correlating imaging parameters with molecular data an integrated approach to improve the management of breast cancer patients

The goal of this review is to provide an overview of the studies aimed at integrating imaging parameters with molecular biomarkers for improving breast cancer patient's diagnosis and prognosis. The use of diagnostic imaging to extract quantitative parameters related to the morphology, metabolism, and functionality of tumors, as well as their correlation with cancer tissue biomarkers is an emerging research topic. Thanks to the development of imaging biobanks and the technological tools required for extraction of imaging parameters including radiomic features, it is possible to integrate imaging markers with genetic data. This new field of study represents the evolution of radiology–pathology correlation from an anatomic–histologic level to a genetic level, which paves new interesting perspectives for breast cancer management

Molecular technology and the recombinant TSH have changed diagnostics of thyroid carcinoma with positive I-131 whole body scan but low serum thyroglobulin.

The early detection of recurrent differentiated thyroid carcinoma (DTC) cells in the post surgery DTC patients relies on the sensitivity of measuring both the level of thyroglobulin (Tg) and 131-Iodine distribution by Whole Body Scan (WBS). Undetectable level of Tg associated with negative WBS or elevated levels of Tg associated with positive WBS ("concordant") is ordinarily indicative of either absence or presence of disease. At times, elevated level of Tg with negative WBS or low levels of Tg with positive WBS ("discordant") could also occur. In the present study, we retrospectively reviewed series of 573 patients with DTC followed in the Diagnostic Imaging and Radiotherapy of the University "Federico II" of Naples between 1993 and 1997. We focused on 9 out of 573 patients (1.56%) who had a discordant pattern with low level of Tg/positive WBS in the post-surgical follow-up. Four patients were metastatic at presentation while 5 patients with metastasis during follow-up still remained in persistently low levels of Tg (<5 ng/mL). This result does point to some flaw in the evaluation of "discordant" cases. Reviewing data previously described series by resetting cut-off values of Tg <1 ng/ml as undetectable changed the apparent "discordant" subgroup of patients into "concordant". Recent introduction of recombinant human TSH (rhTSH) to enhance the expression level of Tg brought significant increase in the sensitivity of diagnostic evaluation of thyroid cancer patients. The role of burdensome WBS in the follow up evaluation of DTC patients is significantly reduced over time especially in low-risk patients while the relevance of Tg assay is steadily increased. Sensitive Tg assays, significantly improved our ability to assess disease status in follow-up of DTC. Given the possibility of late disease relapses, the need for long-term follow-up, and reduced delay in treatment of persistent disease, there is still need for greater sensitive diagnostic tools for DTC

Soft drinks and sweeteners intake: Possible contribution to the development of metabolic syndrome and cardiovascular diseases. Beneficial or detrimental action of alternative sweeteners?

Abstract The rapid increase in obesity, metabolic syndrome, and cardiovascular diseases (CVDs) has been related to the rise in sugar-added foods and sweetened beverages consumption. An interesting approach has been to replace sugar with alternative sweeteners (AS), due to their impact on public health. Preclinical and clinical studies, which analyze the safety of AS intake, are still limited. Major pathogenic mechanisms of these substances include ROS and AGEs formation. Indeed, endothelial dysfunction involving in the pathogenesis of micro- and macro-vascular diseases is mitochondrial dysfunction dependent. Hyperglycemia and endoplasmic reticulum stress together produce ROS, contributing to the development and progression of cardiovascular complications during type 2 diabetes (T2D), thus causing oxidative changes and direct damage of lipids, proteins, and DNA. Epidemiological studies in healthy subjects have suggested that the consumption of artificial AS can promote CV complications, such as glucose intolerance and predisposition to the onset of T2D, whereas natural AS could reduce hyperglycemia, improve lipid metabolism and have antioxidant effects. Long-term prospective clinical randomized studies are needed to evaluate precisely whether exposure to alternative sugars can have clinical implications on natural history and clinical outcomes, especially in children or during the gestational period through breast milk

Investigating the Relationship between White Matter Connectivity and Motivational Circuits in Subjects with Deficit Schizophrenia: A Diffusion Tensor Imaging (DTI) Study

Deficit schizophrenia is a subtype of schizophrenia presenting primary and enduring negative symptoms (NS). Although one of the most updated hypotheses indicates a relationship between NS and impaired motivation, only a few studies have investigated abnormalities of motivational circuits in subjects with deficit schizophrenia (DS). Our aim was to investigate structural connectivity within motivational circuits in DS. We analyzed diffusion tensor imaging (DTI) data from 46 subjects with schizophrenia (SCZ) and 35 healthy controls (HCs). SCZ were classified as DS (n = 9) and nondeficit (NDS) (n = 37) using the Schedule for Deficit Syndrome. The connectivity index (CI) and the Fractional Anisotropy (FA) of the connections between selected brain areas involved in motivational circuits were examined. DS, as compared with NDS and HCs, showed increased CI between the right amygdala and dorsal anterior insular cortex and increased FA of the pathway connecting the left nucleus accumbens with the posterior insular cortex. Our results support previous evidence of distinct neurobiological alterations underlying different clinical subtypes of schizophrenia. DS, as compared with NDS and HCs, may present an altered pruning process (consistent with the hyperconnectivity) in cerebral regions involved in updating the stimulus value to guide goal-directed behavior

