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Lesions arising in or around the pineal gland comprise a heterogeneous group of pathologies ranging from benign non-neoplastic cysts to highly malignant neoplasms. Pineal cysts are frequently encountered as an incidental finding in daily radiology practice but there is no universal agreement on the criteria for, frequency of, and duration of follow-up imaging. Solid pineal neoplasms pose a diagnostic challenge owing to considerable overlap in their imaging characteristics, although a combination of radiological appearances, clinical findings, and tumour markers allows for narrowing of the differential diagnosis. In this review, we describe the radiological anatomy of the pineal region, clinical symptoms, imaging appearances, and differential diagnosis of lesions arising in this area, and highlight the clinical management of these conditions.

Background and PurposeChronic hydrocephalus may develop as a sequela of aneurysmal subarachnoid hemorrhage, requiring long-term cerebrospinal fluid shunting. Several clinical predictors of chronic hydrocephalus and shunt dependence have been proposed. However, no anatomical predictors have been identified.Materials and MethodsA retrospective cohort study was performed including 61 patients with aneurysmal subarachnoid hemorrhage. Clinical characteristics were noted for each patient including presentation World Federation of Neurosurgical Societies grade, modified Fischer grade, aneurysm characteristics, requirement for acute and chronic cerebrospinal fluid diversion, and 3-month modified Rankin scale. CT images were evaluated to determine the Evans’ index and to enumerate the number of arachnoid granulations. Association between the clinical characteristics with ventriculoperitoneal shunt insertion and the 3-month modified Rankin scale were assessed.ResultsThe initial Evans’ index was positively associated with mFisher grade and age, but not the number of arachnoid granulations. 16.4 % patients required insertion of a ventriculoperitoneal shunt. The number of arachnoid granulations were a significant negative predictor of ventriculoperitoneal shunt insertion [OR: 0.251 (95% CI:0.073-0.862; P=0.028)]. There was significant difference in the number of arachnoid granulations between those with and without ventriculoperitoneal shunt (p=0.002). No patient with greater than 4 arachnoid granulations required a ventriculoperitoneal shunt, irrespective of severity of initial grade.ConclusionArachnoid granulations may be protective against the development of shunt dependent chronic hydrocephalus after aneurysmal subarachnoid hemorrhage. This is irrespective of presenting hemorrhage severity. This is a potentially novel radiologic biomarker and anatomic predictor of shunt dependence.

Purpose To evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (

Age-related white matter hyperintensities are associated with cognitive impairment and dementia. Venous insufficiency has recently been proposed as a potential mechanism for the development of periventricular white matter hyperintensities based on the neuroanatomic distribution. The current study assesses age related changes of the internal jugular veins and its association with white matter hyperintensities. A retrospective study was performed assessing patients with computed tomography angiography (CTA) and magnetic resonance imaging (MRI) within a 4-week window. The size of the internal jugular veins, straight sinus, vein of Galen and internal cerebral veins were measured on the CT angiography. A normalized neck venous ratio was developed. Burden of white matter hyperintensities were quantified on MRI using periventricular/deep Fazekas scores. Association was assessed using correlation analysis and multrivariate linear modeling, and differences between groups were assessed using t test, ANOVA or Kruskal-Wallis test, using p 0.05 for significance. One hundred eighty-two patients were included with a mean age of 65.2 ± 16.8 (51.6% females). Age was correlated with the normalized neck venous ratio (r

