Phantom evaluation of electrical conductivity mapping by MRI: Comparison to vector network analyzer measurements and spatial resolution assessment.

PURPOSE: To evaluate the performance of various MR electrical properties tomography (MR-EPT) methods at 3 T in terms of absolute quantification and spatial resolution limit for electrical conductivity. METHODS: Absolute quantification as well as spatial resolution performance were evaluated on homogeneous phantoms and a phantom with holes of different sizes, respectively. Ground-truth conductivities were measured with an open-ended coaxial probe connected to a vector network analyzer (VNA). Four widely used MR-EPT reconstruction methods were investigated: phase-based Helmholtz (PB), phase-based convection-reaction (PB-cr), image-based (IB), and generalized-image-based (GIB). These methods were compared using the same complex images from a 1 mm-isotropic UTE sequence. Alternative transceive phase acquisition sequences were also compared in PB and PB-cr. RESULTS: In large homogeneous phantoms, all methods showed a strong correlation with ground truth conductivities (r > 0.99); however, GIB was the best in terms of accuracy, spatial uniformity, and robustness to boundary artifacts. In the resolution phantom, the normalized root-mean-squared error of all methods grew rapidly (>0.40) when the hole size was below 10 mm, with simplified methods (PB and IB), or below 5 mm, with generalized methods (PB-cr and GIB). CONCLUSION: VNA measurements are essential to assess the accuracy of MR-EPT. In this study, all tested MR-EPT methods correlated strongly with the VNA measurements. The UTE sequence is recommended for MR-EPT, with the GIB method providing good accuracy for structures down to 5 mm. Structures below 5 mm may still be detected in the conductivity maps, but with significantly lower accuracy.

Deep learning HASTE sequence compared with T2-weighted BLADE sequence for liver MRI at 3 Tesla: a qualitative and quantitative prospective study.

OBJECTIVES: To qualitatively and quantitatively compare a single breath-hold fast half-Fourier single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE) with T2-weighted BLADE sequence for liver MRI at 3 T. METHODS: From December 2020 to January 2021, patients with liver MRI were prospectively included. For qualitative analysis, sequence quality, presence of artifacts, conspicuity, and presumed nature of the smallest lesion were assessed using the chi-squared and McNemar tests. For quantitative analysis, number of liver lesions, size of the smallest lesion, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in both sequences were assessed using the paired Wilcoxon signed-rank test. Intraclass correlation coefficients (ICCs) and kappa coefficients were used to assess agreement between the two readers. RESULTS: One hundred and twelve patients were evaluated. Overall image quality (p = .006), artifacts (p < .001), and conspicuity of the smallest lesion (p = .001) were significantly better for the DL HASTE sequence than for the T2-weighted BLADE sequence. Significantly more liver lesions were detected with the DL HASTE sequence (356 lesions) than with the T2-weighted BLADE sequence (320 lesions; p < .001). CNR was significantly higher for the DL HASTE sequence (p < .001). SNR was higher for the T2-weighted BLADE sequence (p < .001). Interreader agreement was moderate to excellent depending on the sequence. Of the 41 supernumerary lesions visible only on the DL HASTE sequence, 38 (93%) were true-positives. CONCLUSION: The DL HASTE sequence can be used to improve image quality and contrast and reduces artifacts, allowing the detection of more liver lesions than with the T2-weighted BLADE sequence. CLINICAL RELEVANCE STATEMENT: The DL HASTE sequence is superior to the T2-weighted BLADE sequence for the detection of focal liver lesions and can be used in daily practice as a standard sequence. KEY POINTS: • The half-Fourier acquisition single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE sequence) has better overall image quality, reduced artifacts (particularly motion artifacts), and improved contrast, allowing the detection of more liver lesions than with the T2-weighted BLADE sequence. • The acquisition time of the DL HASTE sequence is at least eight times faster (21 s) than that of the T2-weighted BLADE sequence (3-5 min). • The DL HASTE sequence could replace the conventional T2-weighted BLADE sequence to meet the growing indication for hepatic MRI in clinical practice, given its diagnostic and time-saving performance.

Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke.

