Proton Resonance Frequency Shift Thermometry: A Review of Modern Clinical Practices.

Magnetic resonance imaging (MRI) has become a popular modality in guiding minimally invasive thermal therapies, due to its advanced, nonionizing, imaging capabilities and its ability to record changes in temperature. A variety of MR thermometry techniques have been developed over the years, and proton resonance frequency (PRF) shift thermometry is the current clinical gold standard to treat a variety of cancers. It is used extensively to guide hyperthermic thermal ablation techniques such as high-intensity focused ultrasound (HIFU) and laser-induced thermal therapy (LITT). Essential attributes of PRF shift thermometry include excellent linearity with temperature, good sensitivity, and independence from tissue type. This noninvasive temperature mapping method gives accurate quantitative measures of the temperature evolution inside biological tissues. In this review, the current status and new developments in the fields of MR-guided HIFU and LITT are presented with an emphasis on breast, prostate, bone, uterine, and brain treatments. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Impaired glymphatic function and clearance of tau in an Alzheimer's disease model.

The glymphatic system, that is aquaporin 4 (AQP4) facilitated exchange of CSF with interstitial fluid (ISF), may provide a clearance pathway for protein species such as amyloid-ß and tau, which accumulate in the brain in Alzheimer's disease. Further, tau protein transference via the extracellular space, the compartment that is cleared by the glymphatic pathway, allows for its neuron-to-neuron propagation, and the regional progression of tauopathy in the disorder. The glymphatic system therefore represents an exciting new target for Alzheimer's disease. Here we aim to understand the involvement of glymphatic CSF-ISF exchange in tau pathology. First, we demonstrate impaired CSF-ISF exchange and AQP4 polarization in a mouse model of tauopathy, suggesting that this clearance pathway may have the potential to exacerbate or even induce pathogenic accumulation of tau. Subsequently, we establish the central role of AQP4 in the glymphatic clearance of tau from the brain; showing marked impaired glymphatic CSF-ISF exchange and tau protein clearance using the novel AQP4 inhibitor, TGN-020. As such, we show that this system presents as a novel druggable target for the treatment of Alzheimer's disease, and possibly other neurodegenerative diseases alike.

Differential Diagnosis of Prostate Cancer Grade to Augment Clinical Diagnosis Based on Classifier Models with Tuned Hyperparameters.

We developed a novel machine-learning algorithm to augment the clinical diagnosis of prostate cancer utilizing first and second-order texture analysis metrics in a novel application of machine-learning radiomics analysis. We successfully discriminated between significant prostate cancers versus non-tumor regions and provided accurate prediction between Gleason score cohorts with statistical sensitivity of 0.82, 0.81 and 0.91 in three separate pathology classifications. Tumor heterogeneity and prediction of the Gleason score were quantified using two feature selection approaches and two separate classifiers with tuned hyperparameters. There was a total of 71 patients analyzed in this study. Multiparametric MRI, incorporating T2WI and ADC maps, were used to derive radiomics features. Recursive feature elimination (RFE), the least absolute shrinkage and selection operator (LASSO), and two classification approaches, incorporating a support vector machine (SVM) (with randomized search) and random forest (RF) (with grid search), were utilized to differentiate between non-tumor regions and significant cancer while also predicting the Gleason score. In T2WI images, the RFE feature selection approach combined with RF and SVM classifiers outperformed LASSO with SVM and RF classifiers. The best performance was achieved by combining LASSO and SVM into a model that used both T2WI and ADC images. This model had an area under the curve (AUC) of 0.91. Radiomic features computed from ADC and T2WI images were used to predict three groups of Gleason score using two kinds of feature selection methods (RFE and LASSO), RF and SVM classifier models with tuned hyperparameters. Using combined sequences (T2WI and ADC map images) and combined radiomics (1st and GLCM features), LASSO, with a feature selection method with RF, was able to predict G3 with the highest sensitivity at a level AUC of 0.92. To predict G3 for single sequence (T2WI images) using GLCM features, LASSO with SVM achieved the highest sensitivity with an AUC of 0.92.

Whole-brain traumatic controlled cortical impact to the left frontal lobe: Magnetic resonance image-based texture analysis.