OBJECTIVEOssification of pterygoalar and pterygospinous ligaments traversing the superior aspect of the infratemporal fossa results in formation of osseous bars that can obstruct percutaneous needle access to the trigeminal ganglion through the foramen ovale (FO), interfere with lateral mandibular nerve block, and impede transzygomatic surgical approaches. Presence of these ligaments has been studied on dry skulls, but description of their radiological anatomy is scarce, in particular on cross-sectional imaging. The aim of this study was to describe visualization of pterygoalar and pterygospinous bars on computed tomography (CT) and to review their prevalence and clinical significance.METHODSThe authors retrospectively reviewed 200 helical sinonasal CT scans by analyzing 0.75- to 1.0-mm axial images, maximum intensity projection (MIP) reconstructions, and volume rendered (VR) images, including views along the anticipated axis of the needle in percutaneous Hartel and submandibular approaches to the FO.RESULTSOssified pterygoalar and pterygospinous ligaments were readily identifiable on CT scans. An ossified pterygoalar ligament was demonstrated in 10 patients, including 1 individual with bilateral complete ossification (0.5%), 4 patients with unilateral complete ossification (2.0%), and 5 with incomplete unilateral ossification (2.5%). Nearly all patients with pterygoalar bars were male (90%, p < 0.01). An ossified pterygospinous ligament was seen in 35 patients, including 2 individuals with bilateral complete (1.0%), 8 with unilateral complete (4%), 8 with bilateral incomplete (4.0%), 12 with bilateral incomplete (6.0%) ossification, and 5 (2.5%) with mixed ossification (complete on one side and incomplete on the contralateral side). All pterygoalar bars interfered with a hypothetical needle access to the FO using the Hartel approach but not the submandibular approach. In contrast, 54% of complete and 24% of incomplete pterygospinous bars impeded the submandibular approach to the FO, without affecting the Hartel approach.CONCLUSIONSThis study provides the first detailed description of cross-sectional radiological and applied surgical anatomy of pterygoalar and pterygospinous bars. Our data are clinically useful during skull base imaging to predict potential obstacles to percutaneous cannulation of the FO and assist in the choice of approach, as these two variants differentially impede the Hartel and submandibular access routes. Our results can also be useful in planning surgical approaches to the skull base through the infratemporal fossa.

Cerebral metabolism is tightly regulated and fundamental for healthy neurological function. There is increasing evidence that alterations in this metabolism may be a precursor and early biomarker of later stage disease processes. Proton magnetic resonance spectroscopy (1H-MRS) is a powerful tool to non-invasively assess tissue metabolites and has many applications for studying the normal and diseased brain. However, the technique has limitations including low spatial and temporal resolution, difficulties in discriminating overlapping peaks, and challenges in assessing metabolic flux rather than steady-state concentrations. Hyperpolarized carbon-13 magnetic resonance imaging is an emerging clinical technique that may overcome some of these spatial and temporal limitations, providing novel insights into neurometabolism in both health and in pathological processes such as glioma, stroke and multiple sclerosis. This review will explore the growing body of pre-clinical data that demonstrates a potential role for the technique in assessing metabolism in the central nervous system. There are now a number of clinical studies being undertaken in this area and this review will present the emerging clinical data as well as the potential future applications of hyperpolarized 13C magnetic resonance imaging in the brain, in both clinical and pre-clinical studies.

Funder: NIHR Cambridge Biomedical Research Centre, Funder: Addenbrooke’s Charitable Trust, Funder: National Institute for Health Research (NIHR), Funder: Mark Foundation For Cancer Research, Funder: Cambridge Commonwealth, European and International Trust, Funder: Cancer Research UK, Funder: Cambridge Clinical Trials Unit, Funder: Cancer Research UK Cambridge Centre, Funder: Engineering and Physical Sciences Research Council Cancer Imaging Centre in Cambridge and Manchester, Funder: Cambridge Experimental Cancer Medicine Centre, PURPOSE: To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. METHOD: Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. RESULTS: 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (p

Infratemporal and pterygopalatine fossae (ITF and PPF) represent two complex paramedian skull base areas, which can be defined as jewelry boxes, containing a large number of neurovascular and osteomuscular structures of primary importance. They are in close communication with many craniofacial areas, such as nasal/paranasal sinuses, orbit, middle cranial fossa, and oral cavities. Therefore, they can be involved by tumoral, infective or inflammatory lesions spreading from these spaces. Moreover, they can be the primary site of the development of some primitive tumors. For the deep-seated location of ITF and PPF lesions and their close relationship with the surrounding functional neuro-vascular structures, their surgery represents a challenge. In the last decades, the introduction of the endoscope in skull base surgery has favored the development of an innovative anterior endonasal approach for ITF and PPF tumors: the transmaxillary-pterygoid, which gives a direct and straightforward route for these areas. It has demonstrated that it is effective and safe for the treatment of a large number of benign and malignant neoplasms, located in these fossae, avoiding extensive bone drilling, soft tissue demolition, possibly unaesthetic scars, and reducing the risk of neurological deficits. However, some limits, especially for vascular tumors or lesions with lateral extension, are still present. Based on the experience of our multidisciplinary team, we present our operative technique, surgical indications, and pre- and post-operative management protocol for patients with ITF and PPF tumors.

