Radiomics-based prognosis classification for high-risk prostate cancer treated with radiotherapy.

OBJECTIVE: The present study aimed to investigate if CT-based radiomics features could correlate to the risk of metastatic progression in high-risk prostate cancer patients treated with radical RT and long-term androgen deprivation therapy (ADT). MATERIALS AND METHODS: A total of 157 patients were investigated and radiomics features extracted from the contrast-free treatment planning CT series. Three volumes were segmented: the prostate gland only (CTV_p), the prostate gland with seminal vesicles (CTV_psv), and the seminal vesicles only (CTV_sv). The patients were split into two subgroups of 100 and 57 patients for training and validation. Five clinical and 62 radiomics features were included in the analysis. Considering metastases-free survival (MFS) as an endpoint, the predictive model was used to identify the subgroups with favorable or unfavorable prognoses (separated by a threshold selected according to the Youden method). Pure clinical, pure radiomic, and combined predictive models were investigated. RESULTS: With a median follow-up of 30.7 months, the MFS at 1 and 3 years was 97.2% ± 1.5 and 92.1% ± 2.0, respectively. Univariate analysis identified seven potential predictors for MFS in the CTV_p group, 11 in the CTV_psv group, and 9 in the CTV_sv group. After elastic net reduction, these were 4 predictors for MFS in the CTV_p group (positive lymph nodes, Gleason score, H_Skewness, and NGLDM_Contrast), 5 in the CTV_psv group (positive lymph nodes, Gleason score, H_Skewnesss, Shape_Surface, and NGLDM_Contrast), and 6 in the CTV_sv group (positive lymph nodes, Gleason score, H_Kurtosis, GLCM_Correlation, GLRLM_LRHGE, and GLZLM_SZLGE). The patients' group of the training and validation cohorts were stratified into favorable and unfavorable prognosis subgroups. For the combined model, for CTV_p, the mean MFS was 134 ± 14.5 vs. 96.9 ± 22.2 months for the favorable and unfavorable subgroups, respectively, and 136.5 ± 14.6 vs. 70.5 ± 4.3 months for CTV_psv and 150.0 ± 4.2 vs. 91.1 ± 8.6 months for CTV_sv, respectively. CONCLUSION: Radiomic features were able to predict the risk of metastatic progression in high-risk prostate cancer. Combining the radiomic features and clinical characteristics can classify high-risk patients into favorable and unfavorable prognostic groups.

Volumetric modulated arc therapy versus intensity-modulated proton therapy in the irradiation of infra diaphragmatic Hodgkin Lymphoma in female patients.

PURPOSE: To investigate the role of infra diaphragmatic intensity-modulated proton therapy (IMPT) compared to volumetric modulated arc therapy (VMAT) for female Hodgkin Lymphoma (HL) patients and to estimate the risk of secondary cancer and ovarian failure. METHODS: A comparative treatment planning study was performed on 14 patients, and the results were compared according to conventional dose-volume metrics. In addition, estimates of the excess absolute risk (EAR) of secondary cancer induction were determined for the bowel, the bladder and the rectum. For the ovaries, the risk of ovarian failure was estimated. RESULTS: The dosimetric findings demonstrate the equivalence between VMAT and IMPT in terms of target coverage. A statistically significant reduction of the mean and near-to-maximum doses was proven for the organs at risk. The EAR ratio estimated for IMPT to VMAT was 0.51 ± 0.32, 0.32 ± 0.35 and 0.05 ± 0.11 for the bowel, bladder and rectum, respectively. Concerning the risk of ovarian failure for the chronologic age ranging from 18 to 46 years, the expected net loss in fertility years ranged from 4.8 to 3.0 years for protons and 12.0 to 5.7 years for photons. CONCLUSION: This in-silico study confirmed the beneficial role of IMPT from a dosimetric point of view. Mathematical models suggested that the use of protons might be further advantageous due to the expected reduction of the risk of secondary cancer induction and its milder impact on the reduction of fertility.

PET/CT radiomics in breast cancer: Mind the step.

The aim of the present review was to assess the current status of positron emission tomography/computed tomography (PET/CT) radiomics research in breast cancer, and in particular to analyze the strengths and weaknesses of the published papers in order to identify challenges and suggest possible solutions and future research directions. Various combinations of the terms "breast", "radiomic", "PET", "radiomics", "texture", and "textural" were used for the literature search, extended until 8 July 2019, within the PubMed/MEDLINE database. Twenty-six articles fulfilling the inclusion/exclusion criteria were retrieved in full text and analyzed. The studies had technical and clinical objectives, including diagnosis, biological characterization (correlation with histology, molecular subtypes and IHC marker expression), prediction of response to neoadjuvant chemotherapy, staging, and outcome prediction. We reviewed and discussed the selected investigations following the radiomics workflow steps related to the clinical, technical, analysis, and reporting issues. Most of the current evidence on the clinical role of PET/CT radiomics in breast cancer is at the feasibility level. Harmonized methods in image acquisition, post-processing and features calculation, predictive models and classifiers trained and validated on sufficiently representative datasets, adherence to consensus guidelines, and transparent reporting will give validity and generalizability to the results.

