Novel approaches to MRI of glioma

Gliomas are extremely heterogeneous, both morphologically and biologically, which contributes to a very poor prognosis. Current imaging of glioma is insufficient for a thorough diagnosis, therapy assessment and prognosis prediction. Moreover, refined and more sophisticated imaging technique could help in furthering our knowledge of gliomas. In order to facilitate proliferation, cancer cells undergo a change in structure and an increase in metabolism that results in distortion and disruption of tissue architecture. Gliomas are characterised by an increase in cells of variable sizes, as well as changes in the tissue microstructure. Diffusion-Weighted Imaging (DWI) and the apparent diffusion coefficient (ADC), have been extensively studied as potential imaging biomarkers for cellularity and tissue architecture. However, several studies have shown partial overlap in the measured values between tumour subtypes. Moreover, ADC is influenced by several factors and does not provide detailed information on the tissue microstructure. The Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) is a novel diffusion model that infers tissue microstructure compartment from conventional DWI measurements. This model derives metrics for the intracellular, intravascular and extracellular– extravascular spaces providing a more detailed interpretation of the tissue microstructure. To date, VERDICT has been applied to xenograft models of colorectal cancer, patient studies of prostate cancer and recently its feasibility in glioma has been shown. In this PhD I have applied a shortened version of the VERDICT method to image intratumoral and intertumoral heterogeneity in glioma. The results have also been validated with histology as part of a prospective study. Gliomas also exhibit a significant increase in mitotic activity within the tumour. The increased number of mitosis alters cell density which, in turn, affects the total concentration of tissue sodium as the concentration of tissue sodium is approximately ten-fold higher in the extracellular compared to the intracellular space. In addition, there is a decrease in Na+/K+-ATPase activity in tumours due to ATP depletion, which contributes to disturb sodium homeostasis. Non-invasive detection of 23Na with MRI has the potential to quantify sodium concentration and therefore could be an imaging probe of cell morphology and membrane function within the tumour microenvironment, as well as a method of probing tissue heterogeneity. During my PhD, a novel 23Na-MRI technique has been used to evaluate sodium distribution within glioma and in the surrounding tissue. Metabolic reprogramming is one of the major driving forces for determining glioma growth and invasion. Therefore, the non-invasive characterization of metabolic intratumoral, peritumoral and intertumoral heterogeneity in vivo could help to better stratify patients and to develop novel therapeutic strategies targeting cancer-specific metabolic pathways. 13C magnetic resonance imaging (MRI) using dynamic nuclear polarization (DNP) is a novel technique that allows non-invasive assessment of the metabolism of hyperpolarized (HP) 13C-labelled molecules in vivo, such as the exchange of [1-13C]pyruvate to [1-13C]lactate in tumours (Warburg effect). Part of my PhD has focused on developing and translating HP [1-13C]pyruvate MRI to explore metabolic reprogramming in glioma and the surrounding microenvironment. The overall aim of my PhD has been to develop novel approaches to imaging glioma with MRI to probe both the architectural and metabolic changes of Glioma. The preliminary evidence suggests that these tools can more deeply phenotype tumours than conventional imaging approaches. Although the main focus of this work has been gliomas, the techniques developed and presented here may be applied to study other pathological conditions within the brain, which raises the possibility of other potential clinical applications for this work

Imaging techniques in ALS.

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease characterized by degeneration of both upper and lower motor neuron located in the spinal cord and brainstem. Diagnosis of ALS is predominantly clinical, nevertheless, electromyography and Magnetic Resonance Imaging (MRI) may provide support. Several advanced MRI techniques have been proven useful for ALS diagnosis and, indeed, the combination of different MRI techniques demonstrated an improvement in sensitivity and specificity as far as 90%. This review focus on the imaging techniques currently used in the diagnosis and management of ALS with brief considerations on future applications

Advanced Computational Methods for Oncological Image Analysis.

