In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases.

The risk of radiation-induced toxicity in patients treated for head and neck (HN) cancer with radiation therapy (RT) is traditionally estimated by condensing the 3D dose distribution into a monodimensional cumulative dose-volume histogram which disregards information on dose localization. We hypothesized that a voxel-based approach would identify correlations between radiation-induced morbidity and local dose release, thus providing a new insight into spatial signature of radiation sensitivity in composite regions like the HN district. This methodology was applied to a cohort of HN cancer patients treated with RT at risk of radiation-induced acute dysphagia (RIAD). We implemented an inter-patient elastic image registration framework that proved robust enough to match even the most elusive HN structures and to provide accurate dose warping. A voxel-based statistical analysis was then performed to test regional dosimetric differences between patients with and without RIAD. We identified a significantly higher dose delivered to RIAD patients in two voxel clusters in correspondence of the cricopharyngeus muscle and cervical esophagus. Our study goes beyond the well-established organ-based philosophy exploring the relationship between radiation-induced morbidity and local dose differences in the HN region. This approach is generally applicable to different HN toxicity endpoints and is not specific to RIAD.

Differentiating between cancerous tissue and healthy liver parenchyma could represent a challenge with the only conventional Magnetic Resonance (MR) imaging. Diffusion weighted imaging (DWI) exploits different tissue characteristics to conventional Magnetic Resonance Imaging (MRI) sequences that enhance hepatocellular carcinoma (HCC) detection, characterization, and post-treatment evaluation. Detection of HCC is improved by DWI, infact this technology increases conspicuity of lesions that might otherwise not be identified due to obscuration by adjacent vessels or due to low contrast between the lesion and background liver. It is important to remember that DWI combined with contrast-enhanced MRI has higher sensitivity than DWI alone, and that some patients are not eligible for use of contrast on CT and MRI; in these patients DWI has a prominent role. MRI has advanced beyond structural anatomic imaging to now showing pathophysiologic processes. DWI is a promising way to characterize lesions utilizing the inherent contrast within the liver and has the benefit of not requiring contrast injection. DWI improves detection and characterization of HCC. Proposed clinical uses for DWI include: assessing prognosis, predicting response, monitoring response to therapy, and distinguishing tumor recurrence from treatment effect. Ideally, DWI will help risk stratify patients and will participate in prognostic modeling.

BACKGROUND AND PURPOSE: Modifications of magnetic susceptibility have been consistently demonstrated in the subcortical gray matter of MS patients, but some uncertainties remain concerning the underlying neurobiological processes and their clinical relevance. We applied quantitative susceptibility mapping and longitudinal relaxation rate relaxometry to clarify the relative contribution of atrophy and iron and myelin changes to deep gray matter damage and disability in MS. MATERIALS AND METHODS: Quantitative susceptibility mapping and longitudinal relaxation rate maps were computed for 91 patients and 55 healthy controls from MR images acquired at 3T. Applying an external model, we estimated iron and myelin concentration maps for all subjects. Subsequently, changes of deep gray matter iron and myelin concentration (atrophy-dependent) and content (atrophy-independent) were investigated globally (bulk analysis) and regionally (voxel-based and atlas-based thalamic subnuclei analyses). The clinical impact of the observed MRI modifications was evaluated via regression models. RESULTS: We identified reduced thalamic (P < .001) and increased pallidal (P < .001) mean iron concentrations in patients with MS versus controls. Global myelin and iron content in the basal ganglia did not differ between the two groups, while actual iron depletion was present in the thalamus (P < .001). Regionally, patients showed increased iron concentration in the basal ganglia (P ≤ .001) and reduced iron and myelin content in thalamic posterior-medial regions (P ≤ .004), particularly in the pulvinar (P ≤ .001). Disability was predicted by thalamic volume (B = –0.341, P = .02), iron concentration (B = -0.379, P = .005) and content (B = –0.406, P = .009), as well as pulvinar iron (B = –0.415, P = .003) and myelin (B = −0.415, P = .02) content, independent of atrophy. CONCLUSIONS: Quantitative MRI suggests an atrophy-related iron increase within the basal ganglia of patients with MS, along with an atrophy-independent reduction of thalamic iron and myelin correlating with disability. Absolute depletions of thalamic iron and myelin may represent sensitive markers of subcortical GM damage, which add to the clinical impact of thalamic atrophy in MS.