%, and 10.3%, respectively. The 5-year risks of local, pelvic lymph node, and metastatic recurrences were 6.4%, 11.3%, and 15%, respectively. The number of involved lymph nodes (≤ 2 or ≥ 3) on MRI was the only significant prognostic factor in clinical recurrence (HR 9.86) and death (HR 2.78). Grade ≥ 2 acute and 5-year late toxicity rates were 13.2% and 12% for digestive toxicity, and 34% and 31.5% for urinary toxicity, respectively. The dose to the pelvic lymph node and the age were predictive of late digestive toxicity. Conclusion: IMRT for T3b prostate cancer allows delivery of a curative dose in the ISV, with a moderate digestive toxicity but a higher urinary toxicity. Lymph node involvement increases the risk of recurrence and death. [ABSTRACT FROM AUTHOR]

Background: To assess the benefits of bladder wall sub-volume equivalent uniform dose (EUD) constraints in prostate cancer intensity-modulated radiotherapy (IMRT) planning. Methods: Two IMRT plans, with and without EUD constraints on the bladder wall, were generated using beams that deliver 80 Gy to the prostate and 46 Gy to the seminal vesicles and were compared in 53 prostate cancer patients. The bladder wall was defined as the volume between the external manually delineated wall and a contraction of 7 mm apart from it. The bladder wall was then separated into two parts: the internal-bladder wall (bla-in) represented by the portion of the bladder wall that intersected with the planning target volume (PTV) plus 5 mm extension; the external-bladder wall (bla-ex) represented by the remaining part of the bladder wall. In the IMRT plan with EUD constraints, the values of "a" parameter for the EUD models were 10.0 for bla-in and 2.3 for bla-ex. The plans with and without EUD constraints were compared in terms of dose-volume histograms, 5-year bladder and rectum normal tissue complication probability values, as well as tumor control probability (TCP) values. Results: The use of bladder sub-volume EUD constraints decreased both the doses to the bladder wall (V70: 22.76% vs 19.65%, Dmean: 39.82 Gy vs 35.45 Gy) and the 5-year bladder complication probabilities ($LENT/SOMA Grade 2: 20.35% vs 17.96%; bladder bleeding: 10.63% vs 8.64%). The doses to the rectum wall and the rectum complication probabilities were also slightly decreased by the EUD constraints compared to physical constraints only. The minimal dose and the V76Gy of PTVprostate were, however, slightly decreased by EUD optimization, nevertheless without significant difference in TCP values between the two plans, and the PTV parameters finally respected the Groupe d'Etude des Tumeurs Uro-Génitales recommendations. Conclusion: Separating the bladder wall into two parts with appropriate EUD optimization may reduce bladder toxicity in prostate IMRT. Combining biological constraints with physical constraints in the organs at risk at the inverse planning step of IMRT may improve the dose distribution. [ABSTRACT FROM AUTHOR]

Background Large anatomical variations occur during the course of intensity-modulated radiation therapy (IMRT) for locally advanced head and neck cancer (LAHNC). The risks are therefore a parotid glands (PG) overdose and a xerostomia increase. The purposes of the study were to estimate: - the PG overdose and the xerostomia risk increase during a "standard" IMRT (IMRTstd); - the benefits of an adaptive IMRT (ART) with weekly replanning to spare the PGs and limit the risk of xerostomia. Material and methods Fifteen patients received radical IMRT (70Gy) for LAHNC. Weekly CTs were used to estimate the dose distributions delivered during the treatment, corresponding either to the initial planning (IMRTstd) or to weekly replanning (ART). PGs dose were recalculated at the fraction, from the weekly CTs. PG cumulated doses were then estimated using deformable image registration. The following PG doses were compared: pre-treatment planned dose, per-reatment IMRTstd and ART. The corresponding estimated risks of xerostomia were also compared. Correlations between anatomical markers and dose differences were searched. Results Compared to the initial planning, a PG overdose was observed during IMRTstd for 59% of the PGs, with an average increase of 3.7Gy (10.0Gy maximum) for the mean dose, and of 8.2% (23.9% maximum) for the risk of xerostomia. Compared to the initial planning, weekly replanning reduced the PG mean dose for all the patients (p < 0.05). In the overirradiated PG group, weekly replanning reduced the mean dose by 5.1Gy (12.2Gy maximum) and the absolute risk of xerostomia by 11% (p < 0.01) (30% maximum). The PG overdose and the dosimetric benefit of replanning increased with the tumor shrinkage and the neck thickness reduction (p < 0.001). Conclusion During the course of LAHNC IMRT, around 60% of the PGs are overdosed of 4Gy. Weekly replanning decreased the PG mean dose by 5Gy, and therefore by 11% the xerostomia risk. [ABSTRACT FROM AUTHOR]

