Vesical Imaging-Reporting and Data System use predicting the outcome of neoadjuvant pembrolizumab in muscle-invasive bladder cancer.

OBJECTIVE: To evaluate the predictive capability of the pre- and post-pembrolizumab Vesical Imaging-Reporting and Data System (VI-RADS) to identify ypT0N0 or ypT≤1N0 response in muscle-invasive bladder cancer (MIBC) within the PURE-01 trial (ClinicalTrials.gov identifier: NCT02736266). PATIENTS AND METHODS: Patients were staged with bladder multiparametric magnetic resonance imaging (mpMRI) before and after treatment (three cycles of pembrolizumab) prior to radical cystectomy (RC). Logistic regression models were used to analyse the pre- and post- pembrolizumab VI-RADS against ypT≤1N0 and ypT0N0 response. The VI-RADS scores were dichotomised between 0 and 3 (0 = no evidence of disease) and 4-5. Event-free survival (EFS) and overall survival (OS) analyses were performed. Comprehensive genomic profiling and transcriptome-wide expression profiling data were matched with the VI-RADS scores. RESULTS: In total, 110 patients underwent centrally reviewed scans (N = 220 mpMRI), treated between February 2017 and July 2020. Both pre- and post-pembrolizumab VI-RADS 0-3 scores were the only significant covariates that predicted the ypT≤1N0 endpoint in multivariable analyses, and the strongest effect was seen with post-pembrolizumab VI-RADS 0-3 predicting the ypT≤1N0 response (P < 0.001). The area under the curve for this model was 0.90. Post-pembrolizumab VI-RADS 0-3 also predicted a longer EFS (P < 0.001) and OS (P = 0.044). The scores of several gene signatures from baseline tumours differed between the pre-pembrolizumab VI-RADS 0-3 and 4-5 categories. CONCLUSION: Post-pembrolizumab VI-RADS scores are strongly associated with pathological downstaging and survival. VI-RADS scores were also characterised by distinct biomarker features. These results indicate that the VI-RADS is emerging as an important tool for designing next-generation trials for MIBC.

Patient satisfaction with ultrasound, whole-body CT and whole-body diffusion-weighted MRI for pre-operative ovarian cancer staging: a multicenter prospective cross-sectional survey.

BACKGROUND: In addition to the diagnostic accuracy of imaging methods, patient-reported satisfaction with imaging methods is important. OBJECTIVE: To report a secondary outcome of the prospective international multicenter Imaging Study in Advanced ovArian Cancer (ISAAC Study), detailing patients' experience with abdomino-pelvic ultrasound, whole-body contrast-enhanced computed tomography (CT), and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) for pre-operative ovarian cancer work-up. METHODS: In total, 144 patients with suspected ovarian cancer at four institutions in two countries (Italy, Czech Republic) underwent ultrasound, CT, and WB-DWI/MRI for pre-operative work-up between January 2020 and November 2022. After having undergone all three examinations, the patients filled in a questionnaire evaluating their overall experience and experience in five domains: preparation before the examination, duration of examination, noise during the procedure, radiation load of CT, and surrounding space. Pain perception, examination-related patient-perceived unexpected, unpleasant, or dangerous events ('adverse events'), and preferred method were also noted. RESULTS: Ultrasound was the preferred method by 49% (70/144) of responders, followed by CT (38%, 55/144), and WB-DWI/MRI (13%, 19/144) (p<0.001). The poorest experience in all domains was reported for WB-DWI/MRI, which was also associated with the largest number of patients who reported adverse events (eg, dyspnea). Patients reported higher levels of pain during the ultrasound examination than during CT and WB-DWI/MRI (p<0.001): 78% (112/144) reported no pain or mild pain, 19% (27/144) moderate pain, and 3% (5/144) reported severe pain (pain score >7 of 10) during the ultrasound examination. We did not identify any factors related to patients' preferred method. CONCLUSION: Ultrasound was the imaging method preferred by most patients despite being associated with more pain during the examination in comparison with CT and WB-DWI/MRI. TRIAL REGISTRATION NUMBER: NCT03808792.