OBJECTIVES: Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR sequences. We aimed to assess the performance of an artificial intelligence-enhanced ultrafast (UF) protocol, compared to the reference protocol, in the AIS management. METHODS: We included patients admitted in the emergency department for suspected AIS. Each patient underwent a 3-T MR protocol, including reference acquisitions of T2-FLAIR, DWI, and SWI (duration: 7 min 54 s) and their accelerated multishot EPI counterparts for T2-FLAIR and T2*, complemented by a single-shot EPI DWI (duration: 1 min 54 s). Two blinded neuroradiologists reviewed each dataset, assessing DWI (detection, location, number of acute lesions), FLAIR (vascular hyperintensities, visibility of acute lesions), and SWI/T2* (hemorrhagic transformation, thrombus). We compared the agreement between the diagnoses obtained with both protocols using kappa coefficients. RESULTS: A total of 173 patients were included consecutively, of whom 80 with an AIS in DWI. We found an almost perfect agreement between the UF and reference protocols regarding the detection, distribution, number of AIS in DWI (κ = 0.98, 0.98, and 0.87 respectively), the presence of vascular hyperintensities, and the presence of a parenchymal hyperintensity in the AIS region in FLAIR (κ = 0.93 and 0.89 respectively). Agreement was substantial in T2*/SWI for thrombus detection, and fair for hemorrhagic transformation detection (κ = 0.64 and 0.38 respectively). Differential diagnoses were similarly detected by both protocols (κ = 1). CONCLUSIONS: Our AI-enhanced ultrafast MRI protocol allowed an effective detection and characterization of both AIS and differential diagnoses in less than 2 min. KEY POINTS: • The AI-enhanced ultrafast MRI protocol allowed an effective detection of acute stroke. • Characterization of stroke features with the UF protocol was equivalent to the reference sequences. • Differential diagnoses were detected similarly by the UF and reference protocols.

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is required. Thus, our objective is to evaluate the performance of two automatic segmentation methods on the calculation of aortic wall pressure. METHODS: Automatic segmentation of the aorta was performed with methods based on deep learning and multi-atlas using the systolic phase in the 4D flow MRI magnitude image of 36 patients. Using mesh morphing, isotopological meshes were generated, and CFD was performed to calculate the aortic wall pressure. Node-to-node comparisons of the pressure results were made to identify the most robust automatic method respect to the pressures obtained with a manually segmented model. RESULTS: Deep learning approach presented the best segmentation performance with a mean Dice similarity coefficient and a mean Hausdorff distance (HD) equal to 0.92+/- 0.02 and 21.02+/- 24.20 mm, respectively. At the global level HD is affected by the performance in the abdominal aorta. Locally, this distance decreases to 9.41+/- 3.45 and 5.82+/- 6.23 for the ascending and descending thoracic aorta, respectively. Moreover, with respect to the pressures from the manual segmentations, the differences in the pressures computed from deep learning were lower than those computed from multi-atlas method. CONCLUSION: To reduce biases in the calculation of aortic wall pressure, accurate segmentation is needed, particularly in regions with high blood flow velocities. Thus, the deep learning segmen-tation method should be preferred.

Magnetic Resonance Elastography for Assessing Fibrosis in Patients with Crohn's Disease: A Pilot Study.

BACKGROUND: Patients with Crohn's disease can develop intestinal strictures, containing various degrees of inflammation and fibrosis. Differentiation of the main component of a stricturing lesion is the key for defining the therapeutic management. AIMS: We assessed for the first time the accuracy of magnetic resonance elastography in detecting intestinal fibrosis and predicting clinical course in patients with Crohn's disease. METHODS: This was a prospective study of adult patients with Crohn's disease and magnetic resonance imaging examination, including magnetic resonance elastography, between April 2019 and February 2020. The association between the bowel stiffness value and the degree of fibrosis was evaluated. The relationship between the stiffness value and the occurrence of clinical events was also investigated. RESULTS: A total of 69 patients were included. The stiffness value measured by magnetic resonance elastography was correlated with the degree of fibrosis (p < 0.001). A bowel stiffness ≥ 3.57 kPa predicted the occurrence of clinical events with an area under the curve of 0.82 (95% CI 0.71-0.93). Bowel stiffness ≥ 3.57 kPa was associated with an increased risk of clinical events (p < 0.0001). CONCLUSION: In Crohn's disease, magnetic resonance elastography is a reliable tool for detecting intestinal fibrosis and predicting a worse disease outcome.

MR electrical properties imaging using a generalized image-based method.