The Special Issue "Advanced Computational Methods for Oncological Image Analysis", published for the Journal of Imaging, covered original research papers about state-of-the-art and novel algorithms and methodologies, as well as applications of computational methods for oncological image analysis, ranging from radiogenomics to deep learning [...]

Accuracy of MRI skeletal age estimation for subjects 12–19. Potential use for subjects of unknown age

In forensic practice, there is a growing need for accurate methods of age estimation, especially in the cases of young individuals of unknown age. Age can be estimated through somatic features that are universally considered associated with chronological age. Unfortunately, these features do not always coincide with the real chronological age: for these reasons that age determination is often very difficult. Our aim is to evaluate accuracy of skeletal age estimation using Tomei's MRI method in subjects between 12 and 19 years old for forensic purposes. Two investigators analyzed MRI images of the left hand and wrist of 77 male and 74 female caucasian subjects, without chronic diseases or developmental disorders, whose age ranged from 12 to 19 years. Skeletal maturation was determined by two operators, who analyzed all MRI images separately, in blinded fashion to the chronological age. Inter-rater agreement was measured with Pearson (R (2)) coefficient. One of the examiners repeated the evaluation after 6 months, and intraobserver variation was analyzed. Bland-Altman plots were used to determine mean differences between skeletal and chronological age. Inter-rater agreement Pearson coefficient showed a good linear correlation, respectively, 0.98 and 0.97 in males and females. Bland-Altman analysis demonstrated that the differences between chronological and skeletal age are not significant. Spearman's correlation coefficient showed good correlation between skeletal and chronological age both in females (R (2) = 0.96) and in males (R (2) = 0.94). Our results show that MRI skeletal age is a reproducible method and has good correlation with chronological age

Effects of Multi-Shell Free Water Correction on Glioma Characterization.

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity

Effects of Multi-Shell Free Water Correction on Glioma Characterization.

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity

Can unenhanced MRI of the breast replace contrast-enhanced MRI in assessing response to neoadjuvant chemotherapy?

BACKGROUND: The goals of neoadjuvant chemotherapy (NAC) are to reduce tumor volume and to offer a prognostic indicator in assessing treatment response. Contrast-enhanced magnetic resonance imaging (CE-MRI) is an established method for evaluating response to NAC in patients with breast cancer. PURPOSE: To validate the role of unenhanced MRI (ue-MRI) compared to CE-MRI for assessing response to NAC in women with breast cancer. MATERIAL AND METHODS: Seventy-one patients with ongoing NAC for breast cancer underwent MRI before, during, and at the end of NAC. Ue-MRI was performed with T2-weighted sequences with iterative decomposition of water and fat and diffusion-weighted sequences. CE-MRI was performed using three-dimensional T1-weighted sequences before and after administration of gadobenate dimeglumine. Two blinded observers rated ue-MRI and CE-MRI for the evaluation of tumor response. Statistical analysis was performed to compare lesion size and ADC values changes during therapy, as well as inter-observer agreement. RESULTS: There were no statistically significant differences between ue-MRI and CE-MRI sequences for evaluation of lesion size at baseline and after every cycle of treatment ( P > 0.05). The mean tumor ADC values at baseline and across the cycles of NAC were significantly different for the responder group. CONCLUSION: Ue-MRI can achieve similar results to CE-MRI for the assessment of tumor response to NAC. ADC values can differentiate responders from non-responders

Accuracy of gadoteridol enhanced MR-angiography in the evaluation of carotid artery stenosis

