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.

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.

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.

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.

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.

Multidisciplinary management of pregnancy-associated and early post-partum head and neck cancer patients.

Background: Pregnancy-associated cancer (PAC) occurs during pregnancy or within 12 months after the delivery. Head and neck cancer (HNC) during pregnancy is infrequent, therefore diagnosis and personalized therapy are intricate. Methods: We investigated outcomes of 15 PAC patients (5 salivary, 4 nasopharyngeal, 3 thyroid, 2 oral cavity, one HPV-related carcinoma) diagnosed in the period 2005-2019. A literature review on PAC is provided. Results: Median gestational age at PAC diagnosis was 28 weeks (range: 16-40 weeks) in ten cases, at 5 months after delivery (range: 1 week-6 months) in the remaining five. Treatments included surgery (3 during pregnancy, 5 after childbirth), chemoradiation (8), and 3 patients with upfront metastatic disease received chemotherapy. Median survival was 6.6 years (eight women remain with no evidence of disease six years after diagnosis). Conclusion: All patients received state-of-the-art therapy, with encouraging long-term results, highlighting treatment safety in women with HNC during pregnancy.

Pre-treatment risk factors to predict early cisplatin-related nephrotoxicity in locally advanced head and neck cancer patients treated with chemoradiation: A single Institution experience.

OBJECTIVES: Cisplatin is essential in the curative treatment of locally advanced head and neck squamous cell carcinoma (LA-HNSCC) patients. The assessment of risk factors to predict an early cisplatin-induced nephrotoxicity could help in better managing one of the most relevant cisplatin-related dose-limiting factors. MATERIAL AND METHODS: We retrospectively collected data of LA-HNSCC patients treated at our Institution from 2008 to 2019. Patients received cisplatin in a curative setting concurrently with radiation. Acute Kidney Injury (AKI) was assessed as a dichotomous variable (CreaIncr) based on pre-treatment values, and values recorded at days 6-20 post-first cycle of cisplatin. Univariable logistic regression models were performed to investigate associations between CreaIncr and clinical characteristics. A multivariable logistic model on a priori selected putative covariates was performed. RESULTS: Of the 350 LA-HNSCC treated patients, 204 were analyzed. Ninety (44 %) suffered from any grade AKI (grade I 51.1 %): out of them, 84.4 % received high-dose cisplatin (100 mg/m2 q21). On the univariable logistic regression model, male sex, age, serum uric acid, creatinine, concomitant drugs, and cisplatin schedule were significantly associated with a higher rate of AKI. At multivariable model, age (p = 0.034), baseline creatinine (p = 0.027), concomitant drugs (p = 0.043), and cisplatin schedule (one-day bolus or fractionated high-dose vs. weekly; p = 0.001) maintained their significant association. CONCLUSIONS: Identifying pre-treatment risk factors in LA-HNSCC patients may improve decision-making in a setting where cisplatin has a curative significance. A strict monitoring of AKI could avoid cisplatin dose adjustments, interruptions, and treatment delays, thus limiting a negative impact on outcomes.

Using Radiomics and Machine Learning Applied to MRI to Predict Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer.

Neoadjuvant chemotherapy plus radical surgery could be a safe alternative to chemo-radiation in cervical cancer patients who are not willing to receive radiotherapy. The response to neoadjuvant chemotherapy is the main factor influencing the need for adjunctive treatments and survival. In the present paper we aim to develop a machine learning model based on cervix magnetic resonance imaging (MRI) images to stratify the single-subject risk of cervical cancer. We collected MRI images from 72 subjects. Among these subjects, 28 patients (38.9%) belonged to the "Not completely responding" class and 44 patients (61.1%) belonged to the 'Completely responding' class according to their response to treatment. This image set was used for the training and cross-validation of different machine learning models. A robust radiomic approach was applied, under the hypothesis that the radiomic features could be able to capture the disease heterogeneity among the two groups. Three models consisting of three ensembles of machine learning classifiers (random forests, support vector machines, and k-nearest neighbor classifiers) were developed for the binary classification task of interest ("Not completely responding" vs. "Completely responding"), based on supervised learning, using response to treatment as the reference standard. The best model showed an ROC-AUC (%) of 83 (majority vote), 82.3 (mean) [79.9-84.6], an accuracy (%) of 74, 74.1 [72.1-76.1], a sensitivity (%) of 71, 73.8 [68.7-78.9], and a specificity (%) of 75, 74.2 [71-77.5]. In conclusion, our preliminary data support the adoption of a radiomic-based approach to predict the response to neoadjuvant chemotherapy.