Relevance of apparent diffusion coefficient features for a radiomics-based prediction of response to induction chemotherapy in sinonasal cancer.

In this paper, several radiomics-based predictive models of response to induction chemotherapy (IC) in sinonasal cancers (SNCs) are built and tested. Models were built as a combination of radiomic features extracted from three types of MRI images: T1-weighted images, T2-weighted images and apparent diffusion coefficient (ADC) maps. Fifty patients (aged 54 ± 12 years, 41 men) were included in this study. Patients were classified according to their response to IC (25 responders and 25 nonresponders). Not all types of images were acquired for all of the patients: 49 had T1-weighted images, 50 had T2-weighted images and 34 had ADC maps. Only in a subset of 33 patients were all three types of image acquired. Eighty-nine radiomic features were extracted from the MRI images. Dimensionality reduction was performed by using principal component analysis (PCA) and by selecting only the three main components. Different algorithms (trees ensemble, K-nearest neighbors, support vector machine, naïve Bayes) were used to classify the patients as either responders or nonresponders. Several radiomic models (either monomodality or multimodality obtained by a combination of T1-weighted, T2-weighted and ADC images) were developed and the performance was assessed through 100 iterations of train and test split. The area under the curve (AUC) of the models ranged from 0.56 to 0.78. Trees ensemble, support vector machine and naïve Bayes performed similarly, but in all cases ADC-based models performed better. Trees ensemble gave the highest AUC (0.78 for the T1-weighted+T2-weighted+ADC model) and was used for further analyses. For trees ensemble, the models based on ADC features performed better than those models that did not use those features (P < 0.02 for one-tail Hanley test, AUC range 0.68-0.78 vs 0.56-0.69) except the T1-weighted+ADC model (AUC 0.71 vs 0.69, nonsignificant differences). The results suggest the relevance of ADC-based radiomics for prediction of response to IC in SNCs.

MRI Characteristics of Pediatric Renal Tumors: A SIOP-RTSG Radiology Panel Delphi Study.

BACKGROUND: The SIOP-Renal Tumor Study Group (RTSG) does not advocate invasive procedures to determine histology before the start of therapy. This may induce misdiagnosis-based treatment initiation, but only for a relatively small percentage of approximately 10% of non-Wilms tumors (non-WTs). MRI could be useful for reducing misdiagnosis, but there is no global consensus on differentiating characteristics. PURPOSE: To identify MRI characteristics that may be used for discrimination of newly diagnosed pediatric renal tumors. STUDY TYPE: Consensus process using a Delphi method. POPULATION: Not applicable. FIELD STRENGTH/SEQUENCE: Abdominal MRI including T1- and T2-weighted imaging, contrast-enhanced MRI, and diffusion-weighted imaging at 1.5 or 3 T. ASSESSMENT: Twenty-three radiologists from the SIOP-RTSG radiology panel with ≥5 years of experience in MRI of pediatric renal tumors and/or who had assessed ≥50 MRI scans of pediatric renal tumors in the past 5 years identified potentially discriminatory characteristics in the first questionnaire. These characteristics were scored in the subsequent second round, consisting of 5-point Likert scales, ranking- and multiple choice questions. STATISTICAL TESTS: The cut-off value for consensus and agreement among the majority was ≥75% and ≥60%, respectively, with a median of ≥4 on the Likert scale. RESULTS: Consensus on specific characteristics mainly concerned the discrimination between WTs and non-WTs, and WTs and nephrogenic rest(s) (NR)/nephroblastomatosis. The presence of bilateral lesions (75.0%) and NR/nephroblastomatosis (65.0%) were MRI characteristics indicated as specific for the diagnosis of a WT, and 91.3% of the participants agreed that MRI is useful to distinguish NR/nephroblastomatosis from WT. Furthermore, all participants agreed that age influenced their prediction in the discrimination of pediatric renal tumors. DATA CONCLUSION: Although the discrimination of pediatric renal tumors based on MRI remains challenging, this study identified some specific characteristics for tumor subtypes, based on the shared opinion of experts. These results may guide future validation studies and innovative efforts. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 3.

The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment.