This research assesses the capability of texture analysis (TA) derived from high-resolution (HR) T2-weighted magnetic resonance imaging to identify primary sequelae following 1-5 hours of controlled cortical impact mild or severe traumatic brain injury (TBI) to the left frontal cortex (focal impact) and secondary (diffuse) sequelae in the right frontal cortex, bilateral corpus callosum, and hippocampus in rats. The TA technique comprised first-order (histogram-based) and second-order statistics (including gray-level co-occurrence matrix, gray-level run length matrix, and neighborhood gray-level difference matrix). Edema in the left frontal impact region developed within 1 hour and continued throughout the 5-hour assessments. The TA features from HR images confirmed the focal injury. There was no significant difference among radiomics features between the left and right corpus callosum or hippocampus from 1 to 5 hours following a mild or severe impact. The adjacent corpus callosum region and the distal hippocampus region (s), showed no diffuse injury 1-5 hours after mild or severe TBI. These results suggest that combining HR images with TA may enhance detection of early primary and secondary sequelae following TBI.

Quantifying Tumor Heterogeneity from Multiparametric Magnetic Resonance Imaging of Prostate Using Texture Analysis.

(1) Background: Multiparametric MRI (mp-MRI) is used to manage patients with PCa. Tumor identification via irregular sampling or biopsy is problematic and does not allow the comprehensive detection of the phenotypic and genetic alterations in a tumor. A non-invasive technique to clinically assess tumor heterogeneity is also in demand. We aimed to identify tumor heterogeneity from multiparametric magnetic resonance images using texture analysis (TA). (2) Methods: Eighteen patients with prostate cancer underwent mp-MRI scans before prostatectomy. A single radiologist matched the histopathology report to single axial slices that best depicted tumor and non-tumor regions to generate regions of interest (ROIs). First-order statistics based on the histogram analysis, including skewness, kurtosis, and entropy, were used to quantify tumor heterogeneity. We compared non-tumor regions with significant tumors, employing the two-tailed Mann-Whitney U test. Analysis of the area under the receiver operating characteristic curve (ROC-AUC) was used to determine diagnostic accuracy. (3) Results: ADC skewness for a 6 × 6 px filter was significantly lower with an ROC-AUC of 0.82 (p = 0.001). The skewness of the ADC for a 9 × 9 px filter had the second-highest result, with an ROC-AUC of 0.66; however, this was not statistically significant (p = 0.08). Furthermore, there were no substantial distinctions between pixel filter size groups from the histogram analysis, including entropy and kurtosis. (4) Conclusions: For all filter sizes, there was poor performance in terms of entropy and kurtosis histogram analyses for cancer diagnosis. Significant prostate cancer may be distinguished using a textural feature derived from ADC skewness with a 6 × 6 px filter size.

Artificial intelligence in the medical physics community: An international survey.

PURPOSE: To assess current perceptions, practices and education needs pertaining to artificial intelligence (AI) in the medical physics field. METHODS: A web-based survey was distributed to the European Federation of Organizations for Medical Physics (EFOMP) through social media and email membership list. The survey included questions about education, personal knowledge, needs, research and professionalism around AI in medical physics. Demographics information were also collected. Responses were stratified and analysed by gender, type of institution and years of experience in medical physics. Statistical significance (p<0.05) was assessed using paired t-test. RESULTS: 219 people from 31 countries took part in the survey. 81% (n = 177) of participants agreed that AI will improve the daily work of Medical Physics Experts (MPEs) and 88% (n = 193) of respondents expressed the need for MPEs of specific training on AI. The average level of AI knowledge among participants was 2.3 ± 1.0 (mean ± standard deviation) in a 1-to-5 scale and 96% (n = 210) of participants showed interest in improving their AI skills. A significantly lower AI knowledge was observed for female participants (2.0 ± 1.0), compared to male responders (2.4 ± 1.0). 64% of participants indicated that they are not involved in AI projects. The percentage of female leading AI projects was significantly lower than the male counterparts (3% vs 19%). CONCLUSIONS: AI was perceived as a positive resource to support MPEs in their daily tasks. Participants demonstrated a strong interest in improving their current AI-related skills, enhancing the need for dedicated training for MPEs.

The 10th Annual scientific Meeting of the Irish Association of physicists in medicine (IAPM ASM 2019).

The Irish Association of Physicists in Medicine (IAPM) is an association of medical physicists in Ireland. The IAPM was founded in 2010 with the merger of the Association of Physical Scientists in Medicine (APSM) and the Irish Radiotherapy Physics Group (IRPG). The 10th Annual Scientific Meeting of the IAPM was held in Dublin on 23rd March 2019. This editorial summarises the proceedings of the day including invited speakers, diagnostic imaging and radiotherapy sessions, the Young Investigator Grant, the Early Careers bursary, joint session and poster presentations. A special issue of Physica Medica was dedicated to the event featuring a number of research papers.

