Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review

Evaluation of focused ultrasound modulation of the blood-brain barrier in gray and white matter

RATIONALE

Focused ultrasound (FUS) in combination with intravenous microbubbles is being studied clinically for modulation of the blood-brain barrier. Contrast-enhanced MRI can be used to visualize the enhanced permeability resulting from the treatment. However, contrast enhancement in the white matter (WM) are inconsistently observed compared to the gray matter (GM). Intrinsic tissue differences are believed to result in reduced treatment efficacy and insufficient drug delivery to the WM. In this study we evaluate the deposition of MRI contrast and clinically relevant antineoplastics in GM and WM tissues following single and repeated FUS and microbubble treatments.

METHODS

The brains of Fischer-344 rats (n = 24) and Yorkshire pigs (n = 6) underwent FUS (rats: 580 kHz; pigs: 220 kHz) treatments targeting the internal capsule and thalamus, repeated at 30-min intervals. Definity microbubbles (rats: 20 μL/kg bolus; pigs: 4 μL/kg/5-min infusion) were administered intravenously for each sonication with MRI contrast to measure gadolinium-mediated signal change. Feedback-controlled algorithms were used to monitor treatments and modulate the pressure based on emitted microbubble signals to ensure safe and effective exposures. The delivery of methotrexate (MTX; 454.4 Da) and bevacizumab (BVZ; 149 kDa) was evaluated via immunofluorescence microscopy in rats, and respectively quantified via liquid chromatography mass spectrometry and enzyme-linked immunosorbent assay in pigs.

RESULTS

Repeated FUS exposures successfully increased the vascular permeability of both gray and white matter tissues to MRI contrast and drugs of both small and large molecular sizes. In rats, single treatments showed statistically significant higher enhancements in the GM (23.5 ± 4.3 %; WM: 4.68 ± 3.75 %), however following a second sonication there were no between-tissue differences (GM: 38.0 ± 6.4 %; WM: 34.0 ± 8.7 %). In pigs, the smaller focus size relative to the brain enabled separate targeting of GM vs WM and the treatment controller used higher average power level in the WM to achieve the same cavitation dose. This resulted in no difference in gray and white matter permeability levels (to both contrast and pharmacological agents) after a single sonication. Repeated treatments sustained MRI enhancements for a longer time and enhanced drug deposition (MTX increased 6.5 and 8.3 folds after single and repeated treatment; BVZ increased 6.8 and 20.4 folds respectively).

CONCLUSIONS

Feedback-controlled algorithms and the possibility to individually target gray and white matter highlighted the impact of tissue composition on treatment outcomes. Repeated FUS-mediated modulation of the brain microvasculature achieved higher levels of permeabilization to contrast and pharmacological agents in both gray and white matter.

Assessing the accuracy of artificial intelligence in mandibular canal segmentation compared to semi-automatic segmentation on cone-beam computed tomography images

Purpose

This study aims to assess the accuracy of artificial intelligence (AI) in mandibular canal (MC) segmentation on cone-beam computed tomography (CBCT) compared to semi-automatic segmentation. The impact of third molar status (absent, erupted, impacted) on AI performance was also evaluated.

Material and methods

A total of 150 CBCT scans (300 MCs) were retrospectively analysed. Semi-automatic MC segmentation was performed by experts using Romexis software, serving as the reference standard. AI-based segmentation was conducted using Diagnocat, an AI-driven cloud-based platform. Three-dimensional segmentation accuracy was assessed by comparing AI and semi-automatic segmentations through surface-to-surface distance metrics in Cloud Compare software. Statistical analyses included the intraclass correlation coefficient (ICC) for inter- and intra-rater reliability, Kruskal-Wallis tests for group comparisons, and Mann-Whitney U tests for post-hoc analyses.

Results

The median deviation between AI and semi-automatic MC segmentation was 0.29 mm (SD: 0.25-0.37 mm), with 88% of cases within the clinically acceptable limit (≤ 0.50 mm). Inter-rater reliability for semi-automatic segmentation was 84.5%, while intra-rater reliability reached 95.5%. AI segmentation demonstrated the highest accuracy in scans without third molars (median deviation: 0.27 mm), followed by erupted third molars (0.28 mm) and impacted third molars (0.32 mm).

Conclusions

AI demonstrated high accuracy in MC segmentation, closely matching expert-guided semi-automatic segmentation. However, segmentation errors were more frequent in cases with impacted third molars, probably due to anatomical complexity. Further optimisation of AI models using diverse training datasets and multi-centre validation is recommended to enhance reliability in complex cases.

Mild traumatic brain injury increases cortical iron: evidence from individual susceptibility mapping

Quantitative susceptibility mapping has been applied to map brain iron distribution after mild traumatic brain injury to understand properties of neural tissue which may be related to cellular dyshomeostasis. However, this is a heterogeneous injury associated with microstructural brain changes, and 'traditional' group-wise statistical approaches may lead to a loss of clinically relevant information, as subtle alterations at the individual level can be obscured by averages and confounded by within-group variability. More precise and individualized approaches are needed to characterize mild traumatic brain injury better and elucidate potential cellular mechanisms to improve intervention and rehabilitation. To address this issue, we use quantitative MRI to build individualized profiles of regional positive (iron-related) magnetic susceptibility across 34 bilateral cortical ROIs following mild traumatic brain injury. Healthy population templates were constructed for each cortical area using standardized Z-scores derived from 25 age-matched male controls aged between 16 and 32 years (M = 21.10, SD = 4.35), serving as a reference against which Z-scores of 35 males with acute (<14 days) sports-related mild traumatic brain injury were compared [M = 21.60 years (range: 16-33), SD = 4.98]. Secondary analyses sensitive to cortical depth and curvature were also generated to approximate the location of iron accumulation in the cortical laminae and the effect of gyrification. Primary analyses indicated that approximately one-third (11/35; 31%) of injured participants exhibited elevated positive susceptibility indicative of abnormal iron profiles relative to the healthy population, a finding that was mainly concentrated in regions within the temporal lobe. Injury severity was significantly higher (P = 0.02) for these participants than their iron-normal counterparts, suggesting a link between injury severity, symptom burden, and elevated cortical iron. Secondary exploratory analyses of cortical depth and curvature profiles revealed abnormal iron accumulation in 83% (29/35) of mild traumatic brain injury participants, enabling better localization of injury-related changes in iron content to specific loci within each region and identifying effects that may be more subtle and lost in region-wise averaging. Our findings suggest that individualized approaches can further elucidate the clinical relevance of iron in mild head injury. Differences in injury severity between iron-normal and iron-abnormal mild traumatic brain injury participants identified in our primary analysis highlight not only why precise investigation is required to understand the link between objective changes in the brain and subjective symptomatology, but also identify iron as a candidate biomarker for tissue pathology after mild traumatic brain injury.