PURPOSE: Human papillomavirus (HPV) status assessment is crucial for decision making in oropharyngeal cancer patients. In last years, several articles have been published investigating the possible role of radiomics in distinguishing HPV-positive from HPV-negative neoplasms. Aim of this review was to perform a systematic quality assessment of radiomic studies published on this topic. METHODS: Radiomics studies on HPV status prediction in oropharyngeal cancer patients were selected. The Radiomic Quality Score (RQS) was assessed by three readers to evaluate their methodological quality. In addition, possible correlations between RQS% and journal type, year of publication, impact factor, and journal rank were investigated. RESULTS: After the literature search, 19 articles were selected whose RQS median was 33% (range 0-42%). Overall, 16/19 studies included a well-documented imaging protocol, 13/19 demonstrated phenotypic differences, and all were compared with the current gold standard. No study included a public protocol, phantom study, or imaging at multiple time points. More than half (13/19) included feature selection and only 2 were comprehensive of non-radiomic features. Mean RQS was significantly higher in clinical journals. CONCLUSION: Radiomics has been proposed for oropharyngeal cancer HPV status assessment, with promising results. However, these are supported by low methodological quality investigations. Further studies with higher methodological quality, appropriate standardization, and greater attention to validation are necessary prior to clinical adoption.

Prognostic role of pre-treatment magnetic resonance imaging (MRI)-based radiomic analysis in effectively cured head and neck squamous cell carcinoma (HNSCC) patients.

OBJECTIVES: To identify and validate baseline magnetic resonance imaging (b-MRI) radiomic features (RFs) as predictors of disease outcomes in effectively cured head and neck squamous cell carcinoma (HNSCC) patients. MATERIALS AND METHODS: Training set (TS) and validation set (VS) were retrieved from preexisting datasets (HETeCo and BD2Decide trials, respectively). Only patients with both pre- and post-contrast enhancement T1 and T2-weighted b-MRI and at least 2 years of follow-up (FUP) were selected. The combination of the best extracted RFs was used to classify low risk (LR) vs. high risk (HR) of disease recurrence. Sensitivity, specificity, and area under the curve (AUC) of the radiomic model were computed on both TS and VS. Overall survival (OS) and 5-year disease-free survival (DFS) Kaplan-Meier (KM) curves were compared for LR vs. HR. The radiomic-based risk class was used in a multivariate Cox model, including well-established clinical prognostic factors (TNM, sub-site, human papillomavirus [HPV]). RESULTS: In total, 57 patients of TS and 137 of VS were included. Three RFs were selected for the signature. Sensitivity of recurrence risk classifier was 0.82 and 0.77, specificity 0.78 and 0.81, AUC 0.83 and 0.78 for TS and VS, respectively. VS KM curves for LR vs. HR groups significantly differed both for 5-year DFS (p<.0001) and OS (p=.0004). A combined model of RFs plus TNM improved prognostic performance as compared to TNM alone, both for VS 5-year DFS (C-index: 0.76 vs. 0.60) and OS (C-index: 0.74 vs. 0.64). CONCLUSIONS: Radiomics of b-MRI can help to predict recurrence and survival outcomes in HNSCC.

Patients with adenoid cystic carcinomas of the salivary glands treated with lenvatinib: Activity and quality of life.