PURPOSE: To develop a fast and easy-to-use electrical properties tomography (EPT) method based on a single MR scan, avoiding both the need of a B1 -map and transceive phase assumption, and that is robust against noise. THEORY: Derived from Maxwell's equations, conductivity, and permittivity are reconstructed from a new partial differential equation involving the product of the RF fields and its derivatives. This also allows us to clarify and revisit the relevance of common assumptions of MREPT. METHODS: Our new governing equation is solved using a 3D finite-difference scheme and compared to previous frameworks. The benefits of our method over selected existing MREPT methods are demonstrated for different simulation models, as well as for both an inhomogeneous agar phantom gel and in vivo brain data at 3T. RESULTS: Simulation and experimental results are illustrated to highlight the merits of the proposed method over existing methods. We show the validity of our algorithm in versatile configurations, with many transition regions notably. Complex admittivity maps are also provided as a complementary MR contrast. CONCLUSION: Because it avoids time-consuming RF field mapping and generalizes the use of standard MR image for electrical properties reconstruction, this contribution is promising as a new step forward for clinical applications.

Quantification and mapping of cerebral hemodynamics before and after carotid endarterectomy, using four-dimensional flow magnetic resonance imaging.

BACKGROUND: Carotid stenosis can profoundly affect cerebral hemodynamics, which cannot simply be inferred from the degree of stenosis. We quantified and mapped the distribution of the blood flow rate (BFR) in the cerebral arteries before and after carotid endarterectomy using four-dimensional (4D) phase-contrast (PC) magnetic resonance imaging (MRI). METHODS: Nineteen patients (age, 71 ± 6 years; 2 women) with symptomatic carotid stenosis (≥50%) undergoing carotid endarterectomy (CEA) were investigated using 4D PC-MRI before and after surgery. The BFR was measured in 17 cerebral arteries and the ophthalmic arteries. Collateral recruitment through the anterior and posterior communicating arteries, ophthalmic arteries, and leptomeningeal arteries was quantified. BFR laterality was significantly different between the paired contralateral and ipsilateral arteries. Subgroups were defined according to the presence of collateral recruitment. RESULTS: The total cerebral blood flow had increased by 15% (P < .01) after CEA. Before CEA, laterality was seen in the internal carotid artery, anterior cerebral artery, and middle cerebral artery (MCA). On the ipsilateral side, an increased BFR was found after CEA in the internal carotid artery (246 ± 62 mL/min vs 135 ± 80 mL/min; P < .001), anterior cerebral artery (87 ± mL/min vs 38 ± 58 mL/min; P < .01), and MCA (149 ± 43 mL/min vs 119 ± 34 mL/min; P < .01), resulting in a postoperative BFR distribution without signs of laterality. In the nine patients with preoperatively recruited collaterals, BFR laterality was found in the MCA before, but not after, CEA (P < .01). This laterality was not found in the 10 patients without collateral recruitment (P = .2). The degree of stenosis did not differ between the groups with and without collateral recruitment (P = .85). CONCLUSIONS: Using 4D PC-MRI, we have presented a comprehensive and noninvasive method to evaluate the cerebral hemodynamics due to carotid stenosis before and after CEA. MCA laterality, seen in the patients with collateral recruitment before CEA, pointed toward a hemodynamic disturbance in MCA territory for those patients. This methodologic advancement provides an insight into the pathophysiology of cerebral hemodynamics in patients with carotid stenosis.

Influence of portal vein occlusion on portal flow and liver elasticity in an animal model.

Hepatic fibrosis causes an increase in liver stiffness, a parameter measured by elastography and widely used as a diagnosis method. The concomitant presence of portal vein thrombosis (PVT) implies a change in hepatic portal inflow that could also affect liver elasticity. The main objective of this study is to determine the extent to which the presence of portal occlusion can affect the mechanical properties of the liver and potentially lead to misdiagnosis of fibrosis and hepatic cirrhosis by elastography. Portal vein occlusion was generated by insertion and inflation of a balloon catheter in the portal vein of four swines. The portal flow parameters peak flow (PF) and peak velocity magnitude (PVM) and liver mechanical properties (shear modulus) were then investigated using 4D-flow MRI and MR elastography, respectively, for progressive obstructions of the portal vein. Experimental results indicate that the reduction of the intrahepatic venous blood flow (PF/PVM decreases of 29.3%/8.5%, 51.0%/32.3% and 83.3%/53.6%, respectively) measured with 50%, 80% and 100% obstruction of the portal vein section results in a decrease of liver stiffness by 0.8% ± 0.1%, 7.7% ± 0.4% and 12.3% ± 0.9%, respectively. While this vascular mechanism does not have sufficient influence on the elasticity of the liver to modify the diagnosis of severe fibrosis or cirrhosis (F4 METAVIR grade), it may be sufficient to attenuate the increase in stiffness due to moderate fibrosis (F2-F3 METAVIR grades) and consequently lead to false-negative diagnoses with elastography in the presence of PVT.

Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness.

OBJECTIVES: We evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer. METHODS: 210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed. RESULTS: A MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively. CONCLUSION: The MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer. KEY POINTS: • Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.

Blood Flow Lateralization and Collateral Compensatory Mechanisms in Patients With Carotid Artery Stenosis.

Background and Purpose- Four-dimensional phase-contrast magnetic resonance imaging enables quantification of blood flow rate (BFR; mL/min) in multiple cerebral arteries simultaneously, making it a promising technique for hemodynamic investigation in patients with stroke. The aim of this study was to quantify the hemodynamic disturbance and the compensatory pattern of collateral flow in patients with symptomatic carotid stenosis. Methods- Thirty-eight patients (mean, 72 years; 27 men) with symptomatic carotid stenosis (≥50%) or occlusion were investigated using 4-dimensional phase-contrast magnetic resonance imaging. For each patient, BFR was measured in 19 arteries/locations. The ipsilateral side to the symptomatic carotid stenosis was compared with the contralateral side. Results- Internal carotid artery BFR was lower on the ipsilateral side (134±87 versus 261±95 mL/min; P<0.001). BFR in anterior cerebral artery (A1 segment) was lower on ipsilateral side (35±58 versus 119±72 mL/min; P<0.001). Anterior cerebral artery territory bilaterally was primarily supplied by contralateral internal carotid artery. The ipsilateral internal carotid artery mainly supplied the ipsilateral middle cerebral artery (MCA) territory. MCA was also supplied by a reversed BFR found in the ophthalmic and the posterior communicating artery routes on the ipsilateral side (-5±28 versus 10±28 mL/min, P=0.001, and -2±12 versus 6±6 mL/min, P=0.03, respectively). Despite these compensations, BFR in MCA was lower on the ipsilateral side, and this laterality was more pronounced in patients with severe carotid stenosis (≥70%). Although comparing ipsilateral MCA BFR between stenosis groups (<70% and ≥70%), there was no difference ( P=0.95). Conclusions- With a novel approach using 4-dimensional phase-contrast magnetic resonance imaging, we could simultaneously quantify and rank the importance of collateral routes in patients with carotid stenosis. An important observation was that contralateral internal carotid artery mainly secured the bilateral anterior cerebral artery territory. Because of the collateral recruitment, compromised BFR in MCA is not necessarily related to the degree of carotid stenosis. These findings highlight the importance of simultaneous investigation of the hemodynamics of the entire cerebral arterial tree.

The pressure difference between eye and brain changes with posture.

OBJECTIVE: The discovery of a posture-dependent effect on the difference between intraocular pressure (IOP) and intracranial pressure (ICP) at the level of lamina cribrosa could have important implications for understanding glaucoma and idiopathic intracranial hypertension and could help explain visual impairments in astronauts exposed to microgravity. The aim of this study was to determine the postural influence on the difference between simultaneously measured ICP and IOP. METHODS: Eleven healthy adult volunteers (age = 46 ± 10 years) were investigated with simultaneous ICP, assessed through lumbar puncture, and IOP measurements when supine, sitting, and in 9° head-down tilt (HDT). The trans-lamina cribrosa pressure difference (TLCPD) was calculated as the difference between the IOP and ICP. To estimate the pressures at the lamina cribrosa, geometrical distances were estimated from magnetic resonance imaging and used to adjust for hydrostatic effects. RESULTS: The TLCPD (in millimeters of mercury) between IOP and ICP was 12.3 ± 2.2 for supine, 19.8 ± 4.6 for sitting, and 6.6 ± 2.5 for HDT. The expected 24-hour average TLCPD on earth-assuming 8 hours supine and 16 hours upright-was estimated to be 17.3mmHg. By removing the hydrostatic effects on pressure, a corresponding 24-hour average TLCPD in microgravity environment was simulated to be 6.7mmHg. INTERPRETATION: We provide a possible physiological explanation for how microgravity can cause symptoms similar to those seen in patients with elevated ICP. The observed posture dependency of TLCPD also implies that assessment of the difference between IOP and ICP in upright position may offer new understanding of the pathophysiology of idiopathic intracranial hypertension and glaucoma. Ann Neurol 2016;80:269-276.