NUT carcinoma of the submandibular gland: A case report.

BACKGROUND: NUT carcinoma (NUTc) is a rare and aggressive malignant epithelial tumor characterized by rearrangement of the NUT gene on chromosome 15q14. METHODS: In this article, we present the fifth case worldwide of a young woman affected by a NUTc arising from a submandibular gland, presenting as a rapidly evolving mass. She underwent a right scialoadenectomy and received the initial diagnosis of high-grade mucoepidermoid carcinoma. Due to evidence of local recurrence at magnetic resonance imaging 1 month later, a subsequent right radical neck dissection was performed. The patient then sought a second opinion at our cancer center and finally received the correct diagnosis of NUT carcinoma. Given the well-known aggressive behavior of this neoplasm, as well as clinical and radiological features, she underwent adjuvant chemo-radiation (intensity-modulated radiotherapy + concurrent chemotherapy with cisplatin). RESULTS: After a disease-free interval of 2.6 months, a widespread metastatic disease led to rapid deterioration of performance status and patient death in a few weeks after metastatic onset. CONCLUSIONS: We presented a case of NUTc arising from salivary gland aiming to improve the knowledge of this rare malignancy. First, we pointed out that in the setting of rare tumors like salivary gland cancers, the diagnosis should be obtained by expert pathologists, and patients should be referred to tertiary cancer centers for their clinical management. Second, molecular profiling may help to identify possible druggable targets that may be exploited to treat patients suffering from this aggressive malignancy. Sharing the molecular data provided in this case will be useful for further research.

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.

The SINTART 2 Study. A phase II non-randomised controlled trial of induction chemotherapy, photon-, proton- and carbon-ion-based radiotherapy integration in patients with locally advanced unresectable sinonasal tumours.

PURPOSE: Unresectable, locally advanced sinonasal epithelial tumours are rare diseases with poor prognosis. Multimodal approach is widely used, although no standard therapy has been established in prospective trials. This study assessed activity and safety of an innovative integration of multimodality treatment-induction chemotherapy (ICT), surgery and radiotherapy (RT)-modulated by histology and response to ICT. METHODS: Patients with untreated, unresectable sinonasal epithelial tumours with selected histotypes (squamous cell carcinoma, intestinal-type adenocarcinoma, sinonasal undifferentiated and neuroendocrine carcinoma, olfactory neuroblastoma) were enroled in a single-arm, open-label, phase II, multicentre clinical trial. Patients were treated with up to 5 ICT cycles, whose regimen was selected according to histotype. Photon and/or proton/carbon-ion-based RT was employed according to disease site, stage and ICT response. Primary end-point was 5-years progression-free survival (PFS), secondary end-points were overall survival (OS), ICT objective response rate per RECIST 1.1 and safety. RESULTS: Twenty-five patients were evaluable for primary end-point. Five-year PFS was 26.8% (95% confidence interval [CI]: 12.6-57.1), with a median PFS of 18 months. Five-year OS was 23.8% (95% CI: 9.5-59.3), with a median OS of 27 months. The overall response rate to ICT was 40%. Three-year PFS for patients achieving major volumetric partial response (mPRv) versus non-mPRv was 40% (95% CI: 13.7-100%) versus 23.1% (95% CI: 8.3-64.7%) (P = 0.318) and 3-year OS was 53.3% (95% CI: 21.4-100%) versus 37.7% (95% CI: 20.0-71.0%) (P = 0.114). CONCLUSION: Multimodal combination of ICT and innovative RT did not provide a significant improvement in survival rates with respect to previous experiences. This finding underscores the need for future research in this rare disease, still characterised by a heavy burden and poor prognosis. We observed longer survival in subjects achieving response to ICT. The overall treatment safety is acceptable.

The SINTART 1 study. A phase II non-randomised controlled trial of induction chemotherapy, surgery, photon-, proton- and carbon ion-based radiotherapy integration in patients with locally advanced resectable sinonasal tumours.