BACKGROUND: The treatment of patients with recurrent and/or metastatic (R/M) salivary gland adenoid cystic carcinoma (ACC) remains an unmet need. METHODS: Patients with R/M disease with a history of clinical or symptomatic disease progression within 6 months and a maximum of 1 previous line of chemotherapy or a multiple kinase inhibitor received oral lenvatinib at a dose of 24 mg/day. The primary endpoint was the objective response rate; secondary endpoints included quality of life (QOL) (according to the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 Items [EORTC QLQ-C30] and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core Module Head and Neck Module [EORTC QLQ-H&N35]), progression-free survival and overall survival, duration of response, and toxicities. RESULTS: Twenty-eight patients with R/M ACC were enrolled. Among 26 evaluable patients, 3 partial responses (11.5%) were reported. Target lesion reductions between 23% to 28% were observed in 4 of 20 patients with stable disease. Treatment-related adverse events were frequent (all grades, 96%; grade≥3 in 50% of cases according to version 4.03 of the National Cancer Institute Common Terminology Criteria for Adverse Events). The dose of lenvatinib was reduced in 24 patients, whereas in 21 patients the dose was reduced within the first 12 weeks and 4 patients maintained the full dose throughout treatment. The QOL deteriorated between baseline and 6 months with regard to Fatigue and Dry Mouth. There was no evidence of changes in Swallowing and Physical Functioning. At a median follow-up of 29 months, 2 patients remained on treatment, 10 patients were off protocol for disease progression and were alive with disease, and 14 patients had died of disease progression. The median overall survival, progression-free survival, and duration of response were 27 months, 9.1 months, and 3.1 months, respectively. CONCLUSIONS: Lenvatinib appears to have modest activity in ACC. Toxicities are common but manageable and QOL was found to deteriorate in some domains.

Reduced-dose craniospinal irradiation is feasible for standard-risk adult medulloblastoma patients.

INTRODUCTION: Medulloblastoma is the most common malignant brain tumor in children, but accounts for only 1% of brain cancers in adults. For standard-risk pediatric medulloblastoma, current therapy includes craniospinal irradiation (CSI) at reduced doses (23.4 Gy) associated with chemotherapy. Whereas most same-stage adult patients are still given CSI at 36 Gy, with or without chemotherapy, we report here on our use of reduced-dose CSI associated with chemotherapy for older patients. METHODS: We gathered non-metastatic patients over 18 years old (median age 28 years, range 18-48) with minimal or no residual disease after surgery, no negative histological subtypes, treated between 1996-2018 at the Centre Léon Bérard (Lyon) and the INT (Milano). A series of 54 children with similar tumors treated in Milano was used for comparison. RESULTS: Forty-four adults were considered (median follow-up 101 months): 36 had 23.4 Gy of CSI, and 8 had 30.6 Gy, plus a boost to the posterior fossa/tumor bed; 43 had chemotherapy as all 54 children, who had a median 83-month follow-up. The PFS and OS were 82.2 ± 6.1% and 89 ± 5.2% at 5 years, and 78.5 ± 6.9% and 75.2 ± 7.8% at ten, not significantly different from those of the children. CSI doses higher than 23.4 Gy did not influence PFS. Female adult patients tended to have a better outcome than males. CONCLUSION: The results obtained in our combined series are comparable with, or even better than those obtained after high CSI doses, underscoring the need to reconsider this treatment in adults.

First-line therapy with dacomitinib, an orally available pan-HER tyrosine kinase inhibitor, for locally advanced or metastatic penile squamous cell carcinoma: results of an open-label, single-arm, single-centre, phase 2 study.

OBJECTIVE: To harness the frontline therapy in advanced penile squamous cell carcinoma (PSCC), for which chemotherapy exerts moderate activity but poor efficacy. Dacomitinib is an irreversible, pan-epidermal growth factor receptor (HER) inhibitor. PATIENTS AND METHODS: In a phase 2 study (NCT01728233), patients received dacomitinib 45 mg/day, orally, continuously. Inclusion criteria were SCC histology, clinical stage N2-3 or M1 (Tumour-Node-Metastasis classification system 2009), and no prior chemotherapy administration. The primary endpoint was the objective response rate (ORR, according to the Response Evaluation Criteria in Solid Tumors, version 1.1). Stopping rules based on the Bayesian posterior probability (PP) to demonstrate that the ORR exceeded 20% were set. RESULTS: From June 2013 to October 2016, 28 patients were treated. Eight (28.6%) had visceral metastases, 14 (50%) had pelvic and 17 (60.7%) clinically involved bilateral lymph nodes. One complete and eight partial responses were obtained (ORR 32.1%, 80% credibility interval 21.0-43.0%). The median (interquartile range [IQR]) follow-up duration was 19.8 (6.3-25.7) months; 12-month progression-free survival was 26.2% (95% confidence interval [CI] 13.2-51.9); 12-month overall survival (OS) was 54.9% (95% CI 36.4-82.8). The median (IQR) OS of locally advanced patients was 20 (11.1-not reached) months. The Bayesian PP of exceeding the 20% ORR target was 92.3%. Grade 3 adverse events (skin rash) were seen in three patients (10.7%). Tissue samples from 25 patients were analysed. Only two patients had high-risk human papillomavirus-positive tumours. Epidermal growth factor receptor (EGFR) amplification was found in four patients (equally responders and non-responders) and it was confirmed in all post-dacomitinib samples. Telomerase reverse transcriptase (TERT) mutations were found in responders only (60%), and phosphatidylinositol 3-kinase/mammalian target of rapamycin (PI3K/mTOR) pathway gene mutations were found in 42.9% of responders vs 8.3% of non-responders. CONCLUSION: Dacomitinib was active and well tolerated in patients with advanced PSCC and may represent an option when combined chemotherapy cannot be administered. Mutations in downstream effectors of EGFR signalling in relation to dacomitinib activity deserve further studies.