Automatic labeling of cerebral arteries in magnetic resonance angiography.

OBJECTIVES: In order to introduce 4D flow magnetic resonance imaging (MRI) as a standard clinical instrument for studying the cerebrovascular system, new and faster postprocessing tools are necessary. The objective of this study was to construct and evaluate a method for automatic identification of individual cerebral arteries in a 4D flow MRI angiogram. MATERIALS AND METHODS: Forty-six elderly individuals were investigated with 4D flow MRI. Fourteen main cerebral arteries were manually labeled and used to create a probabilistic atlas. An automatic atlas-based artery identification method (AAIM) was developed based on vascular-branch extraction and the atlas was used for identification. The method was evaluated by comparing automatic with manual identification in 4D flow MRI angiograms from 67 additional elderly individuals. RESULTS: Overall accuracy was 93%, and internal carotid artery and middle cerebral artery labeling was 100% accurate. Smaller and more distal arteries had lower accuracy; for posterior communicating arteries and vertebral arteries, accuracy was 70 and 89%, respectively. CONCLUSION: The AAIM enabled fast and fully automatic labeling of the main cerebral arteries. AAIM functionality provides the basis for creating an automatic and powerful method to analyze arterial cerebral blood flow in clinical routine.

Brain parenchymal fraction in an age-stratified healthy population - determined by MRI using manual segmentation and three automated segmentation methods.

BACKGROUND AND PURPOSE: Brain atrophy is a prominent feature in many neurodegenerative diseases, such as multiple sclerosis, but age-related decrease of brain volume occurs regardless of pathological neurodegeneration. Changes in brain volume can be described by use of the brain parenchymal fraction (BPF), most often defined as the ratio of total brain parenchyma to total intracranial space. The BPF is of interest both in research and in clinical practice. To be able to properly interpret this variable, the normal range of BPF must be known. The objective of this study is to present normal values for BPF, stratified by age, and compare manual BPF measurement to three automated methods. MATERIALS AND METHODS: The BPFs of 106 healthy individuals aged 21 to 85 years were determined by the automated segmentation methods SyMap, VBM8 and SPM12. In a subgroup of 54 randomly selected individuals, the BPF was also determined by manual segmentation. RESULTS: The median (IQR) BPFs of the whole study population were 0.857 (0.064), 0.819 (0.028) and 0.784 (0.073) determined by SyMap, VBM8 and SPM12, respectively. The BPF decreased with increasing age. The correlation coefficients between manual segmentation and SyMap, VBM8 and SPM12 were 0.93 (P<0.001), 0.77 (P<0.001) and 0.56 (P<0.001), respectively. CONCLUSIONS: There was a clear relationship between increasing age and decreasing BPF. Knowledge of the range of normal BPF in relation to age group will help in the interpretation of BPF data. The automated segmentation methods displayed varying degrees of similarity to the manual reference, with SyMap being the most similar.

Fast 4D flow MRI intracranial segmentation and quantification in tortuous arteries.

PURPOSE: To describe, validate, and implement a centerline processing scheme (CPS) for semiautomated segmentation and quantification in carotid siphons of healthy subjects. 4D flow MRI enables blood flow measurement in all major cerebral arteries with one scan. Clinical translational hurdles are time demanding postprocessing and user-dependence induced variability during analysis. MATERIALS AND METHODS: A CPS for 4D flow data was developed to automatically separate cerebral artery trees. Flow parameters were quantified at planes along the centerline oriented perpendicular to the vessel path. At 3T, validation against 2D phase-contrast (PC) magnetic resonance imaging (MRI) and 4D flow manual processing was performed on an intracranial flow phantom for constant flow, while pulsatile flow validation was performed in the internal carotid artery (ICA) of 10 healthy volunteers. The CPS and 4D manual processing times were measured and compared. Flow and area measurements were also demonstrated along the length of the ICA siphon. RESULTS: Phantom measurements for area and flow were highly correlated between the CPS and 2D measurements (area: R = 0.95, flow: R = 0.94), while in vivo waveforms were highly correlated (R = 0.93). Processing time was reduced by a factor of 4.6 compared with manual processing. Whole ICA measurements revealed a significantly decreased area in the most distal segment of the carotid siphon (P = 0.0017), with flow unchanged (P = 0.84). CONCLUSION: This study exhibits fast semiautomated analysis of intracranial 4D flow MRI. Internal consistency was shown through flow conservation along the tortuous ICA siphon, which is typically difficult to assess.

