Whole-body magnetic resonance imaging (WB-MRI) for cancer screening in asymptomatic subjects of the general population: review and recommendations.

BACKGROUND:The number of studies describing the use of whole-body magnetic resonance imaging (WB-MRI) for screening of malignant tumours in asymptomatic subjects is increasing. Our aim is to review the methodologies used and the results of the published studies on per patient and per lesion analysis, and to provide recommendations on the use of WB-MRI for cancer screening. MAIN BODY:We identified 12 studies, encompassing 6214 WB-MRI examinations, which provided the rates of abnormal findings and findings suspicious for cancer in asymptomatic subjects, from the general population. Eleven of 12 studies provided imaging protocols that included T1- and T2-weighted sequences, while only five included diffusion weighted imaging (DWI) of the whole body. Different categorical systems were used for the classification and the management of abnormal findings. Of 17,961 abnormal findings reported, 91% were benign, while 9% were oncologically relevant, requiring further investigations, and 0.5% of lesions were suspicious for cancer. A per-subject analysis showed that just 5% of subjects had no abnormal findings, while 95% had abnormal findings. Findings requiring further investigation were reported in 30% of all subjects, though in only 1.8% cancer was suspected. The overall rate of histologically confirmed cancer was 1.1%. CONCLUSION:WB-MRI studies of cancer screening in the asymptomatic general population are too heterogeneous to draw impactful conclusions regarding efficacy. A 5-point lesion scale based on the oncological relevance of findings appears the most appropriate for risk-based management stratification. WB-MRI examinations should be reported by experienced oncological radiologists versed on WB-MRI reading abnormalities and on onward referral pathways

Immunogenicity comparison of interferon beta-1a preparations using the BALB/c mouse model: assessment of a new formulation for use in multiple sclerosis

The in vivo immunogenicity of a new interferon (IFN) beta-1a product (Rebif New Formulation; RNF) was compared with that of two approved recombinant human IFN beta-1a products (Rebif and Avonex). Immunogenic potential was assessed based on time to development of neutralizing antibodies (NAbs) and NAb titer. Female BALB/c mice (six in each group) received RNF, Rebif or Avonex (1.0 microg/mL subcutaneously three times weekly), and serum samples collected on Days 7, 21, and 35 (Study 1), or 28, 42, 49, and 60 (Study 2) were assayed for NAbs. In Study 1, no mice had NAbs at Day 7, but by Day 21 one mouse in the RNF group had NAbs, compared with three and four mice in the Rebif and Avonex groups, respectively. Results were similar in Study 2. All control mice were NAb negative; all actively treated mice had NAbs by day 35 or 42. Throughout Study 1, NAb titers were lowest in the RNF group and highest in the Avonex group, and at day 35, NAb titers were significantly lower in the RNF group than the Rebif group (p = 0.037). Results indicate that, on a gram-for-gram basis, RNF appears less immunogenic than Rebif or Avonex

Association of a CT-Based Clinical and Radiomics Score of Non-Small Cell Lung Cancer (NSCLC) with Lymph Node Status and Overall Survival

Background: To evaluate whether a model based on radiomic and clinical features may be associated with lymph node (LN) status and overall survival (OS) in lung cancer (LC) patients; to evaluate whether CT reconstruction algorithms may influence the model performance. Methods: patients operated on for LC with a pathological stage up to T3N1 were retrospectively selected and divided into training and validation sets. For the prediction of positive LNs and OS, the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression model was used; univariable and multivariable logistic regression analysis assessed the association of clinical-radiomic variables and endpoints. All tests were repeated after dividing the groups according to the CT reconstruction algorithm. p-values < 0.05 were considered significant. Results: 270 patients were included and divided into training (n = 180) and validation sets (n = 90). Transfissural extension was significantly associated with positive LNs. For OS prediction, high- and low-risk groups were different according to the radiomics score, also after dividing the two groups according to reconstruction algorithms. Conclusions: a combined clinical\u2013radiomics model was not superior to a single clinical or single radiomics model to predict positive LNs. A radiomics model was able to separate high-risk and low-risk patients for OS; CTs reconstructed with Iterative Reconstructions (IR) algorithm showed the best model performance