Poor reactivity of posterior electroencephalographic alpha rhythms during the eyes open condition in patients with dementia due to Parkinson's disease

Here, we hypothesized that the reactivity of posterior resting-state electroencephalographic (rsEEG) alpha rhythms during the transition from eyes-closed to -open condition might be lower in patients with Parkinson's disease dementia (PDD) than in patients with Alzheimer's disease dementia (ADD). A Eurasian database provided clinical-demographic-rsEEG datasets in 73 PDD patients, 35 ADD patients, and 25 matched cognitively unimpaired (Healthy) persons. The eLORETA freeware was used to estimate cortical rsEEG sources. Results showed substantial (greater than −10%) reduction (reactivity) in the posterior alpha source activities from the eyes-closed to the eyes-open condition in 88% of the Healthy seniors, 57% of the ADD patients, and only 35% of the PDD patients. In these alpha-reactive participants, there was lower reactivity in the parietal alpha source activities in the PDD group than in the healthy control seniors and the ADD patients. These results suggest that PDD patients show poor reactivity of mechanisms desynchronizing posterior rsEEG alpha rhythms in response to visual inputs. That neurophysiological biomarker may provide an endpoint for (non) pharmacological interventions for improving vigilance regulation in those patients.European Consortium of Dementia ; IRCCS San Raffaele Rome ; World Medical Association ; Ministero della Salute ; Sapienza Università di Rom

Mediastinal Images Resembling Thymus Following 131-I Treatment for Thyroid Cancer

The follow-up of Differentiated Thyroid Cancer conventionally includes serum thyroglobulin and periodic Whole Body Scans. The uptake of 131-I in normal and pathological tissues different from metastatic thyroid cancer sites is a cause of false-positive scans. Among them, mediastinal uptake caused by thymic hyperplasia can be observed. The aim of the present study was to review a series of 573 patients with differentiated thyroid cancer treated with 131-I after surgery between 1992 and 2003 looking above all for those with mediastinal images resembling thymus. This evaluation is presented together with some hypotheses on the relationships between thymus and thyroid. Moreover, some considerations are made on the differential diagnosis between thymus and mediastinal tumour thyroid residues

Progression of brain atrophy in spinocerebellar ataxia type 2: A longitudinal tensor-based morphometry study

Spinocerebellar ataxia type 2 (SCA2) is the second most frequent autosomal dominant inherited ataxia worldwide. We investigated the capability of magnetic resonance imaging (MRI) to track in vivo progression of brain atrophy in SCA2 by examining twice 10 SCA2 patients (mean interval 3.6 years) and 16 age- and gender-matched healthy controls (mean interval 3.3 years) on the same 1.5 T MRI scanner. We used T1-weighted images and tensor-based morphometry (TBM) to investigate volume changes and the Inherited Ataxia Clinical Rating Scale to assess the clinical deficit. With respect to controls, SCA2 patients showed significant higher atrophy rates in the midbrain, including substantia nigra, basis pontis, middle cerebellar peduncles and posterior medulla corresponding to the gracilis and cuneatus tracts and nuclei, cerebellar white matter (WM) and cortical gray matter (GM) in the inferior portions of the cerebellar hemisphers. No differences in WM or GM volume loss were observed in the supratentorial compartment. TBM findings did not correlate with modifications of the neurological deficit. In conclusion, MRI volumetry using TBM is capable of demonstrating the progression of pontocerebellar atrophy in SCA2, supporting a possible role of MRI as biomarker in future trials

Radiomic and genomic machine learning method performance for prostate cancer diagnosis : systematic literature review

Background Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance. Objective This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies. Methods Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies–version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I2 statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice. Results In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications. Conclusions The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers

the role of molecular and imaging biomarkers in the evaluation of inflammation in oncology

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Heart failure: Pilot transcriptomic analysis of cardiac tissue by RNA-sequencing

Background: Despite left ventricular (LV) dysfunction contributing to mortality in chronic heart failure (HF), the molecular mechanisms of LV failure continues to remain poorly understood and myocardial biomarkers have yet to be identified. The aim of this pilot study was to investigate specific transcriptome changes occurring in cardiac tissues of patients with HF compared to healthy condition patients to improve diagnosis and possible treatment of affected subjects. Methods: Unlike other studies, only dilated cardiomyopathy (DCM) (n = 2) and restrictive cardiomyopathy (RCM) (n = 2) patients who did not report family history of the disease were selected with the aim of obtaining a homogeneous population for the study. The transcriptome of all patients were studied by RNA-sequencing (RNA-Seq) and the read counts were adequately filtered and normalized using a recently developed user-friendly tool for RNA-Seq data analysis, based on a new graphical user interface (RNA-SeqGUI). Results: By using this approach in a pairwise comparison with healthy donors, we were able to identify DCM- and RCM-specific expression signatures for protein-coding genes as well as for long noncoding RNAs (lncRNAs). Differential expression of 5 genes encoding different members of the mediator complex was disclosed in this analysis. Interestingly, a significant alteration was found for genes which had never been associated with HF until now, and 27 lncRNA/mRNA pairs that were significantly altered in HF patients. Conclusions: The present findings revealed specific expression pattern of both protein-coding and lncRNAs in HF patients, confirming that new LV myocardial biomarkers could be reliably identified using Next-Generation Sequencing-based approaches