Objective: To explore translational biological and imaging biomarkers for sunitinib treatment before and after debulking nephrectomy in the NeoSun (European Union Drug Regulating Authorities Clinical Trials Database [EudraCT] number: 2005-004502-82) single-centre, single-arm, single-agent, Phase II trial. Patients and Methods: Treatment-naïve patients with metastatic renal cell carcinoma (mRCC) received 50mg once daily sunitinib for 12days pre-surgically, then post-surgery on 4 week-on, 2 week-off, repeating 6-week cycles until disease progression in a single arm phase II trial. Structural and dynamic contrast-enhanced magnet resonance imaging (DCE-MRI) and research blood sampling were performed at baseline and after 12days. Computed tomography imaging was performed at baseline and post-surgery then every two cycles. The primary endpoint was objective response rate (Response Evaluation Criteria In Solid Tumors [RECIST]) excluding the resected kidney. Secondary endpoints included changes in DCE-MRI of the tumour following pre-surgery sunitinib, overall survival (OS), progression-free survival (PFS), response duration, surgical morbidity/mortality, and toxicity. Translational and imaging endpoints were exploratory. Results: A total of 14 patients received pre-surgery sunitinib, 71% (10/14) took the planned 12 doses. All underwent nephrectomy, and 13 recommenced sunitinib postoperatively. In all, 58.3% (seven of 12) of patients achieved partial or complete response (PR or CR) (95% confidence interval 27.7–84.8%). The median OS was 33.7months and median PFS was 15.7months. Amongst those achieving a PR or CR, the median response duration was 8.7months. No unexpected surgical complications, sunitinib-related toxicities, or surgical delays occurred. Within the translational endpoints, pre-surgical sunitinib significantly increased necrosis, and reduced cluster of differentiation-31 (CD31), Ki67, circulating vascular endothelial growth factor-C (VEGF-C), and transfer constant (KTrans, measured using DCE-MRI; all P&nbsp

Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.

Funder: CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester; doi: http://dx.doi.org/10.13039/501100014679, Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266, Funder: CRUK Cambridge Centre, Funder: Addenbrooke's Charitable Trust, Cambridge University Hospitals; doi: http://dx.doi.org/10.13039/501100002927, Funder: National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre (BRC), Funder: Experimental Cancer Medicine Centre (ECMC), Funder: The Lundbeck Foundation, Funder: Evelyn Trust; doi: http://dx.doi.org/10.13039/501100004282, Funder: Mark Foundation for Integrative Cancer Research, Measurements of water diffusion with MRI have been used as a biomarker of tissue microstructure and heterogeneity. In this study, diffusion kurtosis tensor imaging (DKTI) of the brain was undertaken in 10 healthy volunteers at a clinical field strength of 3 T. Diffusion and kurtosis metrics were measured in regions-of-interest on the resulting maps and compared with quantitative analysis of normal post-mortem tissue histology from separate age-matched donors. White matter regions showed low diffusion (0.60 ± 0.04 × 10–3 mm2/s) and high kurtosis (1.17 ± 0.06), consistent with a structured heterogeneous environment comprising parallel neuronal fibres. Grey matter showed intermediate diffusion (0.80 ± 0.02 × 10–3 mm2/s) and kurtosis (0.82 ± 0.05) values. An important finding is that the subcortical regions investigated (thalamus, caudate and putamen) showed similar diffusion and kurtosis properties to white matter. Histological staining of the subcortical nuclei demonstrated that the predominant grey matter was permeated by small white matter bundles, which could account for the similar kurtosis to white matter. Quantitative histological analysis demonstrated higher mean tissue kurtosis and vector standard deviation values for white matter (1.08 and 0.81) compared to the subcortical regions (0.34 and 0.59). Mean diffusion on DKTI was positively correlated with tissue kurtosis (r = 0.82, p < 0.05) and negatively correlated with vector standard deviation (r = -0.69, p < 0.05). This study demonstrates how DKTI can be used to study regional structural variations in the cerebral tissue microenvironment and could be used to probe microstructural changes within diseased tissue in the future.

Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk.