Association of a CT-based clinical and radiomics score of non-small cell lung cancer (NSCLC) with lymph node status and overall survival

Background: To evaluate whether a model based on radiomic and clinical features may be associated with lymph node (LN) status and overall survival (OS) in lung cancer (LC) patients; to evaluate whether CT reconstruction algorithms may influence the model performance. Methods: patients operated on for LC with a pathological stage up to T3N1 were retrospectively selected and divided into training and validation sets. For the prediction of positive LNs and OS, the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression model was used; univariable and multivariable logistic regression analysis assessed the association of clinicalradiomic variables and endpoints. All tests were repeated after dividing the groups according to the CT reconstruction algorithm. p-values < 0.05 were considered significant. Results: 270 patients were included and divided into training (n = 180) and validation sets (n = 90). Transfissural extension was significantly associated with positive LNs. For OS prediction, high-and low-risk groups were different according to the radiomics score, also after dividing the two groups according to reconstruction algorithms. Conclusions: a combined clinical\u2013radiomics model was not superior to a single clinical or single radiomics model to predict positive LNs. A radiomics model was able to separate high-risk and low-risk patients for OS; CTs reconstructed with Iterative Reconstructions (IR) algorithm showed the best model performance

Long-term outcomes of a pilot CT screening for lung cancer

Background: Low-dose computed tomography (CT) screening can detect early stage lung cancer in high-risk populations. However, no data on repeated annual screening over more than 5 years are available, and the impact of screening on lung cancer mortality is controversial. Methods: We analysed outcomes in high-risk asymptomatic volunteers (smokers and former smokers, >50 years) enrolled in a pilot study over 1 year from June 2000, who received annual low-dose CT for 7 years. Cumulative lung cancer incidence and survival were represented by Kaplan 12Meier curves. Standardized incidence and mortality ratios were used to estimate risks relative to the general Italian and US population. Results: Compliance was 86% at the end of the seventh year in 1035 recruited volunteers (71% men, mean age 58 years). Lung cancer was diagnosed in 54 (5.3%); radical surgery was possible in 48/54 (87%); 39/54 (72%) had stage I disease. Five-year survival was 63% overall, 89% for stage I cases. During 6308 person-years of observation, 47 participants had died versus 75 expected in the Italian general population standardised for age and sex. Fourteen lung cancer deaths were registered versus 27 expected in a standardised US smoker population. Conclusions: Seventy percent of screening-diagnosed patients had stage I disease, and the survival of screen-detected cancer patients was high. Lung cancer mortality was favourable compared to age- and sex-matched population of US smokers, suggesting that mortality can be lowered by screening, although larger trials with longer follow-up are necessary to confirm these findings

The added value of whole-body magnetic resonance imaging in the management of patients with advanced breast cancer

This study investigates the impact of whole-body MRI (WB-MRI) in addition to CT of chest-abdomen-pelvis (CT-CAP) and 18F-FDG PET/CT (PET/CT) on systemic treatment decisions in standard clinical practice for patients with advanced breast cancer (ABC). WB-MRI examinations in ABC patients were extracted from our WB-MRI registry (2009-2017). Patients under systemic treatment who underwent WB-MRI and a control examination (CT-CAP or PET/CT) were included. Data regarding progressive disease (PD) reported either on WB-MRI or on the control examinations were collected. Data regarding eventual change in treatment after the imaging evaluation were collected. It was finally evaluated whether the detection of PD by any of the two modalities had induced a change in treatment. Among 910 WB-MRI examinations in ABC patients, 58 had a paired control examination (16 CT-CAP and 42 PET/CT) and were analysed. In 23/58 paired examinations, additional sites of disease were reported only on WB-MRI and not on the control examination. In 17/28 paired examinations, PD was reported only on WB-MRI and not on the control examination. In 14 out of the 28 pairs of examinations that were followed by a change in treatment, PD had been reported only on WBMRI (14/28; 50%), while stable disease had been reported on the control examination