The role of a knowledge based dose-volume histogram predictive model in the optimisation of intensity-modulated proton plans for hepatocellular carcinoma patients : Training and validation of a novel commercial system.

PURPOSE: To investigate the performance of a knowledge-based RapidPlan, for optimisation of intensity-modulated proton therapy (IMPT) plans applied to hepatocellular cancer (HCC) patients. METHODS: A cohort of 65 patients was retrospectively selected: 50 were used to "train" the model, while the remaining 15 provided independent validation. The performance of the RapidPlan model was benchmarked against manual optimisation and was also compared to volumetric modulated arc therapy (RapidArc) photon plans. A subanalysis appraised the performance of the RapidPlan model applied to patients with lesions ≤300 cm3 or larger. Quantitative assessment was based on several metrics derived from the constraints of the NRG-GI003 clinical trial. RESULTS: There was an equivalence between manual plans and RapidPlan-optimised IMPT plans, which outperformed the RapidArc plans. The planning dose-volume objectives were met on average for all structures except for D0.5 cm3 ≤30 Gy in the bowels. Limiting the results to the class-solution proton plans (all values in Gy), the data for manual plans vs RapidPlan-based IMPT plans, respectively, showed the following: D99% to the target of 47.5 ± 1.4 vs 47.2 ± 1.2; for organs at risk, the mean dose to the healthy liver was 6.7 ± 3.6 vs 6.7 ± 3.7; the mean dose to the kidneys was 0.2 ± 0.5 vs 0.1 ± 0.2; D0.5 cm3 for the bowels was 33.4 ± 16.4 vs 30.2 ± 16.0; for the stomach was 17.9 ± 19.9 vs 14.9 ± 18.8; for the oesophagus was 17.9 ± 15.1 vs 14.9 ± 13.9; for the spinal cord was 0.5 ± 1.6 vs 0.2 ± 0.7. The model performed similarly for cases with small or large lesions. CONCLUSION: A knowledge-based RapidPlan model was trained and validated for IMPT. The results demonstrate that RapidPlan can be trained adequately for IMPT in HCC. The quality of the RapidPlan-based plans is at least equivalent compared to what is achievable with manual planning. RapidPlan also confirmed the potential to optimise the quality of the proton therapy results, thus reducing the impact of operator planning skills on patient results.

Dose coverage impacts local control in ultra-central lung oligometastases treated with stereotactic radiotherapy.

INTRODUCTION: The use of Stereotactic Body Radiotherapy (SBRT) is controversial in Ultra-Central lung tumors, a subset of central lung tumors characterized by proximity to critical mediastinal structures. This is of interest in oligometastatic (≤3 metastases) patients, who can yield survival benefit from local treatments. The aim of our study is to assess the determinants of efficacy and toxicity in this setting. MATERIALS AND METHODS: Clinical and dosimetric parameters were reviewed in a cohort of oligometastatic patients treated with SBRT for ultra-central tumors. Local control rate (LC) and toxicity were assessed. Statistical Analysis was carried out to assess the impact of those predictors on local recurrence and adverse events. RESULTS: One-hundred-nine consecutive patients were included. A median Biologic Effective Dose (BED) of 105 (75-132) Gy10 was prescribed. At a median follow-up of 17 (range 3-78) months, 2-year LC was 87%. Improved LC was correlated to Planning Treatment Volume (PTV) covered by 95% of the prescription dose (V95% PTV) > 85% (HR 0.15, 95%CI 0.05-0.49, p = 0.0017) and to Gross Tumor Volume (GTV) < 90 cm3 (HR 0.2, 95%CI 0.07-0.56, p = 0.0021). Overall and grade ≥ 3 toxicity incidence was 20% and 5%, respectively. Patients experiencing acute and late toxicities received significantly higher dose to 1 cm3 (D1cm3) of esophagus and lung volume receiving ≥5 Gy (V5Gy) (p = 0.016 and p = 0.013), and higher dose to 0.1 cm3 (D0.1cm3) of heart (p = 0.036), respectively. CONCLUSION: V95% PTV > 85% and GTV < 90 cm3 are independent predictors of LC. Dose to esophagus, lung and heart should be carefully assessed to minimize treatment-related toxicities.