PURPOSE: To assess the potential role of computed tomography (CT) texture analysis (CTTA) in identifying vulnerable patients with carotid artery atherosclerosis. METHODS: In this case-control pilot study, 12 patients with carotid atherosclerosis and a subsequent history of transient ischemic attack or stroke were age and sex matched with 12 control cases with asymptomatic carotid atherosclerosis (follow-up time 103.58 ± 9.2 months). CTTA was performed using a commercially available research software package (TexRAD) by an operator blinded to clinical data. CTTA comprised a filtration-histogram technique to extract features at different scales corresponding to spatial scale filter (fine = 2 mm, medium = 3 mm, coarse = 4 mm), followed by quantification using histogram-based statistical parameters: mean, kurtosis, skewness, entropy, standard deviation, and mean value of positive pixels. A single axial slice was selected to best represent the largest cross-section of the carotid bifurcation or the greatest degree of stenosis, in presence of an atherosclerotic plaque, on each side. RESULTS: CTTA revealed a statistically significant difference in skewness between symptomatic and asymptomatic patients at the medium (0.22 ± 0.35 vs - 0.18 ± 0.39, p < 0.001) and coarse (0.23 ± 0.22 vs 0.03 ± 0.29, p = 0.003) texture scales. At the fine-texture scale, skewness (0.20 ± 0.59 vs - 0.18 ± 0.58, p = 0.009) and standard deviation (366.11 ± 117.19 vs 300.37 ± 82.51, p = 0.03) were significant before correction. CONCLUSION: Our pilot study highlights the potential of CTTA to identify vulnerable patients in stroke and TIA. CT texture may have the potential to act as a novel risk stratification tool in patients with carotid atherosclerosis.

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 [...]

No abstract is available for this article.

Background Carotid artery atherosclerosis is an important cause of ischaemic stroke. In oncology, textural analysis (“radiomics”) of computed tomography (CT) images can predict the metastatic potential and prognosis of several types of malignant tumours. We investigated whether this quantitative approach could be applied in carotid artery disease. Purpose (1) To evaluate the feasibility of computed tomography angiography (CTA) texture analysis in differentiating symptomatic from asymptomatic patients. (2) To investigate whether CTA carotid texture analysis can identify culprit lesions in patients with stroke and transient ischaemic attack (TIA). Methods Carotid CTAs of consented research subjects were included in the study. Symptomatic patients had confirmed carotid artery-related ischaemic stroke or TIA in the 7 days before CTA imaging. Asymptomatic (ASX) patients had no prior stroke/TIA. Both TexRAD, a research texture analysis software, and PyRadiomics, a Python package for radiomics studies, were used to extract 99 first-order and higher-order texture features from regions-of-interest (ROI) drawn around the outer wall of the carotid artery. Single-slice analysis compared the carotid bifurcations of symptomatic and asymptomatic patients, and of culprit (CC) and non-culprit (NC) arteries in symptomatic patients. Multi-slice analysis was conducted using a 3D volume defined by ROIs drawn on 14 consecutive CT slices of 3mm thickness, covering 3cm of carotid artery. The Mann-Whitney U test was used for inter-subject comparisons (ASX vs CC; ASX vs NC) and the Wilcoxon signed-rank test was used for intra-subject comparisons (CC vs NC). A p value Results The dataset comprised 82 carotid arteries from 41 symptomatic patients (41 culprit; 41 non-culprit) and 50 carotid arteries from 25 asymptomatic patients. Single-slice analysis revealed greater homogeneity in asymptomatic carotids versus symptomatic culprit carotids (Uniformity: ASX 0.11 (0.05); CC 0.08 (0.05), p Conclusion Textural analysis of carotid CTAs reveal significant differences between symptomatic and asymptomatic patients and between culprit and non-culprit carotid arteries within symptomatic patients. This approach could be used to identify patients at high risk of further stroke for aggressive medical therapy and surveillance. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): EPVL is undertaking a PhD funded by the Cambridge School of Clinical Medicine and the Medical Research Council's Doctoral Training Partnership