• The paper describes the first challenge on head and neck tumor segmentation in PET/CT. • Training (n = 201 , 4 centers) and test sets (n = 53 , 1 unseen center) amount to 254 cases. • All ground truth segmentations underwent cleaning to ensure quality and homogeneity. • The winning team obtained a DSC of 0.759, showing a larg improvement over the baseline. • Additional post-challenge analyses (e.g. false positives analysis, ranking stability). [Display omitted] This paper relates the post-analysis of the first edition of the HEad and neCK TumOR (HECKTOR) challenge. This challenge was held as a satellite event of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2020, and was the first of its kind focusing on lesion segmentation in combined FDG-PET and CT image modalities. The challenge's task is the automatic segmentation of the Gross Tumor Volume (GTV) of Head and Neck (H&N) oropharyngeal primary tumors in FDG-PET/CT images. To this end, the participants were given a training set of 201 cases from four different centers and their methods were tested on a held-out set of 53 cases from a fifth center. The methods were ranked according to the Dice Score Coefficient (DSC) averaged across all test cases. An additional inter-observer agreement study was organized to assess the difficulty of the task from a human perspective. 64 teams registered to the challenge, among which 10 provided a paper detailing their approach. The best method obtained an average DSC of 0.7591, showing a large improvement over our proposed baseline method and the inter-observer agreement, associated with DSCs of 0.6610 and 0.61, respectively. The automatic methods proved to successfully leverage the wealth of metabolic and structural properties of combined PET and CT modalities, significantly outperforming human inter-observer agreement level, semi-automatic thresholding based on PET images as well as other single modality-based methods. This promising performance is one step forward towards large-scale radiomics studies in H&N cancer, obviating the need for error-prone and time-consuming manual delineation of GTVs. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H&N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H&N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient ( DSC agg ) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2., Competing Interests: No conflict of interest applies. Fundings are specified in the acknowledgments. Only the organizers had access to the test cases’ ground truth contours.

The aims of this multicenter study were to identify clinical and preoperative PET/CT parameters predicting overall survival (OS) and distant metastasis-free survival (DMFS) in a cohort of head and neck squamous cell carcinoma patients treated with surgery, to generate a prognostic model of OS and DMFS, and to validate this prognostic model with an independent cohort. Methods: A total of 382 consecutive patients with head and neck squamous cell carcinoma, divided into training ( n  = 318) and validation ( n  = 64) cohorts, were retrospectively included. The following PET/CT parameters were analyzed: clinical parameters, SUV max , SUV mean , metabolic tumor volume (MTV), total lesion glycolysis, and distance parameters for the primary tumor and lymph nodes defined by 2 segmentation methods (relative SUV max threshold and absolute SUV threshold). Cox analyses were performed for OS and DMFS in the training cohort. The concordance index (c-index) was used to identify highly prognostic parameters. These prognostic parameters were externally tested in the validation cohort. Results: In multivariable analysis, the significant parameters for OS were T stage and nodal MTV, with a c-index of 0.64 ( P  < 0.001). For DMFS, the significant parameters were T stage, nodal MTV, and maximal tumor-node distance, with a c-index of 0.76 ( P  < 0.001). These combinations of parameters were externally validated, with c-indices of 0.63 ( P  < 0.001) and 0.71 ( P  < 0.001) for OS and DMFS, respectively. Conclusion: The nodal MTV associated with the maximal tumor-node distance was significantly correlated with the risk of DMFS. Moreover, this parameter, in addition to clinical parameters, was associated with a higher risk of death. These prognostic factors may be used to tailor individualized treatment., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