Big Data in Head and Neck Cancer.

OPINION STATEMENT: Head and neck cancers can be used as a paradigm for exploring "big data" applications in oncology. Computational strategies derived from big data science hold the promise of shedding new light on the molecular mechanisms driving head and neck cancer pathogenesis, identifying new prognostic and predictive factors, and discovering potential therapeutics against this highly complex disease. Big data strategies integrate robust data input, from radiomics, genomics, and clinical-epidemiological data to deeply describe head and neck cancer characteristics. Thus, big data may advance research generating new knowledge and improve head and neck cancer prognosis supporting clinical decision-making and development of treatment recommendations.

Different pixel pitch and maximum luminance of medical grade displays may result in different evaluations of digital radiography images.

AIM: To evaluate the effects of display pixel pitch and maximum luminance on intra- and inter-observer reproducibility and observer performance when evaluating chest lesions and bone fractures. MATERIALS AND METHODS: This was a multi-institutional study for a retrospective interpretation of selected digital radiography images. Overall, 82 images were selected by senior radiologists, including 50 cases of chest lesions and 32 cases of bone fractures. These images were displayed at two pixel pitches (0.212 and 0.165 mm size pixels) and two maximum luminance values (250 and 500 cd/m2) and reviewed twice by senior and junior radiologists. All the observers had to indicate the likelihood of the presence of the lesions and to rate the relative confidence of their assessment. Cohen Kappa statistic was computed to estimate the reproducibility in correctly identifying lesions; for multi-reader-multi-case (MRMC) analysis, weighted Jackknife Alternative Free-response Receiver Operating Characteristic (wJAFROC) statistical tools was applied. RESULTS: The intra-radiologist and inter-observer reproducibility values were the highest for the 0.165 mm size pixel at 500 cd/m2 display, for both chest lesions and bone fractures evaluations. As regards chest lesions, observer performances were significantly greater with 0.165 mm size pixel display at 500 cd/m2 than with lower maximum luminance and/or larger pixel pitch displays. Concerning bone fractures, the performance obtained with 0.212 mm size pixel display at 250 cd/m2 was statistically lower than that obtained with 0.165 mm sixe pixel display at 500 cd/m2. CONCLUSION: Our results indicate that an increased maximum luminance level and a decreased pixel pitch of medical-grade display improve the accuracy of detecting both chest lesions and bone fractures.

Assessment of Stability and Discrimination Capacity of Radiomic Features on Apparent Diffusion Coefficient Images.