Biomechanical analysis of fluid percussion model of brain injury.

Fluid percussion injury (FPI) is a widely used experimental model for studying traumatic brain injury (TBI). However, little is known about how the brain mechanically responds to fluid impacts and how the mechanical pressures/strains of the brain correlate to subsequent brain damage for rodents during FPI. Hence, we developed a numerical approach to simulate FPI experiments on rats and characterize rat brain pressure/strain responses at a high resolution. A previous rat brain model was improved with a new hexahedral elements-based skull model and a new cerebrospinal fluid (CSF) layer. We validated the numerical model against experimentally measured pressures from FPI. Our results indicated that brain tissues under FPI experienced high pressures, which were slightly lower (10-20%) than input saline pressure. Interestingly, FPI was a mixed focus- and diffuse-type injury model with highest strains (12%) being concentrated in the ipsilateral cortex under the fluid-impact site and diffuse strains (5-10%) being spread to the entire brain, which was different from controlled cortical impact in which high strains decreased gradually away from the impact site.

In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis.

Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD) could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA) has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden. Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG) mice and 16 litter matched wild-type (WT) mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales), followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis). MRTA was applied to manually segmented regions of interest (ROI) drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology. Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01), the hippocampus (K, p < 0.05) and in the thalamus (K, p < 0.01). In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus. Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus) based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using routinely acquired structural MR images.

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy.

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our "in-skull" preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

Imaging the accumulation and suppression of tau pathology using multiparametric MRI.

Mouse models of Alzheimer's disease have served as valuable tools for investigating pathogenic mechanisms relating to neurodegeneration, including tau-mediated and neurofibrillary tangle pathology-a major hallmark of the disease. In this work, we have used multiparametric magnetic resonance imaging (MRI) in a longitudinal study of neurodegeneration in the rTg4510 mouse model of tauopathy, a subset of which were treated with doxycycline at different time points to suppress the tau transgene. Using this paradigm, we investigated the sensitivity of multiparametric MRI to both the accumulation and suppression of pathologic tau. Tau-related atrophy was discernible from 5.5 months within the cortex and hippocampus. We observed markedly less atrophy in the treated rTg4510 mice, which was enhanced after doxycycline intervention from 3.5 months. We also observed differences in amide proton transfer, cerebral blood flow, and diffusion tensor imaging parameters in the rTg4510 mice, which were significantly less altered after doxycycline treatment. We propose that these non-invasive MRI techniques offer insight into pathologic mechanisms underpinning Alzheimer's disease that may be important when evaluating emerging therapeutics targeting one of more of these processes.

Increased cerebral vascular reactivity in the tau expressing rTg4510 mouse: evidence against the role of tau pathology to impair vascular health in Alzheimer's disease.

Vascular abnormalities are a key feature of Alzheimer's disease (AD). Imaging of cerebral vascular reactivity (CVR) is a powerful tool to investigate vascular health in clinical populations although the cause of reduced CVR in AD patients is not fully understood. We investigated the specific role of tau pathology in CVR derangement in AD using the rTg4510 mouse model. We observed an increase in CVR in cortical regions with tau pathology. These data suggest that tau pathology alone does not produce the clinically observed decreases in CVR and implicates amyloid pathology as the dominant etiology of impaired CVR in AD patients.

Semiautomatic region-of-interest validation at the femur in (18)F-fluoride PET/CT.