PURPOSE: Sinonasal tumours are rare diseases with poor prognosis. Multimodal approach including surgery is widely used, although no standard therapy has been established in prospective trials. This study assessed activity and safety of an innovative integration of multimodality treatment-induction chemotherapy (ICT), surgery and radiotherapy (RT)-modulated by histology and response to ICT. METHODS: Patients with untreated, operable sinonasal tumours with selected histotypes (squamous cell carcinoma, intestinal-type adenocarcinoma, sinonasal undifferentiated and neuroendocrine carcinoma, olfactory neuroblastoma) were enrolled in a single-arm, phase II, multicenter clinical trial. Patients were treated with up to 5 ICT cycles, whose regimen was selected according to histotype, followed either by curative chemo-RT for pts with ≥80% reduction of initial tumour diameter or surgery and adjuvant (chemo)RT. Photon and/or proton/carbon ion-based RT was employed according to the disease site and stage. Primary end-point was 5-year progression-free survival (PFS), secondary end-points were overall survival (OS), ICT objective response rate (ORR) per RECIST 1.1 and safety. RESULTS: Thirty-five patients were evaluable for primary end-point. Fourteen patients (40%) were treated with definitive (CT)RT and 20 (57%) underwent surgery. Five-year PFS was 38% (95% confidence interval [CI], 21-69), with a median PFS of 26 months. Five-year OS was 46% (95% CI, 28-75), with a median OS of 36 months. Three-year PFS-OS for pts achieving PR/CR versus stable disease (SD)/PD to ICT were 49.8-57% versus 43.2-53%, respectively. Three-year PFS for patients achieving major volumetric partial response (≥80% reduction of initial tumour volume, major partial volumetric response [mPRv]) versus non-mPRv were 82% versus 28% and 3-year OS were 92% versus 36% (p value 0.010 and 0.029, respectively). The ORR to ICT was 54% and 60% across all histotypes and in the sinonasal undifferentiated carcinoma (SNUC) subpopulation, respectively, with 6/15 SNUCs (40%) achieving mPRv. CONCLUSION: Treatment of advanced sinonasal cancer with histology-driven ICT followed by (CT)RT in responsive patients was feasible. Overall, these findings suggest a possible role of ICT as the primary approach in newly diagnosed, resectable sinonasal tumours-especially SNUC-to select patients with favourable prognosis. Histology heterogeneity limits generalisation of trial results.

Prognostic radiomic signature for head and neck cancer: Development and validation on a multi-centric MRI dataset.

BACKGROUND AND PURPOSE: Prognosis in locally advanced head and neck cancer (HNC) is currently based on TNM staging system and tumor subsite. However, quantitative imaging features (i.e., radiomic features) from magnetic resonance imaging (MRI) may provide additional prognostic info. The aim of this work is to develop and validate an MRI-based prognostic radiomic signature for locally advanced HNC. MATERIALS AND METHODS: Radiomic features were extracted from T1- and T2-weighted MRI (T1w and T2w) using the segmentation of the primary tumor as mask. In total 1072 features (536 per image type) were extracted for each tumor. A retrospective multi-centric dataset (n = 285) was used for features selection and model training. The selected features were used to fit a Cox proportional hazard regression model for overall survival (OS) that outputs the radiomic signature. The signature was then validated on a prospective multi-centric dataset (n = 234). Prognostic performance for OS and disease-free survival (DFS) was evaluated using C-index. Additional prognostic value of the radiomic signature was explored. RESULTS: The radiomic signature had C-index = 0.64 for OS and C-index = 0.60 for DFS in the validation set. The addition of the radiomic signature to other clinical features (TNM staging and tumor subsite) increased prognostic ability for both OS (HPV- C-index 0.63 to 0.65; HPV+ C-index 0.75 to 0.80) and DFS (HPV- C-index 0.58 to 0.61; HPV+ C-index 0.64 to 0.65). CONCLUSION: An MRI-based prognostic radiomic signature was developed and prospectively validated. Such signature can successfully integrate clinical factors in both HPV+ and HPV- tumors.

STYLE (NCT03449173): A Phase 2 Trial of Sunitinib in Patients With Type B3 Thymoma or Thymic Carcinoma in Second and Further Lines.