The objectives of the study are to develop a new way to assess stability and discrimination capacity of radiomic features without the need of test-retest or multiple delineations and to use information obtained to perform a preliminary feature selection. Apparent diffusion coefficient (ADC) maps were computed from diffusion-weighted magnetic resonance images (DW-MRI) of two groups of patients: 18 with soft tissue sarcomas (STS) and 18 with oropharyngeal cancers (OPC). Sixty-nine radiomic features were computed, using three different histogram discretizations (16, 32, and 64 bins). Geometrical transformations (translations) of increasing entity were applied to the regions of interest (ROIs), and the intra-class correlation coefficient (ICC) was used to compare the features computed on the original and modified ROIs. The distribution of ICC values for minimal and maximal entity translations (ICC10 and ICC100, respectively) was used to adjust thresholds of ICC (ICCmin and ICCmax) used to discriminate between good, unstable (ICC10 < ICCmin), and non-discriminative features (ICC100 > ICCmax). Fifty-four and 59 radiomic features passed the stability-based selection for all the three histogram discretizations for the OPC and STS datasets, respectively. The excluded features were similar across the different histogram discretizations (Jaccard's index 0.77 ± 0.13 and 0.9 ± 0.1 for OPC and STS, respectively) but different between datasets (Jaccard's index 0.19 ± 0.02). The results suggest that the observed radiomic features are mainly stable and discriminative, but the stability depends on the region of the body under observation. The method provides a way to assess stability without the need of test-retest or multiple delineations.

An open-label, single-arm, phase 2 study of the Aurora kinase A inhibitor alisertib in patients with advanced urothelial cancer.

BACKGROUND: Progress in developing effective salvage therapies for UC is warranted. Alisertib is an orally available, selective inhibitor of the aurora kinase A. METHODS: A single-group, phase 2 trial was conducted with alisertib 50 mg orally BID for 7 days, with 14d rest until disease progression (PD) (NCT02109328). The primary endpoint (EP) was RECIST 1.1 objective response-rate (ORR, H0 ≤ 5%, H1 ≥ 20%, α = 10% and ß = 20%). Eligibility included failure of at least one platinum-based regimen. RESULTS: From 10/2014 to 04/2015, 22 patients were enrolled (20 evaluable for response), 8 (36.4%) in second-line and 14 (63.6 %) beyond the second-line. Eight (36.4%) had an ECOG-performance status 1-2. Two partial responses (PR, ORR: 9.1%), 7 stable disease (SD) and 11 PD were obtained. Median follow-up was 8.3 months (IQR: 7-10.3), 6-month progression-free survival (PFS) was 13.6% (95%CI: 4.8-39.0). Two SD are still receiving treatment after 11.5 and 6.3 months. Median overall survival (OS) was not reached (6-month OS: 59.1%, 95%CI: 41.7-83.7). Hb < 10 g/dl was significantly associated with shorter PFS and OS multivariably (p = 0.031 and p = 0.033). Tissue of the case with 11.5 month SD harbored a missense mutation of mTOR (E1813D), the nonsense mutation Q527STOP of TSC1, HER3 and TAF1L missense mutations. Grade 3-4 adverse events (AE) were: 40.9% mucositis, 36.4% fatigue, 18.2% neutropenia (13.6% febrile neutropenia). There were 2 treatment-related deaths. CONCLUSIONS: The study did not meet the primary EP, yet sustained disease control was obtained in about 14% of patients. The incidence of AE and the issue of patient selection are two major concerns.

[Lung cancer screening in high-risk subjects: early detection with LDCT and risk stratification using miRNA-based blood test]. / Screening per il tumore polmonare in soggetti ad alto rischio: diagnosi precoce con TC spirale associata a stratificazione del rischio con miRNA circolanti.

Lung cancer still remains a high mortality disease in the face of developments in diagnostic and therapeutic methods that occurred in the last 20 years. The analysis of the experiences from the first studies - in which chest X-ray (CXR) was adopted, associated or not with sputum cytology - has failed to show a reduction in lung cancer specific mortality. Subsequent screening studies that have introduced the use of low-dose computed tomography (LDCT) have revealed a large number of early-stage lung cancers, thus potentially curable; however, this has not allowed us to demonstrate a decrease in lung cancer-specific mortality. With the results of the American study National Lung ScreeningTrial (NLST), published in 2011, for the first time a lung cancer-specific mortality reduction by 20% thanks to the use of LDCT compared to RXT, was highlighted. However, a false discovery rate of 96.4% was also described with an overdiagnosis that can be up to 78.9% for bronchioalveolar lung cancer. Due to the high sensitivity of LDCT, able to identify a non-calcified pulmonary nodule in one subject on two, it becomes necessary to avail instruments to more accurately identify suspicious nodules. Until some time ago, the possible use of lung tumour markers was not viable in view of the poor organ specificity. The study and development was, then, pushed to organ- and tissue-specific markers such as microRNA (miRNA), noncoding RNA sequences involved in many processes and expression of oncogenic activity of the microenvironment. The use of biomarkers such as circulating miRNA implemented in LDCT screening has highlighted a reduction of 5 times for the rate of false positives, going from 19.4% to 3.7%, with a sensitivity of 87%, a specificity of 81%, and a negative predictive value of 99%. The need to appropriately use the available resources commensurate with the disease to treat will push more and more towards the implementation of LDCT biomarkers based screenings, stable and easily reproducible, as circulating miRNAs, obviating to problems such as false positives, unnecessary procedures of invasive surgery for benign lesions, and optimizing the cost benefit ratios.The development of new specific biomarkers appears to offer new promising prospects.