Background Convolutional neural networks (CNNs), part of deep learning, are used widely for computer vision tasks and in some medical domains, such as mammography interpretation. The application of deep learning to carotid artery imaging is scarce. We investigated the ability of deep learning to correctly classify contrast CT images of the carotid arteries without the need for prior feature selection. Purpose (1) To assess the ability of deep learning to differentiate symptomatic patients (had prior stroke or transient ischaemic attack [TIA]) from asymptomatic patients (no prior stroke/TIA) using contrast CT scans alone. (2) To investigate whether deep learning can further discriminate between culprit and non-culprit carotid arteries in symptomatic patients. (3) To assess the interpretability of the deep learning models. Methods Carotid contrast CT scans of consented research subjects were included in the study. Symptomatic patients had confirmed carotid artery-related ischaemic stroke or TIA in the 7 days before CT imaging, and asymptomatic patients had no prior cerebrovascular events. The dataset comprised 1148 axial symptomatic slices (covering a 3cm area of each carotid artery in 41 patients; 41 culprit and 41 non-culprit carotids) and 700 asymptomatic slices (from the bilateral carotid arteries of 25 patients). The dataset was split such that 75% was used for training and 25% for testing. A 30x30 bounding box was used to create patches of the carotid arteries from these axial slices for use as input to the CNN, a modified VGG16 architecture initialised with ImageNet weights to leverage transfer learning (the application of a model trained in one domain to a different domain) implemented in Python. Data augmentation was applied to the training set and the model was trained for 100 epochs using a cyclic learning rate, the RMSProp optimizer and binary cross-entropy loss. Class activation heatmaps were generated using the GradCAM method to highlight the areas of the image that were most important to the model for making its classification decision. Results The deep learning model was 92% accurate in correctly identifying carotid arteries from symptomatic patients versus those from asymptomatic patients. Discriminating between culprit versus non-culprit carotid arteries in symptomatic patients alone was 71% accurate. The class activation heatmaps demonstrated how the model learnt to localise the carotid artery within the image patch, and to ignore the arterial lumen when making its classification decision. Conclusions Deep learning can be used to differentiate between symptomatic and asymptomatic carotid CT scans from stroke/TIA subjects without the need for prior feature engineering. The model learns to identify relevant features in the image that predict the patients' symptom state. If further validated, this approach could be used to identify high-risk patients for intensive medical therapy. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): EPVL is undertaking a PhD funded by the Cambridge School of Clinical Medicine and the Medical Research Council's Doctoral Training Partnership

Introduction Carotid atherosclerosis is the main cause of ischaemic stroke. Texture analysis is a radiomic approach used to quantify image heterogeneity which can predict tumour aggression in oncology. We investigated whether this method could be applied to carotid artery disease to differentiate symptomatic from asymptomatic patients and culprit from non-culprit plaques, and then whether machine learning (ML) could correctly classify plaques based on these features. Methods CT angiography (CTA) images from symptomatic patients with carotid artery-related cerebrovascular accidents (CVAs) and from asymptomatic (ASX) patients were studied. Regions-of-interest (ROIs) were drawn on 14 consecutive carotid artery CTA slices with 3mm slice thickness. PyRadiomics was used for isotropic image (1x1x1) resampling and normalisation prior to texture feature extraction from 6 different classes (Table 1). Asymptomatic carotids were compared to culprit carotids (CC), and non-culprit (NC) carotids using the Mann Whitney U test or Wilcoxon signed-rank tests as appropriate, with a p-value Results The dataset comprised 82 carotid arteries from 41 symptomatic patients (41 culprit; 41 non-culprit) and 50 carotid arteries from 25 asymptomatic patients. CC and NC carotids showed significant differences in both first- and second-order features (IH Median: CC 618 (61); NC 646 (97), p Conclusions Textural analysis combined with machine learning on carotid CT scans reveals highly significant differences between symptomatic and asymptomatic patients, and between culprit and non-culprit carotid arteries within symptomatic patients. This approach could help identify patients at high-risk of stroke for aggressive medical therapy and surveillance. Conflict of Interest None

To determine the utility of F-fluoro-L-3,4-dihydroxy-phenylalanine (F-DOPA) PET/MRI versus cross-sectional MRI alone in glioma response assessment and identify whether the two techniques demonstrate different tumour features.F-DOPA PET/MRI studies from 40 patients were analysed. Quantitative PET parameters and conventional MRI features were recorded. Tumour volume was assessed on both PET and MRI. Using dynamic susceptibility contrast perfusion-weighted imaging, maps of cerebral blood flow (CBF) and cerebral blood volume (CBV) were obtained. Within volume of tumours of tumour features and normal-appearing white matter (NAWM) drawn on MRI, standardised uptake value (SUV)max, CBF and CBV were recorded. Presence of residual active tumour was assessed by qualitative visual assessment. Receiver operating characteristic analysis was performed univariately and on parameter combination to analyse ability to determine presence/absence of disease. Reference standard for presence of viable tissue was biopsy or clinical follow-up.Median SUVmax was 3.4 for low-grade glioma (LGG) and 3.3 for high-grade glioma (HGG). There was a significant correlation between PWI parameters and WHO grade (P 0.001), but no correlation with SUVmax. Median F-DOPA volume was 8216.88 mm for HGG and 6284.94 mm for LGG; MRI volume was 6316.57 mm and 5931.55 mm, respectively. SUVmax analysis distinguished enhancing and nonenhancing components from necrosis and NAWM and demonstrated active disease in nonenhancing regions. Visually, the modalities were concordant in 37 patients. Combining the multiparametric PET/MRI approach with all available data-enhanced detection of the presence of tumour (area under the curve 0.99, P 0.01).MRI and F-DOPA are complementary modalities for assessment of tumour burden. Matching F-DOPA and MRI in assessing residual tumour volume may better delineate the radiotherapy target volume.