Radiomics : the facts and the challenges of image analysis

Radiomics is an emerging translational field of research aiming to extract mineable high-dimensional data from clinical images. The radiomic process can be divided into distinct steps with definable inputs and outputs, such as image acquisition and reconstruction, image segmentation, features extraction and qualification, analysis, and model building. Each step needs careful evaluation for the construction of robust and reliable models to be transferred into clinical practice for the purposes of prognosis, non-invasive disease tracking, and evaluation of disease response to treatment. After the definition of texture parameters (shape features; first-, second-, and higher-order features), we briefly discuss the origin of the term radiomics and the methods for selecting the parameters useful for a radiomic approach, including cluster analysis, principal component analysis, random forest, neural network, linear/logistic regression, and other. Reproducibility and clinical value of parameters should be firstly tested with internal cross-validation and then validated on independent external cohorts. This article summarises the major issues regarding this multi-step process, focussing in particular on challenges of the extraction of radiomic features from data sets provided by computed tomography, positron emission tomography, and magnetic resonance imaging

Radiation exposure of ovarian cancer patients : contribution of CT examinations performed on different MDCT (16 and 64 slices) scanners and image quality evaluation an observational study

The objective of this study is to compare radiation doses given to ovarian cancer patients by different computed tomographies (CTs) and to evaluate association between doses and subjective and objective image quality.CT examinations included were performed either on a 16-slice CT, equipped with automatic z-axis tube current modulation, or on a 64-slice CT, equipped with z-axis, xy-axis modulation, and adaptive statistical iterative algorithm (ASIR). Evaluation of dose included the following dose descriptors: volumetric CT dose index (CTDIvol), dose length product (DLP), and effective dose (E). Objective image noise was evaluated in abdominal aorta and liver. Subjective image quality was evaluated by assessment of image noise, spatial resolution and diagnostic acceptability.Mean and median CTDIvol, DLP, and E; correlation between CTDIvol and DLP and patients' weight; comparison of objective noise for the 2 scanners; association between dose descriptors and subjective image quality.The 64-slice CT delivered to patients 24.5% lower dose (P\u200a<\u200a0.0001) than 16-slice CT. There was a significant correlation between all dose descriptors (CTDIvol, DLP, E) and weight (P\u200a<\u200a0.0001). Objective noise was comparable for the 2 CT scanners. There was a significant correlation between dose descriptors and image noise for the 64-slice CT, and between dose descriptors and spatial resolution for the 16-slice CT.Current dose reduction systems may reduce radiation dose without significantly affecting image quality and diagnostic acceptability of CT exams

Neutralizing antibodies explain the poor clinical response to Interferon beta in a small proportion of patients with Multiple Sclerosis: a retrospective study

<p>Abstract</p> <p>Background</p> <p>Neutralizing antibodies (NAbs) against Interferon beta (IFNβ) are reported to be associated with poor clinical response to therapy in multiple sclerosis (MS) patients. We aimed to quantify the contribution of NAbs to the sub-optimal response of IFNβ treatment.</p> <p>Methods</p> <p>We studied the prevalence of NAbs in MS patients grouped according to their clinical response to IFNβ during the treatment period. Patients were classified as: group A, developing ≥ 1 relapse after the first 6 months of therapy; group B, exhibiting confirmed disability progression after the first 6 months of therapy, with or without superimposed relapses; group C, presenting a stable disease course during therapy. A cytopathic effect assay tested the presence of NAbs in a cohort of ambulatory MS patients treated with one of the available IFNβ formulations for at least one year. NAbs positivity was defined as NAbs titre ≥ 20 TRU.</p> <p>Results</p> <p>Seventeen patients (12.1%) were NAbs positive. NAbs positivity correlated with poorer clinical response (<it>p </it>< 0.04). As expected, the prevalence of NAbs was significantly lower in Group C (2.1%) than in Group A (17.0%) and Group B (17.0%). However, in the groups of patients with a poor clinical response (A, B), NAbs positivity was found only in a small proportion of patients.</p> <p>Conclusion</p> <p>The majority of patients with poor clinical response are NAbs negative suggesting that NAbs explains only partially the sub-optimal response to IFNβ.</p