UNLABELLED: The assessment of regional skeletal metabolism using (18)F-fluoride PET ((18)F-PET) requires segmentation of the tissue region of interest (ROI). The aim of this study was to validate a novel approach to define multiple ROIs at the proximal femur similar to those used in dual x-ray absorptiometry. Regions were first drawn on low-dose CT images acquired as a routine part of the PET/CT study and transferred to the (18)F-PET images for the quantitative analysis of bone turnover. METHODS: Four healthy postmenopausal women with a mean age of 65.1 y (range, 61.8-70.0 y), and with no history of metabolic bone disorder and not currently being administered treatment affecting skeletal metabolism, underwent dynamic (18)F-PET/CT at the hip with an injected activity of 180 MBq. The ROIs at the proximal femur included femoral shaft, femoral neck, and total hip and were segmented using both a semiautomatic method and manually by 8 experts at manual ROI delineation. The mean of the 8 manually drawn ROIs was considered the gold standard against which the performances of the semiautomatic and manual methods were compared in terms of percentage overlap and percentage difference. The time to draw the ROIs was also compared. RESULTS: The percentage overlaps between the gold standard and the semiautomatic ROIs for total hip, femoral neck, and femoral shaft were 86.1%, 37.8%, and 96.1%, respectively, and the percentage differences were 14.5%, 89.7%, and 4.7%, respectively. In the same order, the percentage overlap between the gold standard and the manual ROIs were 85.2%, 39.1%, and 95.2%, respectively, and the percentage differences were 19.9%, 91.6%, and 12.2%, respectively. The semiautomatic method was approximately 9.5, 2.5, and 67 times faster than the manual method for segmenting total-hip, femoral-neck, and femoral-shaft ROIs, respectively. CONCLUSION: We have developed and validated a semiautomatic procedure whereby ROIs at the hip are defined using the CT component of an (18)F-PET/CT scan. The percentage overlap and percentage difference results between the semiautomatic method and the manual method for ROI delineation were similar. Two advantages of the semiautomatic method are that it is significantly quicker and eliminates some of the variability associated with operator or reader input. The tube current used for the CT scan was associated with an effective dose 8 times lower than that associated with a typical diagnostic CT scan. These results suggest that it is possible to segment bone ROIs from low-dose CT for later transfer to PET in a single PET/CT procedure without the need for an additional high-resolution CT scan.

Applying DTI white matter orientations to finite element head models to examine diffuse TBI under high rotational accelerations.

The in-vivo mechanical response of neural tissue during impact loading of the head is simulated using geometrically accurate finite element (FE) head models. However, current FE models do not account for the anisotropic elastic material behaviour of brain tissue. In soft biological tissue, there is a correlation between internal microscopic structure and macroscopic mechanical properties. Therefore, constitutive equations are important for the numerical analysis of the soft biological tissues. By exploiting diffusion tensor techniques the anisotropic orientation of neural tissue is incorporated into a non-linear viscoelastic material model for brain tissue and implemented in an explicit FE analysis. The viscoelastic material parameters are derived from published data and the viscoelastic model is used to describe the mechanical response of brain tissue. The model is formulated in terms of a large strain viscoelastic framework and considers non-linear viscous deformations in combination with non-linear elastic behaviour. The constitutive model was applied in the University College Dublin brain trauma model (UCDBTM) (i.e. three-dimensional finite element head model) to predict the mechanical response of the intra-cranial contents due to rotational injury.

Quantitative MRI analysis of brain volume changes due to controlled cortical impact.

More than 85% of reported brain traumas are classified clinically as "mild" using the Glasgow Coma Scale (GCS); qualitative MRI findings are scarce and provide little correspondence to clinical symptoms. Our goal, therefore, was to establish in vivo sequelae of traumatic brain injury (TBI) following lower and higher levels of impact to the frontal lobe using quantitative MRI analysis and a mechanical model of penetrating impact injury. To investigate time-based morphological and physiological changes of living tissue requires a surrogate for the human central nervous system. The present model for TBI was a systematically varied and controlled cortical impact on deeply-anaesthetized Sprague-Dawley rats, that was designed to mimic different injury severities. Whole-brain MRI scans were performed on each rat prior to either a lower- or a higher-level of impact, and then at hourly intervals for 5 h post-impact. Both brain volume and specific anatomical structures were segmented from MR images for inter-subject comparisons post-registration. Animals subjected to lower and higher impact levels exhibited elevated intracranial pressure (ICP) in the low compensatory reserve (i.e., nearly exhausted), and terminal disturbance (i.e., exhausted) ranges, respectively. There was a statistically significant drop in cerebrospinal fluid (CSF) of 35% in the lower impacts, and 65% in the higher impacts, at 5 h compared to sham controls. There was a corresponding increase in corpus callosum volume starting at 1 h, of 60-110% and 30-40% following the lower- and higher-impact levels, respectively. A statistically significant change in the abnormal tissue from 2 h to 5 h was observed for both impact levels, with greater significance for higher impacts. Furthermore, a statistically significant difference between the lower impacts and the sham controls occurred at 3 h. These results are statistically substantiated by a fluctuation in the physical size of the corpus callosum, a decrease in the volume of CSF, and elevated levels of atrophy in the cerebral cortex.