Purpose To compare hyperpolarized carbon 13 (13C) MRI with dynamic contrast material–enhanced (DCE) MRI in the detection of early treatment response in breast cancer. Materials and Methods In this institutional review board–approved prospective study, a woman with triple-negative breast cancer (age, 49 years) underwent 13C MRI after injection of hyperpolarized [1–carbon 13 {13C}]-pyruvate and DCE MRI at 3 T at baseline and after one cycle of neoadjuvant therapy. The 13C-labeled lactate-to-pyruvate ratio derived from hyperpolarized 13C MRI and the pharmacokinetic parameters transfer constant (Ktrans) and washout parameter (kep) derived from DCE MRI were compared before and after treatment. Results Exchange of the 13C label between injected hyperpolarized [1-13C]-pyruvate and the endogenous lactate pool was observed, catalyzed by the enzyme lactate dehydrogenase. After one cycle of neoadjuvant chemotherapy, a 34% reduction in the 13C-labeled lactate-to-pyruvate ratio resulted in correct identification of the patient as a responder to therapy, which was subsequently confirmed via a complete pathologic response. However, DCE MRI showed an increase in mean Ktrans (132%) and mean kep (31%), which could be incorrectly interpreted as a poor response to treatment. Conclusion Hyperpolarized 13C MRI enabled successful identification of breast cancer response after one cycle of neoadjuvant chemotherapy and may improve response prediction when used in conjunction with multiparametric proton MRI. Published under a CC BY 4.0 license.

Significance Carbon-13 MRI was used to assess exchange of hyperpolarized 13C label between injected [1-13C]pyruvate and the endogenous tumor lactate pool in breast cancer patients. Higher levels of 13C label exchange were observed in more-aggressive tumors, including all triple-negative cancers. The 13C label exchange correlated significantly with the expression of the transmembrane transporter mediating uptake of pyruvate into tumor cells and hypoxia inducible factor 1 (HIF1α), but no significant correlation with the expression of lactate dehydrogenase, the enzyme that catalyzes the exchange. The study has shown that 13C MRI can be used for metabolic imaging of breast cancer patients in the clinic, creating possibilities for noninvasive cancer monitoring in this patient group., Our purpose is to investigate the feasibility of imaging tumor metabolism in breast cancer patients using 13C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13C label exchange between injected [1-13C]pyruvate and the endogenous tumor lactate pool. Treatment-naïve breast cancer patients were recruited: four triple-negative grade 3 cancers; two invasive ductal carcinomas that were estrogen and progesterone receptor-positive (ER/PR+) and HER2/neu-negative (HER2−), one grade 2 and one grade 3; and one grade 2 ER/PR+ HER2− invasive lobular carcinoma (ILC). Dynamic 13C MRSI was performed following injection of hyperpolarized [1-13C]pyruvate. Expression of lactate dehydrogenase A (LDHA), which catalyzes 13C label exchange between pyruvate and lactate, hypoxia-inducible factor-1 (HIF1α), and the monocarboxylate transporters MCT1 and MCT4 were quantified using immunohistochemistry and RNA sequencing. We have demonstrated the feasibility and safety of hyperpolarized 13C MRI in early breast cancer. Both intertumoral and intratumoral heterogeneity of the hyperpolarized pyruvate and lactate signals were observed. The lactate-to-pyruvate signal ratio (LAC/PYR) ranged from 0.021 to 0.473 across the tumor subtypes (mean ± SD: 0.145 ± 0.164), and a lactate signal was observed in all of the grade 3 tumors. The LAC/PYR was significantly correlated with tumor volume (R = 0.903, P = 0.005) and MCT 1 (R = 0.85, P = 0.032) and HIF1α expression (R = 0.83, P = 0.043). Imaging of hyperpolarized [1-13C]pyruvate metabolism in breast cancer is feasible and demonstrated significant intertumoral and intratumoral metabolic heterogeneity, where lactate labeling correlated with MCT1 expression and hypoxia.