Parkinson's Disease Mild Cognitive Impairment with MRI evidence of Cholinergic Nucleus 4 Degeneration: A New Subtype?

Subtyping Parkinson's disease with mild cognitive impairment (PD-MCI) could improve clinical trial design and personalized treatments. Cholinergic nucleus 4 (Ch4) volume has been linked to cognitive impairment severity and future decline in PD. This study investigates whether PD-MCI patients with MRI evidence of Ch4 degeneration have distinct clinical profiles and cognitive trajectories. Baseline MRI scans of 148 PD-MCI participants from the Parkinson's Progression Markers Initiative (PPMI) were analyzed. Patients with low Ch4 grey matter density (GMD) had worse motor, autonomic, and olfactory symptoms, and were more likely to belong to the diffuse malignant PD subtype (51.6% vs. 23.4%; P < 0.01). They also had faster progression to cognitive milestones (P = 0.0046). These findings identify PD-MCI with low Ch4 as a distinct subtype with more severe symptoms and faster cognitive decline, highlighting the importance of considering this group in PD-MCI clinical trials, particularly for cholinergic therapies.

MRI atlas of the pituitary gland in young female adults

The probabilistic topography and inter-individual variability of the pituitary gland (PG) remain undetermined. The absence of a standardized reference atlas hinders research on PG volumetrics. In this study, we aimed at creating maximum probability maps for the anterior and posterior PG in young female adults. We manually delineated the anterior and posterior parts of the pituitary glands in 26 healthy subjects using high-resolution MRI T1 images. A three-step procedure and a cost function-masking approach were employed to optimize spatial normalization for the PG. We generated probabilistic atlases and maximum probability maps, which were subsequently coregistered back to the subjects' space and compared to manual delineations. Manual measurements led to a total pituitary volume of 705 ± 88 mm³, with the anterior and posterior volumes measuring 614 ± 82 mm³ and 91 ± 20 mm³, respectively. The mean relative volume difference between manual and atlas-based estimations was 1.3%. The global pituitary atlas exhibited an 80% (± 9%) overlap for the DICE index and 67% (± 11%) for the Jaccard index. Similarly, these values were 77% (± 13%) and 64% (± 14%) for the anterior pituitary atlas and 62% (± 21%) and 47% (± 17%) for the posterior PG atlas, respectively. We observed a substantial concordance and a significant correlation between the volume estimations of the manual and atlas-based methods for the global pituitary and anterior volumes. The maximum probability maps of the anterior and posterior PG lay the groundwork for automatic atlas-based segmentation methods and the standardized analysis of large PG datasets.

Opposing effects of thyroid hormones on hypothalamic subunits and limbic structures in hyperthyroidism patients: A comprehensive volumetric study

Thyroid hormones play a critical role in brain development, but paradoxically, patients with hyperthyroidism often exhibit cognitive decline and irritability. This study aims to explore the pattern of atrophy in hyperthyroid patients, changes in specific areas of the brain, including hypothalamic subfields and limbic structures, and their relationships with hormonal levels and psychometric tests. This prospective cross-sectional study involves 19 newly diagnosed, untreated hyperthyroid patients, and 15 age and gender-matched control subjects. The participants underwent psychometric and cognitive tests and volumetric MRI. The hypothalamic subfield (anterior-inferior, anterior-superior, superior-tubular, inferior-tubular, and posterior hypothalamus) and limbic structures (fornix, basal forebrain, nucleus accumbens, and septal nucleus) were segmented using voxel-based morphometry, surface-based morphometry, and deep learning algorithms. The groups were compared using the t-test, and correlation analyses were performed between clinical parameters and volumetric measurements. The correlation between hormonal parameters and volumetric measurements in patient and control groups was assessed with the Meng test. Hyperthyroid patients displayed widespread grey matter loss and sulcal shallowing in the left hemisphere. However, no local gyrification index changes or cortical thickness variations were detected. The limbic structures and hypothalamic subunits did not show any volume discrepancies. Free thyroxine in the patient group negatively correlated with bilateral anterior-inferior and right septal nucleus, but positively correlated with left anterior-inferior in the control group. Thyroid stimulating hormone in the patient group showed a positive correlation with bilateral fornix volume, a correlation absent in the control group. Disease duration negatively correlated with right anterior-inferior, right tubular inferior, and right septal nucleus. Changes in cognitive and psychometric test scores in the patient group correlated with the bilateral septal nucleus volume. Hyperthyroidism primarily leads to a reduction in grey matter volume and sulcal shallowing. Thyroid hormones have differing volumetric effects in limbic structures and hypothalamic subunits under physiological and hyperthyroid conditions.

Comparison of EPI DWI and STEAM DWI in Early Postoperative MRI Controls After Resection of Tumors of the Central Nervous System

PURPOSE

Diffusion-weighted imaging (DWI) is important for differentiating residual tumor and subacute infarctions in early postoperative magnetic resonance imaging (MRI) of central nervous system (CNS) tumors. In cases of pneumocephalus and especially in the presence of intraventricular trapped air, conventional echo-planar imaging (EPI) DWI is distorted by susceptibility artifacts. The performance and robustness of a newly developed DWI sequence using the stimulated echo acquisition mode (STEAM) was evaluated in patients after neurosurgical operations with early postoperative MRI.

METHODS

We compared EPI and STEAM DWI of 43 patients who received 3‑Tesla MRI within 72 h after a neurosurgical operation between 1 October 2019 and 30 September 2021. We analyzed susceptibility artifacts originating from air and blood and whether these artifacts compromised the detection of ischemic changes after surgery. The DWI sequences were (i) visually rated and (ii) volumetrically analyzed.