The prediction of cancer characteristics, treatment planning and patient outcome from medical images generally requires tumor delineation. In Head and Neck cancer (H&N), the automatic segmentation and differentiation of primary Gross Tumor Volumes (GTVt) and malignant lymph nodes (GTVn) is a necessary step for large-scale radiomics studies to predict patient outcome such as Progression Free Survival (PFS). Detecting malignant lymph nodes is also a crucial step for Tumor-Node-Metastases (TNM) staging and to support the decision to resect the nodes. In turn, automatic TNM staging and patient outcome prediction can greatly benefit patient care by helping clinicians to find the best personalized treatment. We propose the first model to automatically individually segment GTVt and GTVn in PET/CT images. A bi-modal 3D U-Net model is trained for multi-class and multi-components segmentation on the multi-centric HECKTOR 2020 dataset containing 254 cases. The dataset has been specifically re-annotated by experts to obtain ground truth GTVn contours. The results show promising segmentation performance for the automation of radiomics pipelines and their validation on large-scale studies for which manual annotations are not available. An average test Dice Similarity Coefficients (DSC) of 0.717 is obtained for the segmentation of GTVt. The GTVn segmentation is evaluated with an aggregated DSC to account for the cases without GTVn, which is estimated at 0.729 on the test set.

Hepatocellular carcinoma (HCC) is the sixth more frequent cancer worldwide. This type of cancer has a poor overall survival rate mainly due to underlying cirrhosis and risk of recurrence outside the treated lesion. Quantitative imaging within a radiomics workflow may help assessing the probability of survival and potentially may allow tailoring personalized treatments. In radiomics a large amount of features can be extracted, which may be correlated across a population and very often can be surrogates of the same physiopathology. This issues are more pronounced and difficult to tackle with imbalanced data. Feature selection strategies are therefore required to extract the most informative with the increased predictive capabilities. In this paper, we compared different unsupervised and supervised strategies for feature selection in presence of imbalanced data and optimize them within a machine learning framework. Multi-parametric Magnetic Resonance Images from 81 individuals (19 deceased) treated with stereotactic body radiation therapy (SBRT) for inoperable (HCC) were analyzed. Pre-selection of a reduced set of features based on Affinity Propagation clustering (non supervised) achieved a significant improvement in AUC compared to other approaches with and without feature pre-selection. By including the synthetic minority over-sampling technique (SMOTE) for imbalanced data and Random Forest classification this workflow emerges as an appealing feature selection strategy for survival prediction within radiomics studies.

Importance: Head and neck squamous cell cancer (HNSCC) represents the seventh most frequent cancer worldwide. More than half of the patients diagnosed with HNSCC are treated with primary surgery., Objective: To report the available evidence on the value of quantitative parameters of fluorodeoxyglucose F 18-labeled positron emission tomography and computed tomography (FDG-PET/CT) performed before surgical treatment of HNSCC to estimate overall survival (OS), disease-free survival (DFS), and distant metastasis (DM) and to discuss their limitations., Evidence Review: A systematic review of the English-language literature in PubMed/MEDLINE and ScienceDirect published between January 2003 and February 15, 2019, was performed between March 1 and July 27, 2019, to identify articles addressing the association between preoperative FDG-PET/CT parameters and oncological outcomes among patients with HNSCC. Articles included those that addressed the following: (1) cancer of the oral cavity, oropharynx, hypopharynx, or larynx; (2) surgically treated (primary or for salvage); (3) pretreatment FDG-PET/CT; (4) quantitative or semiquantitative evaluation of the FDG-PET/CT parameters; and (5) the association between the value of FDG-PET/CT parameters and clinical outcomes. Quality assessment was performed using the Oxford Centre for Evidence-Based Medicine level of evidence., Findings: A total of 128 studies were retrieved from the databases, and 36 studies met the inclusion criteria; these studies comprised 3585 unique patients with a median follow-up of 30.6 months (range, 16-53 months). Of these 36 studies, 32 showed an association between at least 1 FDG-PET/CT parameter and oncological outcomes (OS, DFS, and DM). The FDG-PET/CT volumetric parameters (metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) were independent prognostic factors in most of the data, with a higher prognostic value than the maximum standard uptake value (SUVmax). For example, in univariate analysis of OS, the SUVmax was correlated with OS in 5 of 11 studies, MTV in 11 of 12 studies, and TLG in 6 of 9 studies. The spatial distribution of metabolism via textural indices seemed promising, although that factor is currently poorly evaluated: only 3 studies analyzed data from radiomics indices., Conclusions and Relevance: The findings of this study suggest that the prognostic effectiveness of FDG-PET/CT parameters as biomarkers of OS, DFS, and DM among patients with HNSCC treated with surgery may be valuable. The volumetric parameters (MTV and TLG) seemed relevant for identifying patients with a higher risk of postsurgical disease progression who could receive early therapeutic intervention to improve their prognosis. However, further large-scale studies including exclusively surgery-treated patients stratified according to localization and further analysis of the textural indices are required to define a reliable FDG-PET/CT-based prognostic model of mortality and recurrence risk for these patients.