Anatomic connections between the cerebral lateral and third ventricles have been mischaracterized since Monro's original erroneous description of his eponymous foramina (FoMs) as being only one T-shaped passage. Accurate knowledge of the in vivo three-dimensional (3D) configuration of FoM has important clinical neuroendoscopic, neurosurgical, and neuroimaging implications. We retrospectively analyzed volumetric high-resolution brain magnetic resonance imaging of 100 normal individuals to characterize the normal spatial anatomy and morphometry for each FoM. We measured the true anatomical 3D angulations of FoMs relative to standard neuroimaging orthogonal planes, and their minimum width, depth, and distance between the medial borders of bilateral FoMs. The right and left FoMs were separate, distinct, and in a V-shaped configuration. Each FoM was a round, oval, or crescent-shaped canal-like passage with well-defined borders formed by the semicircular concavity of the ipsilateral forniceal column. The plane of FoM was angled on average 56.8° ± 9.1° superiorly from the axial plane, 22.5° ± 10.7° laterally, and 37.0° ± 6.9° anteriorly from the midsagittal plane; all these angles changing significantly with increasing age. The mean narrowest diameter of FoM was 2.8 ± 1.2 mm, and its depth was 2.5 ± 0.2 mm. Thus, the true size and orientation of FoM differs from that depicted on standard neuroimaging. Notably, in young subjects, FoM has a diameter smaller than its depth, a configuration akin to a short, small canal. We propose that the eponym "Monro" no longer be associated with this structure, and the term "foramen" be abandoned. Instead, FoM should be more appropriately renamed as the "interventricular canaliculus," or IVC, for short.

Mood disorders (MD) are important and frequent psychiatric illness. The management of patients affected by these conditions represents an important factor of disability as well as a significant social and economic burden. The "in-vivo" studies can help researchers to understand the first developmental events of the pathology and to identify the molecular and non-molecular targets of therapies. However, they have strong limitations due to the fact that human brain circuitry can not be reproduced in animal models. In addition, these neural pathways are difficult to be selectively studied with the modern imaging (such as Magnetic Resonance and Positron Emitted Tomography/Computed Tomography) and non-imaging (such as electroencephalography, magnetoencephalography, transcranial magnetic stimulation and evoked potentials) methods. In comparison with other methods, the "in-vivo" imaging investigations have higher temporal and spatial resolution compared to the "in-vivo" non-imaging techniques. All these factors make difficult to fully understand the aetiology and pathophysiology of these disorders, and consequently hinder the analysis of the effects of pharmacological and non-pharmacological therapies, which have been demonstrated effective in clinical settings. In this review, we will focus our attention on the current state of the art of imaging in the assessment of treatment efficacy in MD. We will analyse briefly the actual classification of MD; then we will focus on the "in vivo" imaging methods used in research and clinical activity, the current knowledge about the neural models at the base of MD. Finally the last part of the review will focus on the analysis of the main markers of response to treatment.

Purpose: The aim of the study is to report radiological findings and features in advanced decomposed bodies obtained by post-mortem computed tomography (PMCT) with autopsy correlation. Materials and methods: This retrospective descriptive multicentric study included 41 forensic cases examined between May 2013 and November 2016. All the bodies were PMCT-scanned prior to autopsy, and internal putrefactive state was determined using the radiological alteration index (RAI) by a radiologist with expertise in forensic radiology and a forensic pathologist trained in forensic imaging. After PMCT scans, grade of external putrefaction (GEP) was assigned during the external examination and the complete autopsy was performed by forensic pathologists. Results: The PMCT images evaluation revealed that the RAI index was > 61 in all bodies, corresponding to a moderate-massive presence of putrefactive gas. The gas grade was > II in correspondence of the major vessels, heart cavities, liver parenchyma, vertebra L3 and subcutaneous pectoral tissues, and varied from I to III in correspondence of the kidney. Cadaveric external examination revealed the presence of advanced transformative phenomena, with a GEP3 and GEP4 in most of the cases, with body swelling, eyes and tongue protrusion, body fluids expulsion and fat liquefaction. Conclusion: Radiological imaging by PMCT as an adjunct to autopsy in advanced decomposed bodies represents a useful tool in detecting post-mortem gas, even in very small amounts. A correct interpretation process of the PMCT data is essential to avoid images pitfalls, due to natural decomposition that can be mistaken for pathologic processes.