RESULTS

In 28 of 43 patients, we found severe and diagnostically relevant artifacts in EPI DWI, but none in STEAM DWI. In these cases, in which artifacts were caused by intracranial air, they led to a worse detection of ischemic lesions and thus to a possible failed diagnosis or lack of judgment using EPI DWI. Additionally, volumetric analysis demonstrated a 14% smaller infarct volume detected with EPI DWI. No significant differences in visual rating and volumetric analysis were detected among the patients without severe artifacts.

CONCLUSION

The newly developed version of STEAM DWI with highly undersampled radial encodings is superior to EPI DWI in patients with postoperative pneumocephalus.

Gray matter reserve determines glymphatic system function in young-onset Alzheimer's disease: Evidenced by DTI-ALPS and compared with age-matched controls

BACKGROUND

The diffusion tensor imaging analysis along the perivascular space (ALPS)-index can be used to model the glymphatic system in vivo.

AIM

This study explores putative mechanisms between prediction of ALPS-index and cognitive outcomes in young-onset Alzheimer's disease (YOAD) and age-matched controls (CTLs) and analyzes whether the link was mediated by the integrity of ALPS-index-anchored cerebral gray matter (GM).

METHODS

We enrolled 130 patients with YOAD and 137 CTLs. All participants underwent three-dimensional T1 -weighted MRI, diffusion tensor imaging and cognitive tests. We constructed GM regions correlated with the ALPS-index in the YOAD and CTL groups. For the GM regions significantly correlated with the ALPS-index and cognitive measures, we extracted a 4-mm radius sphere. In the YOAD and CTL groups, we used mediator analysis to explore the ALPS-index as predictor, GM partitions as mediators, and significant cognitive test scores as outcomes.

RESULTS

Patient group had significantly lower ALPS-index. The ALPS-index was associated with GM volume in the cerebellar gray, dorsolateral prefrontal, thalamus, superior frontal, amygdala and hippocampus, and these coherent regions coincided with those showing GM atrophy in the YOAD group. Mediation analysis of the YOAD group suggested that the relationships between the ALPS-index and cognitive performance were fully mediated by the integrity of ALPS-index coherent GM areas.

DISCUSSION

Reserved GM mediates the link between the glymphatic system and cognition. Our findings suggest that GM integrity rather than the glymphatic system could serve as a direct cognitive test scores predictor in patients with YOAD.

The Unresolved Methodological Challenge of Detecting Neuroplastic Changes in Astronauts

After completing a spaceflight, astronauts display a salient upward shift in the position of the brain within the skull, accompanied by a redistribution of cerebrospinal fluid. Magnetic resonance imaging studies have also reported local changes in brain volume following a spaceflight, which have been cautiously interpreted as a neuroplastic response to spaceflight. Here, we provide evidence that the grey matter volume changes seen in astronauts following spaceflight are contaminated by preprocessing errors exacerbated by the upwards shift of the brain within the skull. While it is expected that an astronaut's brain undergoes some neuroplastic adaptations during spaceflight, our findings suggest that the brain volume changes detected using standard processing pipelines for neuroimaging analyses could be contaminated by errors in identifying different tissue types (i.e., tissue segmentation). These errors may undermine the interpretation of such analyses as direct evidence of neuroplastic adaptation, and novel or alternate preprocessing or experimental paradigms are needed in order to resolve this important issue in space health research.

The amyloid imaging for the prevention of Alzheimer's disease consortium: A European collaboration with global impact

Background

Amyloid-β (Aβ) accumulation is considered the earliest pathological change in Alzheimer's disease (AD). The Amyloid Imaging to Prevent Alzheimer's Disease (AMYPAD) consortium is a collaborative European framework across European Federation of Pharmaceutical Industries Associations (EFPIA), academic, and 'Small and Medium-sized enterprises' (SME) partners aiming to provide evidence on the clinical utility and cost-effectiveness of Positron Emission Tomography (PET) imaging in diagnostic work-up of AD and to support clinical trial design by developing optimal quantitative methodology in an early AD population.

The AMYPAD studies

In the Diagnostic and Patient Management Study (DPMS), 844 participants from eight centres across three clinical subgroups (245 subjective cognitive decline, 342 mild cognitive impairment, and 258 dementia) were included. The Prognostic and Natural History Study (PNHS) recruited pre-dementia subjects across 11 European parent cohorts (PCs). Approximately 1600 unique subjects with historical and prospective data were collected within this study. PET acquisition with [¹⁸F]flutemetamol or [¹⁸F]florbetaben radiotracers was performed and quantified using the Centiloid (CL) method.

Results

AMYPAD has significantly contributed to the AD field by furthering our understanding of amyloid deposition in the brain and the optimal methodology to measure this process. Main contributions so far include the validation of the dual-time window acquisition protocol to derive the fully quantitative non-displaceable binding potential (BP _ND ), assess the value of this metric in the context of clinical trials, improve PET-sensitivity to emerging Aβ burden and utilize its available regional information, establish the quantitative accuracy of the Centiloid method across tracers and support implementation of quantitative amyloid-PET measures in the clinical routine.

Future steps

The AMYPAD consortium has succeeded in recruiting and following a large number of prospective subjects and setting up a collaborative framework to integrate data across European PCs. Efforts are currently ongoing in collaboration with ARIDHIA and ADDI to harmonize, integrate, and curate all available clinical data from the PNHS PCs, which will become openly accessible to the wider scientific community.

Diverse limbic comorbidities cause limbic and temporal atrophy in lewy body disease

BACKGROUND

In contrast to Alzheimer's disease (AD)-related pathology, the influence of comorbid limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) or argyrophilic grains (AG) on structural imaging in Lewy body disease (LBD) has seldom been evaluated.

OBJECTIVE

This study aimed to investigate whether non-AD limbic comorbidities, including LATE-NC and AG, cause cortical atrophy in LBD.