Knowledge-based intensity-modulated proton planning for gastroesophageal carcinoma.

PURPOSE: To investigate the performance of a narrow-scope knowledge-based RapidPlan (RP) model, for optimisation of intensity-modulated proton therapy (IMPT) plans applied to patients with locally advanced carcinoma in the gastroesophageal junction. METHODS: A cohort of 60 patients was retrospectively selected; 45 were used to 'train' a dose-volume histogram predictive model; the remaining 15 provided independent validation. The performance of the RP model was benchmarked against manual optimisation. Quantitative assessment was based on several dose-volume metrics. RESULTS: Manual and RP-optimised IMPT plans resulted dosimetrically similar, and the planning dose-volume objectives were met for all structures. Concerning the validation set, the comparison of the manual vs RP-based plans, respectively, showed for the target (PTV): the homogeneity index was 6.3 ± 2.2 vs 5.9 ± 1.2, and V98% was 89.3 ± 2.9 vs 91.4 ± 2.2% (this was 97.2 ± 1.9 vs 98.8 ± 1.1 for the CTV). Regarding the organs at risk, no significant differences were reported for the combined lungs, the whole heart, the left anterior descending artery, the kidneys, the spleen and the spinal canal. The D0.1 cm3 for the left ventricle resulted in 40.3 ± 3.4 vs 39.7 ± 4.3 Gy(RBE). The mean dose to the liver was 3.4 ± 1.3 vs 3.6 ± 1.5 Gy(RBE). CONCLUSION: A narrow-scope knowledge-based RP model was trained and validated for IMPT delivery in locally advanced cancer of the gastroesophageal junction. The results demonstrate that RP can create models for effective IMPT. Furthermore, the equivalence between manual interactive and unattended RP-based optimisation could be displayed. The data also showed a high correlation between predicted and achieved doses in support of the valuable predictive power of the RP method.

Dosimetric impact of volumetric modulated arc therapy for nasopharyngeal cancer treatment.

BACKGROUND: The purpose of the study was to evaluate the toxicity and outcome of nasopharyngeal carcinoma patients treated using 3-dimensional conformal radiotherapy (3DCRT) or volumetric modulated arc therapy (VMAT) technique. MATERIALS AND METHODS: 68 patients treated between 2006 and 2018 were retrospectively analysed. Since 2009 patients received 3DCRT with 50/70 Gy to the elective/boost volumes in 35 fractions; from then, VMAT with simultaneous integrated boost (SIB) with 54.45/69.96 Gy in 33, or 54/66 Gy in 30 fractions. Induction chemotherapy was administered in 74% of the patients, concomitant cisplatinum in 87%. Acute and late toxicity data, progression-free survival PSF and overall survival OS, and toxicity correlations with dose metrics were reported. RESULTS: With a median follow-up of 64 months, complete remission at the last evaluation was in 68% of the patients, while 28% and 9% had locoregional relapse and distant disease, respectively. The 5- and 10-year progression free survival (PFS) rates were 62.7 ± 6.5% and 53.2 ± 8.7%, respectively. The 5- and 10-year OS rates were 78.9 ± 5.5% and 61.4 ± 9.2%, respectively. At the multivariate Cox analysis TNM stage (p = 0.02) and concomitant chemotherapy (p = 0.01) resulted significant for PFS, concomitant chemotherapy (p = 0.04) for OS.Improvements in acute toxicity were presented for VMAT patients due to its ability to spare OARs. Odds ratio (OR) for acute salivary toxicity, between VMAT and 3DCRT, was 4.67 (p = 0.02). Dosimetrically, salivary toxicity correlated with mean parotid dose (p = 0.05), dysphagia with laryngeal (p = 0.04) and mean oral cavity (p = 0.06) doses, when dose-volume histograms (DVHs) are corrected for fractionation. CONCLUSION: This study is a proof of a significant benefit of the VMAT technique compared with 3DCRT in terms of side effects in nasopharynx patients, and adds dosimetric correlations.

A radiomic approach to predicting nodal relapse and disease-specific survival in patients treated with stereotactic body radiation therapy for early-stage non-small cell lung cancer.