A case of relapsing spinal atypical teratoid/rhabdoid tumor (AT/RT) responding to vinorelbine, cyclophosphamide, and celecoxib.

INTRODUCTION: Atypical teratoid/rhabdoid tumor (AT/RT) of the central nervous system is a highly aggressive neoplasm which prevalently affects children and is characterized by a severe prognosis. CASE PRESENTATION: The authors describe an extremely rare case of a primary spinal AT/RT that occurred in a young girl. The patient underwent a wide surgical resection of a lumbar mass, followed by aggressive chemotherapy, myeloablative treatment, and local radiotherapy. After 7 months from the end of the treatment, the patient experienced local recurrence and was treated with surgery and second-line chemotherapy with antiangiogenic purposes, consisting of oral vinorelbine, cyclophosphamide, and celecoxib. Treatment was well tolerated, and patient was still alive 36 months after diagnosis. CONCLUSION: The peculiarity of this case report is the clinical-radiological response to a metronomic therapy in a case of early-relapsing spinal AT/RT despite previous maximal surgery, chemotherapy, and radiotherapy.

Developing a robust two-step machine learning multiclassification pipeline to predict primary site in head and neck carcinoma from lymph nodes.

This study aimed to develop a robust multiclassification pipeline to determine the primary tumor location in patients with head and neck carcinoma of unknown primary using radiomics and machine learning techniques. The dataset included 400 head and neck cancer patients with primary tumor in oropharynx, OPC (n = 162), nasopharynx, NPC (n = 137), oral cavity, OC (n = 63), larynx and hypopharynx, HL (n = 38). Two radiomic-based multiclassification pipelines (P1 and P2) were developed. P1 consisted in a direct identification of the primary sites, whereas P2 was based on a two-step approach: in the first step, the number of classes was reduced by merging the two minority classes which were reclassified in the second step. Diverse correlation thresholds (0.75, 0.80, 0.85), feature selection methods (sequential forwards/backwards selection, sequential floating forward selection, neighborhood component analysis and minimum redundancy maximum relevance), and classification models (neural network, decision tree, naïve Bayes, bagged trees and support vector machine) were assessed. P2 outperformed P1, with the best results obtained with the support vector machine classifier including radiomic and clinical features (accuracies of 75.3 % (HL), 75.4 % (OC), 71.3 % (OPC), 92.9 % (NPC)). These results indicate that the two-step multiclassification pipeline integrating radiomics and clinical information is a promising approach to predict the tumor site of unknown primary.

MRI radiomics in head and neck cancer from reproducibility to combined approaches.

The clinical applicability of radiomics in oncology depends on its transferability to real-world settings. However, the absence of standardized radiomics pipelines combined with methodological variability and insufficient reporting may hamper the reproducibility of radiomic analyses, impeding its translation to clinics. This study aimed to identify and replicate published, reproducible radiomic signatures based on magnetic resonance imaging (MRI), for prognosis of overall survival in head and neck squamous cell carcinoma (HNSCC) patients. Seven signatures were identified and reproduced on 58 HNSCC patients from the DB2Decide Project. The analysis focused on: assessing the signatures' reproducibility and replicating them by addressing the insufficient reporting; evaluating their relationship and performances; and proposing a cluster-based approach to combine radiomic signatures, enhancing the prognostic performance. The analysis revealed key insights: (1) despite the signatures were based on different features, high correlations among signatures and features suggested consistency in the description of lesion properties; (2) although the uncertainties in reproducing the signatures, they exhibited a moderate prognostic capability on an external dataset; (3) clustering approaches improved prognostic performance compared to individual signatures. Thus, transparent methodology not only facilitates replication on external datasets but also advances the field, refining prognostic models for potential personalized medicine applications.