METHODS

Seventeen patients with pathologically confirmed LBD with lower Braak neurofibrillary tangle stage (<IV) and 10 healthy controls (HC) were included. Based on the presence of comorbid LATE-NC or AG, LBD patients were subdivided into nine patients with these proteinopathies (mixed LBD [mLBD]) and eight without (pure LBD [pLBD]). In addition to clinical feature evaluation, gray matter atrophy on voxel-based morphometry was compared between the two LBD and HC groups.

RESULTS

The mean age at antemortem magnetic resonance imaging of the mLBD patients was higher than that of the pLBD patients (84.3 ± 3.9 vs. 76.5 ± 10.5; p = .046). Irrespective of the presence or absence of comorbid LATE-NC or AG, all patients were clinically diagnosed with probable dementia with Lewy bodies or Parkinson's disease with dementia, respectively. Compared to the pLBD group, the mLBD group showed more conspicuous cortical atrophy of the bilateral hippocampus, amygdala, and temporal pole.

CONCLUSIONS

Non-AD limbic comorbidities, including LATE-NC and AG, are associated with limbic and temporal atrophy in older patients with LBD. Therefore, the possibility of non-AD limbic comorbidities should be considered in the diagnosis of elderly patients with dementia with clinical symptoms of LBD and medial temporal atrophy.

ISRS Technical Guidelines for Stereotactic Radiosurgery: Treatment of Small Brain Metastases (≤1 cm in Diameter)

PURPOSE

The objective of this literature review was to develop International Stereotactic Radiosurgery Society (ISRS) consensus technical guidelines for the treatment of small, ≤1 cm in maximal diameter, intracranial metastases with stereotactic radiosurgery. Although different stereotactic radiosurgery technologies are available, most of them have similar treatment workflows and common technical challenges that are described.

METHODS AND MATERIALS

A systematic review of the literature published between 2009 and 2020 was performed in Pubmed using the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) methodology. The search terms were limited to those related to radiosurgery of brain metastases and to publications in the English language.

RESULTS

From 484 collected abstract 37 articles were included into the detailed review and bibliographic analysis. An additional 44 papers were identified as relevant from a search of the references. The 81 papers, including additional 7 international guidelines, were deemed relevant to at least one of five areas that were considered paramount for this report. These areas of technical focus have been employed to structure these guidelines: imaging specifications, target volume delineation and localization practices, use of margins, treatment planning techniques, and patient positioning.

CONCLUSION

This systematic review has demonstrated that Stereotactic Radiosurgery (SRS) for small (1 cm) brain metastases can be safely performed on both Gamma Knife (GK) and CyberKnife (CK) as well as on modern LINACs, specifically tailored for radiosurgical procedures, However, considerable expertise and resources are required for a program based on the latest evidence for best practice.

Diffusion-weighted imaging as an imaging biomarker for assessing survival of patients with intrahepatic mass-forming cholangiocarcinoma

BACKGROUND

Mass-forming cholangiocarcinoma is the most common form of intrahepatic cholangiocarcinoma and is associated with a worse prognosis. This study aimed to assess the role of diffusion-weighted imaging and other imaging features as prognostic markers to predict the survival of patients with intrahepatic mass-forming cholangiocarcinoma (IMCC).

MATERIALS AND METHODS

The study included patients with pathologically proven IMCC from January 2011 to January 2018. Two radiologists retrospectively reviewed various imaging findings and manually estimated the area of diffusion restriction. Patients were grouped according to their restriction area into (group 1) restriction ≥ 1/3 of the tumor and (group 2) restriction < 1/3 of the tumor. Statistical analysis was performed to assess the relationship between various imaging features and patients' survival.

RESULTS

Seventy-three patients were included in the study. IMCC patients with tumor size ≥ 5 cm had increased intrahepatic- and peritoneal metastases (p = 039 and p = 0.001 for reader 1 and p = 0.048 and p = 0.057 for reader 2). There was no significant relationship between the diffusion restriction area and tumor size, enhancement pattern, vascular involvement, lymph node metastasis, peritoneal- and distant metastasis. The number of deaths was significantly higher in patients with group 2 restriction (63.6% for group 1 vs. 96.6% for group 2; p = 0.001 for reader 1)(68.2% for group 1 vs. 89.7%% for group 2; p = 0.030 for reader 2). Patients with group 2 restriction had shorter 1- and 3-year survival rates and lower median survival time. Multivariable survival analysis showed two independent prognostic factors relating to poor survival outcomes: peritoneal metastasis (p = 0.04 for reader 1 and p = 0.041 for reader 2) and diffusion restriction < 1/3 (p = 0.011 for reader 1 and p = 0.042 for reader 2). Lymph node metastasis and intrahepatic metastasis were associated with shorter survival in the univariate analysis. However, these factors were non-significant in the multivariate analysis.

CONCLUSION

Restriction diffusion of less than 1/3 and peritoneal metastasis were associated with shorter overall survival of IMCC patients. Other features that might correlate with the outcome are suspicious lymph nodes and multifocal lesions.

Brain tissue classification from stereoelectroencephalographic recordings

BACKGROUND

Stereoelectroencephalographic (SEEG) recordings can be performed before final resective surgery in some drug-resistant patients with focal epilepsies. For good SEEG signal interpretation, it is important to correctly identify the brain tissue in which each contact is inserted. Tissue classification is usually done with the coregistration of CT scan (with implanted SEEG electrodes) with preoperative MRI.

NEW METHOD

Brain tissue classification is done here directly from SEEG signals obtained at rest by a linear discriminant analysis (LDA) classifier using measured SEEG signals. The classification operates on features extracted from Bode plots obtained via non-parametric frequency domain transfer functions of adjacent contacts pairs. Classification results have been compared with classification from T1 MRI following the labelling procedure described in Deman et al. (2018), together with minor corrections by visual inspection by specialists.

RESULTS

With the data processed from 19 epileptic patients representing 1284 contact pairs, an accuracy of 72 ± 3% was obtained for homogeneous tissue separation. To our knowledge only one previous study conducted brain tissue classification using the power spectra of SEEG signals, and the distance between contacts on a shaft. The features proposed in our article performed better with the LDA classifier. However, the Bayesian classifier proposed in Greene et al. (2020) is more robust and could be used in a future study to enhance the classification performance.