PURPOSE: To describe the possibility of building a classifier for patients at risk of lymph node relapse and a predictive model for disease-specific survival in patients with early stage non-small cell lung cancer. METHODS: A cohort of 102 patients who received stereotactic body radiation treatment was retrospectively investigated. A set of 45 textural features was computed for the tumor volumes on the treatment planning CT images. Patients were split into two independent cohorts (70 patients, 68.9%, for training; and 32 patients, 31.4%, for validation). Three different models were built in the study. A stepwise backward linear discriminant analysis was applied to identify patients at risk of lymph node progression. The performance of the model was assessed by means of standard metrics derived from the confusion matrix. Furthermore, all textural features were correlated to survival data to build two separate predictive models for progression-free survival (PFS) and disease-specific survival (DS-OS). These models were built from the features/predictors found significant in univariate analysis and elastic net regularization by means of a multivarate Cox regression with backward selection. Low- and high-risk groups were identified by maximizing the separation by means of the Youden method. RESULTS: In the total cohort (77, 75.5%, males; and 25, 24.5%, females; median age 76.6 years), 15 patients presented nodal progression at the time of analysis; 19 patients (18.6%) died because of disease-specific causes, 25 (24.5%) died from other reasons, 28 (27.5%) were alive without disease, and 30 (29.4%) with either local or distant progression. The specificity, sensitivity, and accuracy of the classifier resulted 83.1 ± 24.5, 87.4 ± 1.2, and 85.4 ± 12.5 in the validation group (coherent with the findings in the training). The area under the curve for the classifier resulted in 0.84 ± 0.04 and 0.73 ± 0.05 for training and validation, respectively. The mean time for DS-OS and PFS for the low- and high-risk subgroups of patients (in the validation groups) were 88.2 month ± 9.0 month vs. 84.1 month ± 7.8 month (low risk) and 52.7 month ± 5.9 month vs. 44.6 month ± 9.2 month (high risk), respectively. CONCLUSION: Radiomics analysis based on planning CT images allowed a classifier and predictive models capable of identifying patients at risk of nodal relapse and high-risk of bad prognosis to be built. The radiomics signatures identified were mostly related to tumor heterogeneity.

Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas.

OBJECTIVES: We aimed to assess the ability of radiomics, applied to not-enhanced computed tomography (CT), to differentiate mediastinal masses as thymic neoplasms vs lymphomas. METHODS: The present study was an observational retrospective trial. Inclusion criteria were pathology-proven thymic neoplasia or lymphoma with mediastinal localization, availability of CT. Exclusion criteria were age < 16 years and mediastinal lymphoma lesion < 4 cm. We selected 108 patients (M:F = 47:61, median age 48 years, range 17-79) and divided them into a training and a validation group. Radiomic features were used as predictors in linear discriminant analysis. We built different radiomic models considering segmentation software and resampling setting. Clinical variables were used as predictors to build a clinical model. Scoring metrics included sensitivity, specificity, accuracy and area under the curve (AUC). Wilcoxon paired test was used to compare the AUCs. RESULTS: Fifty-five patients were affected by thymic neoplasia and 53 by lymphoma. In the validation analysis, the best radiomics model sensitivity, specificity, accuracy and AUC resulted 76.2 ± 7.0, 77.8 ± 5.5, 76.9 ± 6.0 and 0.84 ± 0.06, respectively. In the validation analysis of the clinical model, the same metrics resulted 95.2 ± 7.0, 88.9 ± 8.9, 92.3 ± 8.5 and 0.98 ± 0.07, respectively. The AUCs of the best radiomic and the clinical model not differed. CONCLUSIONS: We developed and validated a CT-based radiomic model able to differentiate mediastinal masses on non-contrast-enhanced images, as thymic neoplasms or lymphoma. The proposed method was not affected by image postprocessing. Therefore, the present image-derived method has the potential to noninvasively support diagnosis in patients with prevascular mediastinal masses with major impact on management of asymptomatic cases.

Predicting survival and local control after radiochemotherapy in locally advanced head and neck cancer by means of computed tomography based radiomics.

PURPOSE: To appraise the ability of a radiomics signature to predict clinical outcome after definitive radiochemotherapy (RCT) of stage III-IV head and neck cancer. METHODS: A cohort of 110 patients was included in a retrospective analysis. Radiomics texture features were extracted from the gross tumor volumes contoured on planning computed tomography (CT) images. The cohort of patients was randomly divided into a training (70 patients) and a validation (40 patients) cohorts. Textural features were correlated to survival and control data to build predictive models. All the significant predictors of the univariate analysis were included in a multivariate model. The quality of the models was appraised by means of the concordance index (CI). RESULTS: A signature with 3 features was identified as predictive of overall survival (OS) with CI = 0.88 and 0.90 for the training and validation cohorts, respectively. A signature with 2 features was identified for progression-free survival (PFS; CI = 0.72 and 0.80); 2 features also characterized the signature for local control (LC; CI = 0.72 and 0.82). In all cases, the stratification in high- and low-risk groups for the training and validation cohorts led to significant differences in the actuarial curves. In the validation cohort the mean OS times (in months) were 78.9 ± 2.1 vs 67.4 ± 6.0 in the low- and high-risk groups, respectively, the PFS was 73.1 ± 3.7 and 50.7 ± 7.2, while the LC was 78.7 ± 2.1 and 63.9 ± 6.5. CONCLUSION: CT-based radiomic signatures that correlate with survival and control after RCT were identified and allow low- and high-risk groups of patients to be identified.