The concentration of sodium ions (Na(+)) is raised in solid tumours and can be measured at the cellular, tissue and patient levels. At the cellular level, the Na(+) gradient across the membrane powers the transport of H(+) ions and essential nutrients for normal activity. The maintenance of the Na(+) gradient requires a large proportion of the cell's ATP. Na(+) is a major contributor to the osmolarity of the tumour microenvironment, which affects cell volume and metabolism as well as immune function. Here, we review evidence indicating that Na(+) handling is altered in tumours, explore our current understanding of the mechanisms that may underlie these alterations and consider the potential consequences for cancer progression. Dysregulated Na(+) balance in tumours may open opportunities for new imaging biomarkers and re-purposing of drugs for treatment.

Sophisticated volume measurements of brain structures on magnetic resonance imaging (MRI) may improve specificity in determining long-term progression of multiple sclerosis (MS), but these techniques are laborious. The optic chiasm (OC) is a white matter (WM) structure clearly visible on a routine MRI and is related to the optic nerves (ONs), which are known to atrophy in MS. We hypothesized that OC morphometric measurements would show OC atrophy in MS compared to normal patients. If so, this could help establish a novel simplified brain MRI measure of WM atrophy in MS patients. We retrospectively evaluated standard brain MRIs of 97 patients with known MS and 98 normal individuals. We electronically measured eight OC morphometrics on axial T2WIs and midsagittal T1WIs: OC width and anteroposterior (AP) diameter, diameters of each ON and optic tract (OT), and angles between the ONs or OTs. Mean OC width, AP diameter, and height in MS patients were 11.83 ± 1.25 mm (95% CI 11.58–12.09), 2.99 ± 0.65 mm (95% CI 2.85–3.12), and 2.09 ± 0.37 mm (95% CI 2–2.19), respectively. In normal individuals, they were 12.1 ± 1.4 mm (95% CI 11.78–12.34), 3.43 ± 0.63 mm (95% CI 3.3–3.58), and 2.15 ± 0.37 mm (95% CI 2.07–2.23), respectively. There were statistically significant differences between MS patients and controls for AP diameter (P = 0.000), but not for width (P = 0.204) or height (P = 0.183). The ONs were significantly smaller in MS (P < 0.0017), but not the OTs. Thus, the OC is significantly atrophied in an unstratified cohort of MS patients. Future studies may establish an MRI OC morphometric index to evaluate demyelinating disease in the brain. Clin. Anat. 32:1072–1081, 2019. © 2019 Wiley Periodicals, Inc.

Purpose This prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region. Methods Fourteen consecutive treatment-naïve patients (43.5 years ± 15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size. Results VERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13 ± 0.07 vs. 0.08 ± 0.02, respectively; p = 0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88 ± 0.07 vs. 0.92 ± 0.04, respectively; p = 0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22 ± 0.13 × 10−3 mm2/s vs. 0.98 ± 0.38 × 10−3 mm2/s, respectively; p = 0.18). Conclusion This feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future. Key Points • VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale. Electronic supplementary material The online version of this article (10.1007/s00330-019-6011-8) contains supplementary material, which is available to authorized users.

Objectives To assess whether there is mid-term reorganization in brain networks connectivity after Carotid Endarterectomy (CEA) using resting state functional connectivity Magnetic Resonance (fc-rsMR), with a special focus on the Default Mode Network (DMN). Materials and methods In this prospective exploratory study, 14 asymptomatic consecutive patients (10 males and 4 females, mean age 73.5) with unilateral, significant ICA stenosis eligible for CEA according to European Society for Vascular Surgery guidelines were prospectively recruited. The week before CEA procedure, each patient underwent both neurocognitive and rs-fcMR evaluations on the same day; the neurocognitive test consisted on a Mini Mental State Examination (MMSE). The same neurocognitive test and rs-fcMR examination were repeated on follow-up between 3–6 months after CEA. MMSE scores were compared using paired T-Student Test. Rs-fcMR Region Of Interest (ROI-to-ROI) and Seed-to-voxel group analysis were conducted using the CONN toolbox v18 and the SPM 12 software. Results Patients showed improvements in MMSE scores from before to after CEA (p-value = 0.0001). ROI-to-ROI analysis revealed several statistically significant connectivity changes following CEA, both in terms of positive and negative correlations; Seed-to-Voxel focusing on DMN revealed increased connectivity between medial prefrontal cortex (mPFC) and three different clusters of voxels. Conclusions CEA procedure is associated with an improvement in neurocognitive performance (according to MMSE testing) and reorganization of functional connectivity, including the DMN. These results represent a starting point in order to design further studies for a better understanding of the reorganization of brain networks following CEA, and to investigate the potential role of CEA as a therapeutic procedure for cognitive impairments in selected patients with critical ICA stenosis.