CONCLUSIONS AND SIGNIFICANCE

Our findings suggest that careful analysis of the transfer function between adjacent contacts measuring resting activity via frequency domain identification, could allow improved interpretation of SEEG data and or their co-registration with subject's anatomy.

Comparison and Reliability of Hippocampal Subfield Segmentations Within FreeSurfer Utilizing T1- and T2-Weighted Multispectral MRI Data

The accurate segmentation of in vivo magnetic resonance imaging (MRI) data is a crucial prerequisite for the reliable assessment of disease progression, patient stratification or the establishment of putative imaging biomarkers. This is especially important for the hippocampal formation, a brain area involved in memory formation and often affected by neurodegenerative or psychiatric diseases. FreeSurfer, a widely used automated segmentation software, offers hippocampal subfield delineation with multiple input options. While a single T1-weighted (T1) sequence is regularly used by most studies, it is also possible and advised to use a high-resolution T2-weighted (T2H) sequence or multispectral information. In this investigation it was determined whether there are differences in volume estimations depending on the input images and which combination of these deliver the most reliable results in each hippocampal subfield. 41 healthy participants (age = 25.2 years ± 4.2 SD) underwent two structural MRIs at three Tesla (time between scans: 23 days ± 11 SD) using three different structural MRI sequences, to test five different input configurations (T1, T2, T2H, T1 and T2, and T1 and T2H). We compared the different processing pipelines in a cross-sectional manner and assessed reliability using test-retest variability (%TRV) and the dice coefficient. Our analyses showed pronounced significant differences and large effect sizes between the processing pipelines in several subfields, such as the molecular layer (head), CA1 (head), hippocampal fissure, CA3 (head and body), fimbria and CA4 (head). The longitudinal analysis revealed that T1 and multispectral analysis (T1 and T2H) showed overall higher reliability across all subfields than T2H alone. However, the specific subfields had a substantial influence on the performance of segmentation results, regardless of the processing pipeline. Although T1 showed good test-retest metrics, results must be interpreted with caution, as a standard T1 sequence relies heavily on prior information of the atlas and does not take the actual fine structures of the hippocampus into account. For the most accurate segmentation, we advise the use of multispectral information by using a combination of T1 and high-resolution T2-weighted sequences or a T2 high-resolution sequence alone.

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

Association between Quantitative MR Markers of Cortical Evolving Organization and Gene Expression during Human Prenatal Brain Development

The relationship between structural changes of the cerebral cortex revealed by Magnetic Resonance Imaging (MRI) and gene expression in the human fetal brain has not been explored. In this study, we aimed to test the hypothesis that relative regional thickness (a measure of cortical evolving organization) of fetal cortical compartments (cortical plate [CP] and subplate [SP]) is associated with expression levels of genes with known cortical phenotype. Mean regional SP/CP thickness ratios across age measured on in utero MRI of 25 healthy fetuses (20-33 gestational weeks [GWs]) were correlated with publicly available regional gene expression levels (23-24 GW fetuses). Larger SP/CP thickness ratios (more pronounced cortical evolving organization) was found in perisylvian regions. Furthermore, we found a significant association between SP/CP thickness ratio and expression levels of the FLNA gene (mutated in periventricular heterotopia, congenital heart disease, and vascular malformations). Further work is needed to identify early MRI biomarkers of gene expression that lead to abnormal cortical development.

Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging

Single-tensor diffusion imaging (DTI) has traditionally been used to assess integrity of white matter. For example, we previously showed that integrity of limbic white matter tracts declines in healthy aging and relates to episodic memory performance. However, multi-compartment diffusion models may be more informative about microstructural properties of gray matter. The current study examined hippocampal gray matter integrity using both single-tensor and multi-compartment (neurite orientation dispersion and density imaging, NODDI) diffusion imaging. Younger (20-38 years) and older (59-84 years) adults also completed the Mnemonic Similarity Task to measure mnemonic discrimination performance. Results revealed age-related declines in both single-tensor (lower fractional anisotropy, higher mean diffusivity) and multi-compartment (higher restricted, hindered and free diffusion) measures of hippocampal gray matter integrity. As expected, NODDI measures (hindered and free diffusion) captured more age-related variance than DTI measures. Moreover, mnemonic discrimination of highly similar lure items in memory was related to hippocampal gray matter integrity in younger but not older adults. These findings support the notion that age-related differences in gray matter integrity are better captured by multi-compartment versus single-tensor diffusion models and show that the relationship between mnemonic discrimination and hippocampal gray matter integrity is moderated by age.

Spinal cord atrophy in a primary progressive multiple sclerosis trial: Improved sample size using GBSI

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The GBSI provided clinically meaningful measurements of spinal cord atrophy, with low sample size.

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Deriving spinal cord atrophy from brain MRI using the GBSI is easier than spinal cord MRI.

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Spinal cord atrophy on GBSI could be used as a secondary outcome measure.

Background

We aimed to evaluate the implications for clinical trial design of the generalised boundary-shift integral (GBSI) for spinal cord atrophy measurement.

Methods

We included 220 primary-progressive multiple sclerosis patients from a phase 2 clinical trial, with baseline and week-48 3DT1-weighted MRI of the brain and spinal cord (1 × 1 × 1 mm³), acquired separately. We obtained segmentation-based cross-sectional spinal cord area (CSA) at C1-2 (from both brain and spinal cord MRI) and C2-5 levels (from spinal cord MRI) using DeepSeg, and, then, we computed corresponding GBSI.

Results

Depending on the spinal cord segment, we included 67.4–98.1% patients for CSA measurements, and 66.9–84.2% for GBSI. Spinal cord atrophy measurements obtained with GBSI had lower measurement variability, than corresponding CSA. Looking at the image noise floor, the lowest median standard deviation of the MRI signal within the cerebrospinal fluid surrounding the spinal cord was found on brain MRI at the C1-2 level. Spinal cord atrophy derived from brain MRI was related to the corresponding measures from dedicated spinal cord MRI, more strongly for GBSI than CSA. Spinal cord atrophy measurements using GBSI, but not CSA, were associated with upper and lower limb motor progression.