PET/CT radiomics in breast cancer: promising tool for prediction of pathological response to neoadjuvant chemotherapy.

PURPOSE: To assess the role of radiomics parameters in predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer. METHODS: Seventy-nine patients who had undergone pretreatment staging 18F-FDG PET/CT and treatment with NAC between January 2010 and January 2018 were included in the study. Primary lesions on PET images were delineated, and extraction of first-, second-, and higher-order imaging features was performed using LIFEx software. The relationship between these parameters and pCR to NAC was analyzed by multiple logistic regression models. RESULTS: Nineteen patients (24%) had pCR to NAC. Different models were generated on complete information and imputed datasets, using univariable and multivariable logistic regression and least absolute shrinkage and selection operator (lasso) regression. All models could predict pCR to NAC, with area under the curve values ranging from 0.70 to 0.73. All models agreed that tumor molecular subtype is the primary predictor of the primary endpoint. CONCLUSIONS: Our models predicted that patients with subtype 2 and subtype 3 (HER2+ and triple negative, respectively) are more likely to have a pCR to NAC than those with subtype 1 (luminal). The association between PET imaging features and pCR suggested that PET imaging features could be considered as potential predictors of pCR in locally advanced breast cancer patients.

Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery.

PURPOSE: Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients. The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery. METHODS: A cohort of 295 patients was selected. Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients. The endpoint of this study was DFS. Both computed tomography (CT) and fluorodeoxyglucose positron emission tomography (PET) images generated from the PET/CT scanner were analysed. Textural features were calculated using the LifeX package. Statistical analysis was performed using the R platform. The datasets were separated into two cohorts by random selection to perform training and validation of the statistical models. Predictors were fed into a multivariate Cox proportional hazard regression model and the receiver operating characteristic (ROC) curve as well as the corresponding area under the curve (AUC) were computed for each model built. RESULTS: The Cox models that included radiomic features for the CT, the PET, and the PET+CT images resulted in an AUC of 0.75 (95%CI: 0.65-0.85), 0.68 (95%CI: 0.57-0.80), and 0.68 (95%CI: 0.58-0.74), respectively. The addition of clinical predictors to the Cox models resulted in an AUC of 0.61 (95%CI: 0.51-0.69), 0.64 (95%CI: 0.53-0.75), and 0.65 (95%CI: 0.50-0.72) for the CT, the PET, and the PET+CT images, respectively. CONCLUSIONS: A radiomic signature, for either CT, PET, or PET/CT images, has been identified and validated for the prediction of disease-free survival in patients with non-small cell lung cancer treated by surgery.

Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions.

PURPOSE: To evaluate the ability of CT and PET radiomics features to classify lung lesions as primary or metastatic, and secondly to differentiate histological subtypes of primary lung cancers. METHODS: A cohort of 534 patients with lung lesions were retrospectively studied. Radiomics texture features were extracted using the LIFEx package from semiautomatically segmented PET and CT images. Histology data were recorded in all patients. The patient cohort was divided into a training and a validation group and linear discriminant analysis (LDA) was performed to classify the lesions using both direct and backward stepwise methods. The robustness of the procedure was tested by repeating the entire process 100 times with different assignments to the training and validation groups. Scoring metrics included analysis of the receiver operating characteristic curves in terms of area under the curve (AUC), sensitivity, specificity and accuracy. RESULTS: Radiomics features extracted from CT and PET datasets were able to differentiate primary tumours from metastases in both the training and the validation group (AUCs 0.79 ± 0.03 and 0.70 ± 0.04, respectively, from the CT dataset; AUCs 0.92 ± 0.01 and 0.91 ± 0.03, respectively, from the PET dataset). The AUC cut-off thresholds identified by LDA using direct and backward elimination strategies were -0.79 ± 0.06 and -0.81 ± 0.08, respectively (CT dataset) and -0.69 ± 0.05 and -0.68 ± 0.04, respectively (PET dataset). For differentiation between primary subgroups based on CT features, the AUCs in the training and validation groups were 0.81 ± 0.02 and 0.69 ± 0.04 for adenocarcinoma (Adc) vs. squamous cell carcinoma (Sqc) or "Other", 0.85 ± 0.02 and 0.70 ± 0.05 for Sqc vs. Adc or Other, and 0.77 ± 0.03 and 0.57 ± 0.05 for Other vs. Adc or Sqc. The same analyses for the PET data revealed AUCs of 0.90 ± 0.10 and 0.80 ± 0.04, 0.80 ± 0.02 and 0.61 ± 0.06, and 0.97 ± 0.01 and 0.88 ± 0.04, respectively. CONCLUSION: PET radiomics features were able to differentiate between primary and metastatic lung lesions and showed the potential to identify primary lung cancer subtypes.