To compare image quality and diagnostic performance of Gadoteridol-enhanced MR angiography (MRA) with Gadobutrol-enhanced MRA in the evaluation of carotid artery stenosis. MRA was performed in 30 patients with carotid stenosis diagnosed at DUS. Patients were randomly assigned to group A (Gadobutrol-enhanced MRA) or group B (Gadoteridol-enhanced MRA). All examinations were performed with a 3T MR system. Image quality was assessed qualitatively by a 3-grade scale and quantitatively with SNR measurements. Diagnostic performance in the assessment of stenosis, plaque length and morphology was evaluated in the two MRA groups by accuracy calculation and RoC curves analysis using CTA as reference standard. Statistically significant differences in SNR and quality scale were evaluated by the Independent-Samples T Test and Mann–Whitney test, while the Z-statistics was used to compare diagnostic accuracy in the two groups. Image quality was graded adequate to excellent for both GBCAs, without significant differences (p = 0.165). SNR values were not significantly different in group B (Gadoteridol-enhanced MRA) as compared to group A (Gadobutrol-enhanced MRA) (89.32 ± 70.4 vs 81.09 ± 28.38; p = 0.635). Diagnostic accuracy was 94 % for the evaluation of stenosis degree and 94 % for the identification of ulcerated plaques in group A, while it was 93 % for the evaluation of stenosis degree and 76 % for the identification of ulcerated plaques in group B, without statistically significant differences (p = 0.936). No significant difference in terms of image quality and diagnostic accuracy was observed between Gadoteridol-enhanced MRA and Gadobutrol-enhanced MRA in patients undergoing evaluation of carotid stenosis

High-Resolution Steady State Magnetic Resonance Angiography of the Carotid Arteries: Are Intravascular Agents Necessary? Feasibility and Preliminary Experience With Gadobenate Dimeglumine

Purpose: To prospectively evaluate the potential of gadobenate dimeglumine for high-resolution steady-state (SS) contrast-enhanced magnetic resonance angiography (CE-MRA) of the carotid arteries as an adjunct to conventional first-pass (FP) MRA, with computed tomography angiography (CTA) and digital subtraction angiography (DSA) as reference. Materials and Methods: Institutional ethics committee approval and written informed consent were obtained. Forty consecutive patients underwent conventional FP MRA with 15 mL gadobenate dimeglumine, using a conventional 3D FLASH sequence (14 see acquisition time). Immediately afterward, SS images were obtained using a high resolution coronal 3D FLASH sequence (240 see acquisition time). All patients also underwent CTA and conventional DSA within 8 +/- 3 days. Three experienced radiologists assessed FP and SS image quality and calculated sensitivity, specificity, accuracy, and predictive values for stenosis grade and length, plaque morphology, and tandem lesions using DSA as reference. Detected stenoses were quantified and compared (Spearman rank correlation coefficient, [R(s)]. McNemar test) with DSA and CTA findings. Inter-read variability was assessed using kappa (kappa) statistics. The impact of SS acquisitions on diagnostic confidence and patient management was assessed. Results: MRA FP and SS image quality was excellent in 63 (78.8%) and 46 (57.5%) vessels, adequate in 11 (13.8%) and 20 (25.0%) vessels, and poor in 6 (7.5%) and 14 (17.5%) vessels, respectively. Area under the curve analysis revealed no significant differences between MRA FP, MRA FP + SS, and CTA for the grading of stenoses (P = 0.838; accuracy values of 97.4% 97.4%, and 98.7%, respectively). Greater accuracy (P < 0.001) was noted for FP + SS images over FP images alone for the assessment of plaque morphology (96.1% for FP + SS images vs. 83.3% for FP). Increased diagnostic confidence was noted for 49 (61.3%) vessels because of additional SS images whereas an impact on final diagnosis was noted in 8 (10%) cases. Good correlation was noted between SS image quality and impact on final diagnosis (R(s) = 0.7; P < 0.0001). Conclusion: SS imaging of the carotid arteries is feasible with gadobenate dimeglumine. The increased spatial resolution attainable allows improved evaluation of stenoses and plaque irregularity, yielding comparable diagnostic performance to that of CTA and DSA

Current State-of-the-Art of AI Methods Applied to MRI

Di Noia, C., Grist, J. T., Riemer, F., Lyasheva, M., Fabozzi, M., Castelli, M., Lodi, R., Tonon, C., Rundo, L., & Zaccagna, F. (2022). Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics, 12(9), 1-16. [2125]. https://doi.org/10.3390/diagnostics12092125Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.publishersversionpublishe