Discussion

Notwithstanding the reduced measurement variability, the clinical correlates, and the possibility of using brain acquisitions, spinal cord atrophy using GBSI should remain a secondary outcome measure in MS studies, until further advancements increase the quality of acquisition and reliability of processing.

Partial-volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia

The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial‐volume‐based over probabilistic‐based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex‐matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel‐wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub‐region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect.

Ventricular Volume Is More Strongly Associated with Clinical Improvement Than the Evans Index after Shunting in Idiopathic Normal Pressure Hydrocephalus

BACKGROUND AND PURPOSE

Ventricular enlargement in idiopathic normal pressure hydrocephalus is often estimated using the Evans index. However, the sensitivity of the Evans index to estimate changes in ventricular size postoperatively has been questioned. Here, we evaluated the postoperative change in ventricle size in relation to shunt response in patients with idiopathic normal pressure hydrocephalus, by comparing ventricular volume and the Evans index.

MATERIALS AND METHODS

Fifty-seven patients with idiopathic normal pressure hydrocephalus underwent high-resolution MR imaging preoperatively and 6 months after shunt insertion. Clinical symptoms of gait, balance, cognition, and continence were assessed according to the idiopathic normal pressure hydrocephalus scale. The ventricular volume of the lateral and third ventricles and the Evans index were measured using ITK-SNAP software. Semiautomatic volumetric analysis was performed, and postoperative changes in ventricular volume and the Evans index and their relationships to postoperative clinical improvement were compared.

RESULTS

The median postoperative ventricular volume decrease was 25 mL (P < .001). The proportional decrease in ventricular volume was greater than that in the Evans index (P < .001). The postoperative decrease in ventricular volume was associated with a postoperative increase in the idiopathic normal pressure hydrocephalus scale score (P = .004). Shunt responders (75%) demonstrated a greater ventricular volume decrease than nonresponders (P = .002).

CONCLUSIONS

Clinical improvement after shunt surgery in idiopathic normal pressure hydrocephalus is associated with a reduction of ventricular size. Ventricular volume is a more sensitive estimate than the Evans index and, therefore, constitutes a more precise method to evaluate change in ventricle size after shunt treatment in idiopathic normal pressure hydrocephalus.

Dentate Gyrus Volume Mediates the Effect of Fornix Microstructure on Memory Formation in Older Adults

Age-related deterioration in white and gray matter is linked to cognitive deficits. Reduced microstructure of the fornix, the major efferent pathway of the hippocampus, and volume of the dentate gyrus (DG), may cause age-associated memory decline. However, the linkage between these anatomical determinants and memory retrieval in healthy aging are poorly understood. In 30 older adults, we acquired diffusion tensor and T1-weighted images for individual deterministic tractography and volume estimation. A memory task, administered outside of the scanner to assess retrieval of learned associations, required discrimination of previously acquired picture-word pairs. The results showed that fornix fractional anisotropy (FA) and left DG volumes were related to successful retrieval. These brain-behavior associations were observed for correct rejections, but not hits, indicating specificity of memory network functioning for detecting false associations. Mediation analyses showed that left DG volume mediated the effect of fornix FA on memory (48%), but not vice versa. These findings suggest that reduced microstructure induces volume loss and thus negatively affects retrieval of learned associations, complementing evidence of a pivotal role of the fornix in healthy aging. Our study offers a neurobehavioral model to explain variability in memory retrieval in older adults, an important prerequisite for the development of interventions to counteract cognitive decline.

Magnetic resonance fingerprinting review part 2: Technique and directions

Magnetic resonance fingerprinting (MRF) is a general framework to quantify multiple MR-sensitive tissue properties with a single acquisition. There have been numerous advances in MRF in the years since its inception. In this work we highlight some of the recent technical developments in MRF, focusing on sequence optimization, modifications for reconstruction and pattern matching, new methods for partial volume analysis, and applications of machine and deep learning. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:993-1007.

Fast multi-component analysis using a joint sparsity constraint for MR fingerprinting

PURPOSE

To develop an efficient algorithm for multi-component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties.

METHODS

Different tissues or components within a voxel are potentially separable in MRF because of their distinct signal evolutions. The observed signal evolution in each voxel can be described as a linear combination of the signals for each component with a non-negative weight. An assumption that only a small number of components are present in the measured field of view is usually imposed in the interpretation of multi-component data. In this work, a joint sparsity constraint is introduced to utilize this additional prior knowledge in the multi-component analysis of MRF data. A new algorithm combining joint sparsity and non-negativity constraints is proposed and compared to state-of-the-art multi-component MRF approaches in simulations and brain MRF scans of 11 healthy volunteers.

RESULTS

Simulations and in vivo measurements show reduced noise in the estimated tissue fraction maps compared to previously proposed methods. Applying the proposed algorithm to the brain data resulted in 4 or 5 components, which could be attributed to different brain structures, consistent with previous multi-component MRF publications.

CONCLUSIONS

The proposed algorithm is faster than previously proposed methods for multi-component MRF and the simulations suggest improved accuracy and precision of the estimated weights. The results are easier to interpret compared to voxel-wise methods, which combined with the improved speed is an important step toward clinical evaluation of multi-component MRF.

Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison

Neuroimaging MRI data in scientific research is increasingly pooled, but the reliability of such studies may be hampered by the use of different hardware elements. This might introduce bias, for example when cross-sectional studies pool data acquired with different head coils, or when longitudinal clinical studies change head coils halfway. In the present study, we aimed to estimate this possible bias introduced by using different head coils to create awareness and to avoid misinterpretation of results. We acquired, with both an 8 channel and 32 channel head coil, T1-weighted, diffusion tensor imaging and resting state fMRI images at 3T MRI (Philips Achieva) with stable acquisition parameters in a large group of cognitively healthy participants (n = 77). Standard analysis methods, i.e., voxel-based morphometry, tract-based spatial statistics and resting state functional network analyses, were used in a within-subject design to compare 8 and 32 channel head coil data. Signal-to-noise ratios (SNR) for both head coils showed similar ranges, although the 32 channel SNR profile was more homogeneous. Our data demonstrates specific patterns of gray and white matter volume differences between head coils (relative volume change of 6 to 9%), related to altered image contrast and therefore, altered tissue segmentation. White matter connectivity (fractional anisotropy and diffusivity measures) showed hemispherical dependent differences between head coils (relative connectivity change of 4 to 6%), and functional connectivity in resting state networks was higher using the 32 channel head coil in posterior cortical areas (relative change up to 27.5%). This study shows that, even when acquisition protocols are harmonized, the results of standardized analysis models can be severely affected by the use of different head coils. Researchers should be aware of this when combining multiple neuroimaging MRI datasets, to prevent coil-related bias and avoid misinterpretation of their findings.