Is surgical resection useful in elderly newly diagnosed glioblastoma patients? Outcome evaluation and prognostic factors assessment.

ASTRACT: BACKGROUND: The incidence of glioblastoma among elderly patients is constantly increasing. The value of radiation therapy and concurrent/adjuvant chemotherapy has been widely assessed. So far, the role of surgery has not been thoroughly investigated. The study aimed to evaluate safety and impact of several entities of surgical resection on outcome of elderly patients with newly diagnosed glioblastoma treated by a multimodal approach. METHODS: Patients ≥ 65 years, underwent surgery were included. The extent of surgical resection (EOR) was defined as complete resection (CR = 100%), gross total resection (GTR = 90-99%), sub-total resection (STR = 78-90%), partial resection (PR = 30-78%), and biopsy. After surgery, all patients received adjuvant radiotherapy (60/2 Gy fraction) with concomitant/adjuvant temozolomide chemotherapy. RESULTS: From March 2004 to December 2015, 178 elderly with a median age of 71 years (range 65-83 years) were treated. CR was obtained in 8 (4.5%), GTR in 63 (35.4%), STR in 46 (25.8%), PR in 16 (9.0%), and biopsy in 45 (25.3%). RT was started in all patients, concurrent/adjuvant CHT in 149 (83.7%) and 132 (74.2%). The median follow-up time was 12.2 months (range 0.4-50.4 months). The median, 1- and 2-year progression-free survival was 8.9 months (95%CI 7.8-100 months), 32.0 ± 3.5%, and 12.9 ± 2.6%. The median, 1- and 2-year overall survival were 12.2 (95%CI 11.3-13.1 months), 51.1 ± 3.7%, and 16.3 ± 2.9%. Tumor location, extent of resection, and neurological status after surgery statistically affected survival (p ≪ 0.01). CONCLUSION: Maximal surgical resection is safe and feasible in elderly patients with influence on survival. A preoperative evaluation has to be carried out.

On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system.

Inverse planning optimization using biologically based objectives is becoming part of the intensity modulated optimization process. The performances and efficacy of the biologically based gEUD (generalized Equivalent Uniform Dose) objective implemented in the Photon Optimizer (PO) of Varian Eclipse treatment planning system have been here analyzed. gEUD is associated with the parameter a that accounts for the seriality of a structure, being higher for more serial organs. The PO was used to optimize volumetric modulated arc therapy (VMAT) plans on a virtual homogeneous cylindrical phantom presenting a target and an organ at risk (OAR). The OAR was placed at 4 mm, 1 and 2 cm distance, or cropped at 0, 2 and 4 mm from the target. Homogeneous target dose of 60 Gy in 20 fractions was requested with physical dose-volume objectives, while OAR dose was minimized with the upper gEUD objective. The gEUD specific a parameter was varied from 0.1 to 40 to assess its impact to OAR sparing and target coverage. Actual head and neck and prostate cases, with one parotid and the rectum as test OAR, were also analyzed to translate the results in the more complex clinical environment. Increasing the a parameter value in the gEUD objective, the optimization achieved lower volumes of the OAR which received the highest dose levels. The maximum dose in the OAR was minimized well with a values up to 20, while further increase of a to 40 did not further improve the result. The OAR mean dose was reduced for the OAR located at 1 and 2 cm distance from the target, enforced with increasing a. For cropped OARs, a mean dose reduction was achieved for a values up to 3-5, but mean dose increased for higher a values. The optimal choice of the parameter a depends on the mutual OAR and target position, and seriality of the organ. Today no significant compendium of clinical and biological specific a and gEUD values are available for a wide range of OARs.

Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy.