Background: To assess the benefits of bladder wall sub-volume equivalent uniform dose (EUD) constraints in prostate cancer intensity-modulated radiotherapy (IMRT) planning., Methods: Two IMRT plans, with and without EUD constraints on the bladder wall, were generated using beams that deliver 80 Gy to the prostate and 46 Gy to the seminal vesicles and were compared in 53 prostate cancer patients. The bladder wall was defined as the volume between the external manually delineated wall and a contraction of 7 mm apart from it. The bladder wall was then separated into two parts: the internal-bladder wall (bla-in) represented by the portion of the bladder wall that intersected with the planning target volume (PTV) plus 5 mm extension; the external-bladder wall (bla-ex) represented by the remaining part of the bladder wall. In the IMRT plan with EUD constraints, the values of " a " parameter for the EUD models were 10.0 for bla-in and 2.3 for bla-ex. The plans with and without EUD constraints were compared in terms of dose-volume histograms, 5-year bladder and rectum normal tissue complication probability values, as well as tumor control probability (TCP) values., Results: The use of bladder sub-volume EUD constraints decreased both the doses to the bladder wall ( V 70 : 22.76% vs 19.65%, D mean : 39.82 Gy vs 35.45 Gy) and the 5-year bladder complication probabilities (≥LENT/SOMA Grade 2: 20.35% vs 17.96%; bladder bleeding: 10.63% vs 8.64%). The doses to the rectum wall and the rectum complication probabilities were also slightly decreased by the EUD constraints compared to physical constraints only. The minimal dose and the V 76Gy of PTV prostate were, however, slightly decreased by EUD optimization, nevertheless without significant difference in TCP values between the two plans, and the PTV parameters finally respected the Groupe d'Etude des Tumeurs Uro-Génitales recommendations., Conclusion: Separating the bladder wall into two parts with appropriate EUD optimization may reduce bladder toxicity in prostate IMRT. Combining biological constraints with physical constraints in the organs at risk at the inverse planning step of IMRT may improve the dose distribution., Competing Interests: The authors report no conflicts of interest in this work.

Objective: For para- and intraspinal tumors, precise spinal cord delineation is critical for CyberKnife (Accuray, Inc., Sunnyvale, CA) stereotactic radiotherapy. We evaluated whether computed tomographic (CT) myelography is superior to magnetic resonance imaging (MRI) for accurate spinal cord delineation. Treatment parameters and short-term outcome and toxicity are also presented., Methods: The planning CT scan, the gadolinium-enhanced, T1-weighted, 3-dimensional (3D) fast imaging employing steady-state acquisition MRI scan, and the CT myelogram were fused before volume-of-interest delineation. The planning target volume margin was less than 1 mm using the Xsight Spine tracking system (Accuray). We present data from 11 heavily pretreated patients who underwent CyberKnife stereotactic radiosurgery between November 2006 and January 2008., Results: Spatial resolution was 0.46 and 0.93 mm/pixel for CT myelography and 3D-fast imaging employing steady-state acquisition MRI, respectively. The contrast between cerebrospinal fluid and spinal cord was excellent with CT myelography. A transient postmyelography headache occurred in 1 patient. The mean gross tumor volume was 51.1 mL. The mean prescribed dose was 34 Gy in 4 fractions (range, 2-7 fractions) with 147 beams (range, 79-232 beams) to the 75% reference isodose line (range, 68-80%), covering 95% (range, 86-99%) of the gross tumor volume with a mean conformity index of 1.4 (range, 1.1-1.8). No short-term toxicity on the spinal cord was noted at 1- to 6-months of follow-up., Conclusion: CT myelography was more accurate for spinal cord delineation than 3D-fast imaging employing steady-state acquisition MRI (used for its myelographic effect), particularly in the presence of ferromagnetic artifacts in heavily pretreated patients or in patients with severe spinal compression. Because other MRI sequences (T2 and gadolinium-enhanced T1) provide excellent tumor characterization, we suggest trimodality imaging for spinal tumor treatment to yield submillimetric delineation accuracy. Combined with CyberKnife technology, CT myelography can improve the feasibility of dose escalation or reirradiation of spinal tumors in selected patients, thereby increasing local control while avoiding myelopathy. Further follow-up and prospective studies are warranted.