Liver MR relaxometry at 3T - segmental normal T1 and T2* values in patients without focal or diffuse liver disease and in patients with increased liver fat and elevated liver stiffness

Magnetic resonance (MR) T₁ and T₂* mapping allows quantification of liver relaxation times for non-invasive characterization of diffuse liver disease. We hypothesized that liver relaxation times are not only influenced by liver fibrosis, inflammation and fat, but also by air in liver segments adjacent to the lung – especially in MR imaging at 3T. A total of 161 study participants were recruited, while 6 patients had to be excluded due to claustrophobia or technically uninterpretable MR elastography. Resulting study population consisted of 12 healthy volunteers and 143 patients who prospectively underwent multiparametric MR imaging at 3T. Of those 143 patients, 79 had normal liver stiffness in MR elastography (shear modulus <2.8 kPa, indicating absence of fibrosis) and normal proton density fat fraction (PDFF < 10%, indicating absence of steatosis), defined as reference population. T₁ relaxation times in these patients were significantly shorter in liver segments adjacent to the lung than in those not adjacent to the lung (p < 0.001, mean of differences 33 ms). In liver segments not adjacent to the lung, T₁ allowed to differentiate significantly between the reference population and patients with steatosis and/or fibrosis (p ≤ 0.011), while there was no significant difference of T₁ between the reference population and healthy volunteers. In conclusion, we propose to measure T₁ relaxation times in liver segments not adjacent to the lung. Otherwise, we recommend taking into account slightly shorter T₁ values in liver segments adjacent to the lung.

Computer-aided pancreas segmentation based on 3D GRE Dixon MRI: a feasibility study

Background

Pancreas segmentation is of great significance for pancreatic cancer radiotherapy positioning, pancreatic structure, and function evaluation.

Purpose

To investigate the feasibility of computer-aided pancreas segmentation based on optimized three-dimensional (3D) Dixon magnetic resonance imaging (MRI).

Material and Methods

Seventeen healthy volunteers (13 men, 4 women; mean age = 53.4 ± 13.2 years; age range = 28–76 years) underwent routine and optimized 3D gradient echo (GRE) Dixon MRI at 3.0 T. The computer-aided segmentation of the pancreas was executed by the Medical Imaging Interaction ToolKit (MITK) with the traditional segmentation algorithm pipeline (a threshold method and a morphological method) on the opposed-phase and water images of Dixon. The performances of our proposed computer segmentation method were evaluated by Dice coefficients and two-dimensional (2D)/3D visualization figures, which were compared for the opposed-phase and water images of routine and optimized Dixon sequences.

Results

The dice coefficients of the computer-aided pancreas segmentation were 0.633 ± 0.080 and 0.716 ± 0.033 for opposed-phase and water images of routine Dixon MRI, respectively, while they were 0.415 ± 0.143 and 0.779 ± 0.048 for the optimized Dixon MRI, respectively. The Dice index was significantly higher based on the water images of optimized Dixon than those in the other three groups (all P values < 0.001), including water images of routine Dixon MRI and both of the opposed-phase images of routine and optimized Dixon sequences.

Conclusion

Computer-aided pancreas segmentation based on Dixon MRI is feasible. The water images of optimized Dixon obtained the best similarity with a good stability.

Preclinical Imaging Biomarkers for Postischaemic Neurovascular Remodelling

In the pursuit of understanding the pathological alterations that underlie ischaemic injuries, such as vascular remodelling and reorganisation, there is a need for recognising the capabilities and limitations of in vivo imaging techniques. Thus, this review presents contemporary published research of imaging modalities that have been implemented to study postischaemic neurovascular changes in small animals. A comparison of the technical aspects of the various imaging tools is included to set the framework for identifying the most appropriate methods to observe postischaemic neurovascular remodelling. A systematic search of the PubMed® and Elsevier's Scopus databases identified studies that were conducted between 2008 and 2018 to explore postischaemic neurovascular remodelling in small animal models. Thirty-five relevant in vivo imaging studies are included, of which most made use of magnetic resonance imaging or positron emission tomography, whilst various optical modalities were also utilised. Notably, there is an increasing trend of using multimodal imaging to exploit the most beneficial properties of each imaging technique to elucidate different aspects of neurovascular remodelling. Nevertheless, there is still scope for further utilising noninvasive imaging tools such as contrast agents or radiotracers, which will have the ability to monitor neurovascular changes particularly during restorative therapy. This will facilitate more successful utility of the clinical imaging techniques in the interpretation of neurovascular reorganisation over time.

Multicompartment Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is a technique for quantitative estimation of spin- relaxation parameters from magnetic-resonance data. Most current MRF approaches assume that only one tissue is present in each voxel, which neglects intravoxel structure, and may lead to artifacts in the recovered parameter maps at boundaries between tissues. In this work, we propose a multicompartment MRF model that accounts for the presence of multiple tissues per voxel. The model is fit to the data by iteratively solving a sparse linear inverse problem at each voxel, in order to express the measured magnetization signal as a linear combination of a few elements in a precomputed fingerprint dictionary. Thresholding-based methods commonly used for sparse recovery and compressed sensing do not perform well in this setting due to the high local coherence of the dictionary. Instead, we solve this challenging sparse-recovery problem by applying reweighted-𝓁1-norm regularization, implemented using an efficient interior-point method. The proposed approach is validated with simulated data at different noise levels and undersampling factors, as well as with a controlled phantom-imaging experiment on a clinical magnetic-resonance system.