BACKGROUND: To appraise the ability of a radiomics based analysis to predict local response and overall survival for patients with hepatocellular carcinoma. METHODS: A set of 138 consecutive patients (112 males and 26 females, median age 66 years) presented with Barcelona Clinic Liver Cancer (BCLC) stage A to C were retrospectively studied. For a subset of these patients (106) complete information about treatment outcome, namely local control, was available. Radiomic features were computed for the clinical target volume. A total of 35 features were extracted and analyzed. Univariate analysis was used to identify clinical and radiomics significant features. Multivariate models by Cox-regression hazards model were built for local control and survival outcome. Models were evaluated by area under the curve (AUC) of receiver operating characteristic (ROC) curve. For the LC analysis, two models selecting two groups of uncorrelated features were analyzes while one single model was built for the OS analysis. RESULTS: The univariate analysis lead to the identification of 15 significant radiomics features but the analysis of cross correlation showed several cross related covariates. The un-correlated variables were used to build two separate models; both resulted into a single significant radiomic covariate: model-1: energy p < 0.05, AUC of ROC 0.6659, C.I.: 0.5585-0.7732; model-2: GLNU p < 0.05, AUC 0.6396, C.I.:0.5266-0.7526. The univariate analysis for covariates significant with respect to local control resulted in 9 clinical and 13 radiomics features with multiple and complex cross-correlations. After elastic net regularization, the most significant covariates were compacity and BCLC stage, with only compacity significant to Cox model fitting (Cox model likelihood ratio test p < 0.0001, compacity p < 0.00001; AUC of the model is 0.8014 (C.I. = 0.7232-0.8797)). CONCLUSION: A robust radiomic signature, made by one single feature was finally identified. A validation phases, based on independent set of patients is scheduled to be performed to confirm the results.

Maximize surgical resection beyond contrast-enhancing boundaries in newly diagnosed glioblastoma multiforme: is it useful and safe? A single institution retrospective experience.

The extent of surgical resection (EOR) has been recorded as conditioning outcome in glioblastoma multiforme (GBM) patients but no significant improvements were recorded in survival. The study aimed to evaluate the impact of EOR on survival, investigating the role of fluid-attenuated inversion recovery (FLAIR) abnormalities removal. 282 newly diagnosed GBM patients were treated with surgery followed by concurrent and adjuvant chemo-radiotherapy. The EOR was defined as: SUPr, in case of resection amounting to 100% of enhanced and FLAIR areas; gross total (GTR) in case of resection between 90 and 100% of enhanced areas with variable amount of FLAIR abnormalities; sub-total (STR), between 10 and 89%; biopsy (B) <10%. FLAIR-RTV was dichotomized in percentage values to identify the best separation threshold for progression free survival (PFS) and overall survival (OS). SUPr was obtained in 21 patients (7.4%), GTR in 60 (21.3%), STR in 143 (50.7%) and biopsy only in 58 (20.6%). The median, 1, 2-year PFS were 10.4 ± 0.4 months, 39.0 ± 3.0, and 17.0 ± 2.0%; the median, 1, 2-year OS were 14.5 ± 0.5 months, 63.3 ± 3.0, and 23.1 ± 3.1%. EOR was significantly influencing survival (p < 0.001). The median, 1, 2-year OS were 28.6 ± 5.2 months, 90.0 ± 6.0, 71.0 ± 10.0% for patients underwent SUPr vs. 16.2 ± 1.2 months, 81.0 ± 5.0, 24.0 ± 6.0% for GTR. The FLAIR removal threshold conditioning survival was 45%. Minor complications were recorded in 14 (5%) patients and major in 8 (2.8%). surgical resection beyond contrast-enhancing boundaries could represent a promising strategy to improve outcome in GBM patients. The identification of a FLAIR-RTV threshold can be useful in clinical practice and it was recorded as factor influencing survival.

Role of surgical resection in recurrent glioblastoma: prognostic factors and outcome evaluation in an observational study.

The role of surgical resection in progressive or recurrent glioblastoma multiforme (GBM) lack of high level of evidence. The aim of this evaluation was to assess the role of surgical resection in relapsing GBM, in relation to the extent of surgical resection (EOR) and the amount of residual tumor volume (RTV). Among patients treated for newly diagnosed GBM between September 2008-December 2014, 64 patients with recurrent GBM were included in this retrospective evaluation. All patients underwent surgical resection followed by adjuvant treatments, chemotherapy and/or radiotherapy Results were evaluated in terms of local control (LC) rate, progression free survival (PFS) and patients overall survival (OS). Gross total resection (GTR) (>90%) was achieved in 48 (75%) patients and subtotal resection (STR) in 16 (25%). RTV was 0 in 40 (62.5%) patients and >0 in 24 (37.5%). No severe postoperative morbidity occurred. The median LC time was 6.0 ± 0.1 months (95% CI 5.29-8.55), with a 1 and 2 years LC rate of 29.4 ± 6.9%. The median PFS time was 6.8 ± 0.8 months, with a 1 year PFS rate of 27.2 ± 7.2% (95% CI 14.2-41.9). The median OS time was 10.3 ± 0.5 months (95% CI 7.6-10.4) with a 1 and 2 years OS rate of 22.5 ± 6.7% (95% CI 10.9-36.6). On univariate analysis EOR and RTV were recorded as conditioning LC and survival. These data was confirmed also in multivariate analysis only for RTV (p < 0.01). Recurrent GBM can take advantage of repeated surgery in selected patients with younger age and good clinical status. The entity of surgical resection was confirmed as conditioning survival.