INTRODUCTION: Thymic malignancies are rare tumors with few therapeutic options. The STYLE trial was aimed to evaluate activity and safety of sunitinib in advanced or recurrent type B3 thymoma (T) and thymic carcinoma (TC). METHODS: In this multicenter, Simon 2 stages, phase 2 trial, patients with pretreated T or TC were enrolled in two cohorts and assessed separately. Sunitinib was administered 50 mg daily for 4 weeks, followed by a 2-week rest period (schedule 4/2), until disease progression or unacceptable toxicity. The primary endpoint was objective response rate (ORR). Progression-free survival, overall survival, disease control rate and safety were secondary endpoints. RESULTS: From March 2017 to January 2022, 12 patients with T and 32 patients with TC were enrolled. At stage 1, ORR was 0% (90% confidence interval [CI]: 0.0-22.1) in T and 16.7% (90% CI: 3.1-43.8) in TC, so the T cohort was closed. At stage 2, the primary endpoint was met for TC with ORR of 21.7% (90% CI: 9.0%-40.4%). In the intention-to-treat analysis, disease control rate was 91.7% (95% CI: 61.5%-99.8%) in Ts and 89.3% (95% CI: 71.8%-97.7%) in TCs. Median progression-free survival was 7.7 months (95% CI: 2.4-45.5) in Ts and 8.8 months (95% CI: 5.3-11.1) in TCs; median overall survival was 47.9 months (95% CI: 4.5-not reached) in Ts and 27.8 months (95% CI: 13.2-53.2) in TCs. Adverse events occurred in 91.7% Ts and 93.5% TCs. Grade 3 or greater treatment-related adverse events were reported in 25.0% Ts and 51.6% TCs. CONCLUSIONS: This trial confirms the activity of sunitinib in patients with TC, supporting its use as a second-line treatment, albeit with potential toxicity that requires dose adjustment.

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.

The Interplay between Age and Viral Status in EBV-Related Nasopharyngeal and HPV-Related Oropharyngeal Carcinoma Patients.

Background. The aim of this work was to analyze the interplay between age and viral status on the outcomes in loco-regionally advanced oropharyngeal and nasopharyngeal cancer patients treated with radiotherapy and different chemotherapy combinations. Methods. A retrospective (2006−2017) analysis was performed on non-metastatic loco-regionally advanced oropharyngeal (both HPV+ and HPV−) and EBV+ nasopharyngeal cancer patients (young: <65 years vs. elderly: ≥65 years) treated with radiotherapy with or without chemotherapy. The impact of age and viral status on overall (OS) and disease-free survival (DFS) were studied with multivariable models, which were adjusted for smoking, stage, comorbidities, chemotherapy dose intensity and treatment strategy. Results. We analyzed 324 patients (146 HPV+ oropharynx, 63 HPV−, 115 nasopharynx). Elderly patients had more comorbidities, and received less intensive treatments when compared to younger subjects. Although OS and DFS were shorter in older patients, after adjustment for stage, smoking, comorbidities, treatment strategy and dose intensity, no significant differences in terms of survival were observed according to age (65 vs. 50 years of age: HR 1.89, 95% CI 0.45−7.84 for HPV+ OPC; HR 0.91, 95% CI 0.29−2.89 for HPV− OPC; HR 1.99, 95% CI 0.9−4.39 for NPC; p = 0.395). Conclusions. Several potential age-related (comorbidities, treatment intensity) and disease-related (stage) confounding factors play a prognostic role with differential impacts on both virus and non-virus-related tumors. In HPV+ oropharyngeal cancer and in EBV+ nasopharyngeal cancer patients, age should be considered as the expression of an array of host- and tumor-related features rather than an independent prognostic factor.

Relapsing pediatric non-rhabdomyosarcoma soft tissue sarcomas: The impact of routine imaging surveillance on early detection and post-relapse survival.