Bayesian estimation of multicomponent relaxation parameters in magnetic resonance fingerprinting

PURPOSE

To estimate multiple components within a single voxel in magnetic resonance fingerprinting when the number and types of tissues comprising the voxel are not known a priori.

THEORY

Multiple tissue components within a single voxel are potentially separable with magnetic resonance fingerprinting as a result of differences in signal evolutions of each component. The Bayesian framework for inverse problems provides a natural and flexible setting for solving this problem when the tissue composition per voxel is unknown. Assuming that only a few entries from the dictionary contribute to a mixed signal, sparsity-promoting priors can be placed upon the solution.

METHODS

An iterative algorithm is applied to compute the maximum a posteriori estimator of the posterior probability density to determine the magnetic resonance fingerprinting dictionary entries that contribute most significantly to mixed or pure voxels.

RESULTS

Simulation results show that the algorithm is robust in finding the component tissues of mixed voxels. Preliminary in vivo data confirm this result, and show good agreement in voxels containing pure tissue.

CONCLUSIONS

The Bayesian framework and algorithm shown provide accurate solutions for the partial-volume problem in magnetic resonance fingerprinting. The flexibility of the method will allow further study into different priors and hyperpriors that can be applied in the model. Magn Reson Med 80:159-170, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington's Disease

The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington's disease (HD), and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

A Survey of White Matter Neurons at the Gyral Crowns and Sulcal Depths in the Rhesus Monkey

Gyrencephalic brains exhibit deformations of the six neocortical laminae at gyral crowns and sulcal depths, where the deeper layers are, respectively, expanded and compressed. The present study addresses: (1) the degree to which the underlying white matter neurons (WMNs) observe the same changes at gyral crowns and sulcal depths; and (2) whether these changes are consistent or variable across different cortical regions. WMNs were visualized by immunohistochemistry using the pan-neuronal label NeuN, and their density was quantified in eight rhesus monkey brains for four regions; namely, frontal (FR), superior frontal gyrus (SFG), parietal (Par) and temporal (TE). In all four regions, there were about 50% fewer WMNs in the sulcal depth, but there was also distinct variability from region to region. For the gyral crown, we observed an average density per 0.21 mm2 of 82 WMNs for the FR, 51 WMNs for SFG, 80 WMNs for Par and 93 WMNs for TE regions. By contrast, for the sulcal depth, the average number of WMNs per 0.21 mm2 was 41 for FR, 31 for cingulate sulcus (underlying the SFG), 54 for Par and 63 for TE cortical regions. Since at least some WMNs participate in cortical circuitry, these results raise the possibility of their differential influence on cortical circuitry in the overlying gyral and sulcal locations. The results also point to a possible role of WMNs in the differential vulnerability of gyral vs. sulcal regions in disease processes, and reinforce the increasing awareness of the WMNs as part of a complex, heterogeneous and structured microenvironment.

Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance - a derivation/validation approach

BACKGROUND

Myocardial native T1 measurements are likely influenced by intramyocardial blood. Since blood T1 is both variable and longer compared to myocardial T1, this will degrade the precision of myocardial T1 measurements. Precision could be improved by correction, but the amount of correction and the optimal blood T1 variables to correct with are unknown. We hypothesized that an appropriate correction would reduce the standard deviation (SD) of native myocardial T1.

METHODS

Consecutive patients (n = 400) referred for CMR with known or suspected heart disease were split into a derivation cohort for model construction (n = 200, age 51 ± 18 years, 50% male) and a validation cohort for assessing model performance (n = 200, age 48 ± 17 years, 50% male). Exclusion criteria included focal septal abnormalities. A Modified Look-Locker inversion recovery sequence (MOLLI, 1.5 T Siemens Aera) was used to acquire T1 and T1* maps. T1 and T1* maps were used to measure native myocardial T1, and blood T1 and T1*. A multivariate linear regression correction model was implemented using blood measurement of R1 (1/T1), R1* (1/T1*) or hematocrit. The correction model from the derivation cohort was applied to the validation cohort, and assessed for reduction in variability with the F-test.

RESULTS

Blood [LV + RV] mean R1, mean R1* and hematocrit correlated with myocardial T1 (Pearson's r, range 0.37 to 0.45, p < 0.05 for all) in both the derivation and validation cohorts respectively, suggesting that myocardial T1 measurements are influenced by intramyocardial blood. Mean myocardial native T1 did not differ between the derivation and validation cohorts (1030 ± 42.6 ms and 1023 ± 45.2 ms respectively, p = 0.07). In the derivation cohort, correction using blood mean R1 and mean R1* yielded a decrease in myocardial T1 SD (45.2 ms to 36.6 ms, p = 0.03). When the model from the derivation cohort was applied to the validation cohort, the SD reduction was maintained (39.3 ms, p = 0.049). This 13% reduction in measurement variability leads to a 23% reduction in sample size to detect a 50 ms difference in native myocardial T1.

CONCLUSIONS

Correcting native myocardial T1 for R1 and R1* of blood improves the precision of myocardial T1 measurement by ~13%, and could consequently improve disease detection and reduce sample size needs for clinical research.

Magnetic resonance imaging atlas of the cervical spine musculature

The anatomy of the cervical spine musculature visible on magnetic resonance (MR) images is poorly described in the literature. However, the correct identification of individual muscles is clinically important because certain conditions of the cervical spine, for example whiplash associated disorders, idiopathic neck pain, cervical nerve root avulsion and cervical spondylotic myelopathy, are associated with different morphological changes in specific muscles visible on MR images. Knowledge of the precise structure of different cervical spine muscles is crucial when comparisons with the contralateral side or with normal are required for accurate description of imaging pathology, management and assessment of treatment efficacy. However, learning the intricate arrangement of 27 muscles is challenging. A multi-level cross-sectional depiction combined with three-dimensional reconstructions could facilitate the understanding of this anatomically complex area. This paper presents a comprehensive series of labeled axial MR images from one individual and serves as a reference atlas of the cervical spine musculature to guide clinicians, researchers, and anatomists in the accurate identification of these muscles on MR imaging. Clin. Anat. 29:643-659, 2016. © 2016 Wiley Periodicals, Inc.