Multi-isocentric 4π volumetric-modulated arc therapy approach for head and neck cancer.

OBJECTIVES: To explore the feasibility of multi-isocentric 4π volumetric-modulated arc therapy (MI4π-VMAT) for the complex targets of head and neck cancers. METHODS: Twenty-five previously treated patients of HNC underwent re-planning to improve the dose distributions with either coplanar VMAT technique (CP-VMAT) or noncoplanar MI4π-VMAT plans. The latter, involving 3-6 noncoplanar arcs and 2-3 isocenters were re-optimized using the same priorities and objectives. Dosimetric comparison on standard metrics from dose-volume histograms was performed to appraise relative merits of the two techniques. Pretreatment quality assurance was performed with IMRT phantoms to assess deliverability and accuracy of the MI4π-VMAT plans. The gamma agreement index (GAI) analysis with criteria of 3 mm distance to agreement (DTA) and 3% dose difference (DD) was applied. RESULTS: CP-VMAT and MI4π-VMAT plans achieved the same degree of coverage for all target volumes related to near-to-minimum and near-to-maximum doses. MI4π-VΜΑΤ plans resulted in an improved sparing of organs at risk. The average mean dose reduction to the parotids, larynx, oral cavity, and pharyngeal muscles were 3 Gy, 4 Gy, 5 Gy, and 4.3 Gy, respectively. The average maximum dose reduction to the brain stem, spinal cord, and oral cavity was 6.0 Gy, 3.8 Gy, and 2.4 Gy. Pretreatment QA results showed that plans can be reliably delivered with mean gamma agreement index of 97.0 ± 1.1%. CONCLUSIONS: MI4π-VMAT plans allowed to decrease the dose-volume-metrics for relevant OAR and results are reliable from a dosimetric standpoint. Early clinical experience has begun and future studies will report treatment outcome.

Value of Surgical Resection in Patients with Newly Diagnosed Grade III Glioma Treated in a Multimodal Approach: Surgery, Chemotherapy and Radiotherapy.

BACKGROUND: Current treatments in grade III gliomas include surgery, radiotherapy, and chemotherapy. The value of the entity of surgical resection remains an open question. The aim of this evaluation was to analyze the impact of extent of resection (EOR) and residual tumor volume (RTV) on progression-free survival (PFS) and overall survival (OS) in patients with newly diagnosed grade III gliomas. METHODS: Overall, 136 patients were included in this evaluation. EOR and RTV were defined in all patients on postoperative volumetric magnetic resonance imaging, with EOR being defined as the rate of surgical resection, and RTV as contrast-enhancing RTV (CE-RTV) and fluid-attenuated inversion recovery (FLAIR) RTV. A threshold of EOR and RTV was recorded using increments of 2 % and 1 cm(3). RESULTS: EOR and RTV were the only clinical variables influencing PFS and OS. The EOR cut-off value for conditioning survival was 76 %. For EOR ≥76 % or <76 %, the 5- to 10-year PFS was 57 % and 18 % versus 0 % (p = 0.03), and 5- to 10-year OS was 68 % and 42 % versus 0 % (p = 0.06), respectively. Additionally, the RTV cut-off value was 3 cm(3); for RTV <3 cm(3) or >3 cm(3), 5- to 10-year PFS was 64.3 % and 48.2 % versus 42 % and 0 % (p = 0.02), and 5- to 10-year OS was 66.8 % and 33.4 % versus 56 % and 0 % (p = 0.3), respectively. RTV was a more significant parameter conditioning PFS and OS than EOR (p = 0.04), and the presence of CE-RTV was an unfavorable prognostic factor compared with FLAIR-RTV. CONCLUSIONS: In heterogeneous lesions from a radiological point of view as WHO grade III gliomas if a complete removal is not possible, it would be advisable to maximize the removal of enhancing areas, possibly with an EOR >76 % and an RTV <3 cm(3).