PURPOSE: The chances of patients with relapsing pediatric non-rhabdomyosarcoma soft tissue sarcomas (NRSTS) being cured are limited. This retrospective single-institutional study examines the potential role of routine surveillance imaging for detecting recurrent tumor, and its impact on post-relapse survival. METHODS: The analysis concerned 86 patients < 21 years old with relapsing NRSTS treated from 1985 to 2020. Clinical findings, treatment modalities and survival were analyzed, comparing patients whose relapse was first suspected from symptoms (symptomatic group) with those whose relapse was detected by radiological surveillance (imaging group). RESULTS: Tumor relapses were identified from clinical symptoms in 49 cases and on routine imaging in 37. Time to relapse was similar in the two groups. Routine imaging detected 6/32 local relapses and 31/48 distant relapses (and 79% of the cases of lung metastases). Overall survival (OS) at 5 years was 34.3% for the symptomatic group, and 24.0% for the imaging group (p-value 0.270). In patients with lung metastases at relapse, the 5-year OS was statistically better for the imaging group, that is, 25.8% versus 0% for the symptomatic group (p-value 0.044). CONCLUSION: This is the first study to explore the role of surveillance imaging in pediatric NRSTS. Judging from our findings, the value of routine scanning of primary sites seems limited, while radiological surveillance may help to detect lung metastases, improving survival for this patient category. The potentially negative effects of periodic radiological exams should be considered in deciding the optimal follow-up for patients off therapy.

Case Report: Exceptional Response to Poziotinib in Patient with Metastatic Non-Small Cell Lung Cancer With EGFR Exon 20 Insertion Mutation.

Among the several next-generation tyrosine kinase inhibitors (TKIs) tested against uncommon EFGR alterations, poziotinib has been demonstrated to be a powerful agent for metastatic non-small-cell lung cancer (mNSCLC) with aberrations in HER2 exon 20, and FDA approval is being sought in the previously-treated population. Poziotinib has also shown activity in mNSCLC with aberrations in EGFR exon 20. Herein, we report the first published case of a patient affected by mNSCLC harbouring an EGFR exon 20 insertion (EGFRex20ins) mutation who achieved a complete response (CR) under treatment with poziotinib as part of the ZENITH20 trial. In January 2021, a former smoker 62-year-old female patient was diagnosed with relapse, after two surgeries and post-operative chemotherapy of mNSCLC, at liver and retroperitoneal nodes. Given the identification by Next Generation Sequencing (NGS) of EGFRex20ins mutation, she was enrolled in ZENITH20-cohort 5 trial, a phase 2 multicentre study aimed to assess the efficacy and safety of poziotinib in patients with EGFR or HER2 exon 20 insertion mutations. Poziotinib as first-line systemic therapy for metastatic disease was initiated at the end of January 2021 and administrated at the initial dosage of 8 mg orally twice daily (BID). The most common side effects from the beginning of the treatment included alopecia, macular skin rash, diarrhoea, xerostomia, and conjunctivitis. Due to these adverse events, poziotinib was discontinued during the first 3 months and then reduced to 6 mg orally BID in April 2021. After the dose de-escalation, the adverse events ameliorated, and the patient better tolerated the treatment without further interruption. Since the first reevaluation (after 4 weeks of therapy), the treatment with poziotinib resulted to be remarkably effective, with a partial response (PR) subsequently confirmed in May and July 2021. Then, in October 2021, a CT scan confirmed a CR, maintained with good tolerance at the last reevaluation in February 2022. Treatment is still ongoing at the same dosage. In this case, poziotinib has represented a successful and well-tolerated first-line treatment alternative to chemotherapy in this patient with EGFR exon 20 insertion mutated mNSCLC.

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.

Refining Tumor Treatment in Sinonasal Cancer Using Delta Radiomics of Multi-Parametric MRI after the First Cycle of Induction Chemotherapy.

BACKGROUND: Response to induction chemotherapy (IC) has been predicted in patients with sinonasal cancer using early delta radiomics obtained from T1- and T2-weighted images and apparent diffusion coefficient (ADC) maps, comparing results with early radiological evaluation by RECIST. METHODS: Fifty patients were included in the study. For each image (at baseline and after the first IC cycle), 536 radiomic features were extracted as follows: semi-supervised principal component analysis components, explaining 97% of the variance, were used together with a support vector machine (SVM) to develop a radiomic signature. One signature was developed for each sequence (T1-, T2-weighted and ADC). A multiagent decision-making algorithm was used to merge multiple signatures into one score. RESULTS: The area under the curve (AUC) for mono-modality signatures was 0.79 (CI: 0.65-0.88), 0.76 (CI: 0.62-0.87) and 0.93 (CI: 0.75-1) using T1-, T2-weighted and ADC images, respectively. The fuse signature improved the AUC when an ADC-based signature was added. Radiological prediction using RECIST criteria reached an accuracy of 0.78. CONCLUSIONS: These results suggest the importance of early delta radiomics and of ADC maps to predict the response to IC in sinonasal cancers.