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). METHODS AND OBJECTIVES: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. CONCLUSION: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project.

Repeatability and reproducibility of MRI-radiomic features: A phantom experiment on a 1.5 T scanner.

PURPOSE: Aim of this study is to assess the repeatability of radiomic features on magnetic resonance images (MRI) and their stability to variations in time of repetition (TR), time of echo (TE), slice thickness (ST), and pixel spacing (PS) using vegetable phantoms. METHODS: The organic phantom was realized using two cucumbers placed inside a cylindrical container, and the analysis was performed using T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted images. One dataset was used to test the repeatability of the radiomic features, whereas other four datasets were used to test the sensitivity of the different MRI sequences to image acquisition parameters (TR, TE, ST, and PS). Four regions of interest (ROIs) were segmented: two for the central part of each cucumber and two for the external parts. Radiomic features were extracted from each ROI using Pyradiomics. To assess the effect of preprocessing on the reduction of variability, features were extracted both before and after the preprocessing. The coefficient of variation (CV) and intra-class correlation coefficient (ICC) were used to evaluate variability. RESULTS: The use of intensity standardization increased the stability for the first-order statistics features. Shape and size features were always stable for all the analyses. Textural features were particularly sensitive to changes in ST and PS, although some increase in stability could be obtained by voxel size resampling. When images underwent image preprocessing, the number of stable features (ICC > 0.75 and mean absolute CV < 0.3) was 33 for apparent diffusion coefficient (ADC), 52 for T1w, and 73 for T2w. CONCLUSIONS: The most critical source of variability is related to changes in voxel size (either caused by changes in ST or PS). Preprocessing increases features stability to both test-retest and variation of the image acquisition parameters for all the types of analyzed MRI (T1w, T2w, and ADC), except for ST.

MRI-based radiomic prognostic signature for locally advanced oral cavity squamous cell carcinoma: development, testing and comparison with genomic prognostic signatures.

BACKGROUND: . At present, the prognostic prediction in advanced oral cavity squamous cell carcinoma (OCSCC) is based on the tumor-node-metastasis (TNM) staging system, and the most used imaging modality in these patients is magnetic resonance image (MRI). With the aim to improve the prediction, we developed an MRI-based radiomic signature as a prognostic marker for overall survival (OS) in OCSCC patients and compared it with published gene expression signatures for prognosis of OS in head and neck cancer patients, replicated herein on our OCSCC dataset. METHODS: For each patient, 1072 radiomic features were extracted from T1 and T2-weighted MRI (T1w and T2w). Features selection was performed, and an optimal set of five of them was used to fit a Cox proportional hazard regression model for OS. The radiomic signature was developed on a multi-centric locally advanced OCSCC retrospective dataset (n = 123) and validated on a prospective cohort (n = 108). RESULTS: The performance of the signature was evaluated in terms of C-index (0.68 (IQR 0.66-0.70)), hazard ratio (HR 2.64 (95% CI 1.62-4.31)), and high/low risk group stratification (log-rank p < 0.001, Kaplan-Meier curves). When tested on a multi-centric prospective cohort (n = 108), the signature had a C-index of 0.62 (IQR 0.58-0.64) and outperformed the clinical and pathologic TNM stage and six out of seven gene expression prognostic signatures. In addition, the significant difference of the radiomic signature between stages III and IVa/b in patients receiving surgery suggests a potential association of MRI features with the pathologic stage. CONCLUSIONS: Overall, the present study suggests that MRI signatures, containing non-invasive and cost-effective remarkable information, could be exploited as prognostic tools.