Changes of in vivo electrical conductivity in the brain and torso related to age, fat fraction and sex using MRI.

This work was inspired by the observation that a majority of MR-electrical properties tomography studies are based on direct comparisons with ex vivo measurements carried out on post-mortem samples in the 90's. As a result, the in vivo conductivity values obtained from MRI in the megahertz range in different types of tissues (brain, liver, tumors, muscles, etc.) found in the literature may not correspond to their ex vivo equivalent, which still serves as a reference for electromagnetic modelling. This study aims to pave the way for improving current databases since the definition of personalized electromagnetic models (e.g. for Specific Absorption Rate estimation) would benefit from better estimation. Seventeen healthy volunteers underwent MRI of both brain and thorax/abdomen using a three-dimensional ultrashort echo-time (UTE) sequence. We estimated conductivity (S/m) in several classes of macroscopic tissue using a customized reconstruction method from complex UTE images, and give general statistics for each of these regions (mean-median-standard deviation). These values are used to find possible correlations with biological parameters such as age, sex, body mass index and/or fat volume fraction, using linear regression analysis. In short, the collected in vivo values show significant deviations from the ex vivo values in conventional databases, and we show significant relationships with the latter parameters in certain organs for the first time, e.g. a decrease in brain conductivity with age.

Characterization of susceptibility artifacts in magnetic resonance thermometry images during laser interstitial thermal therapy: dimension analysis and temperature error estimation.

Objective.Laser interstitial thermal therapy (LITT) is a minimally invasive procedure used to treat a lesion through light irradiation and consequent temperature increase. Magnetic resonance thermometry imaging (MRTI) provides a multidimensional measurement of the temperature inside the target, thus enabling accurate monitoring of the damaged zone during the procedure. In proton resonance frequency shift-based thermometry, artifacts in the images may strongly interfere with the estimated temperature maps. In our work, after noticing the formation of the dipolar-behavior artifact linkable to magnetic susceptibility changes duringin vivoLITT, an investigation of susceptibility artifacts in tissue-mimicking phantoms was implemented.Approach.The artifact was characterized: (i) by measuring the area and total volume of error regions and their evolution during the treatment; and (ii) by comparison with temperature reference provided by three temperature sensing needles. Lastly, a strategy to avoid artifacts formation was devised by using the temperature-sensing needles to implement a temperature-controlled LITT.Main results.The artifact appearance was associated with gas bubble formation and with unwanted treatment effects producing magnetic susceptibility changes when 2 W laser power was set. The analysis of the artifact's dimension demonstrated that in the sagittal plane the dipolar-shape artifact may consistently spread following the temperature trend until reaching a volume 8 times bigger than the ablated one. Also, the artifact shape is quite symmetric with respect to the laser tip. An absolute temperature error showing a negative Gaussian profile in the area of susceptibility artifact with values up to 64.4 °C was estimated. Conversely, a maximum error of 2.8 °C is measured in the area not-affected by artifacts and far from the applicator tip. Finally, by regulating laser power, susceptibility artifacts formation was avoided, and appreciable thermal damage was induced.Significance.These findings may help in improving the MRTI-based guidance of thermal therapies.

4D segmentation of the thoracic aorta from 4D flow MRI using deep learning.

BACKGROUND: 4D flow MRI allows the analysis of hemodynamic changes in the aorta caused by pathologies such as thoracic aortic aneurysms (TAA). For personalized management of TAA, new biomarkers are required to analyze the effect of fluid structure iteration which can be obtained from 4D flow MRI. However, the generation of these biomarkers requires prior 4D segmentation of the aorta. OBJECTIVE: To develop an automatic deep learning model to segment the aorta in 4D from 4D flow MRI. METHODS: Segmentation is addressed with a U-Net based segmentation model that treats each 4D flow MRI frame as an independent sample. Performance is measured with respect to Dice score (DS) and Hausdorff distance (HD). In addition, the maximum and minimum surface areas at the level of the ascending aorta are measured and compared with those obtained from cine-MRI. RESULTS: The segmentation performance was 0.90 ± 0.02 for the DS and the mean HD was 9.58 ± 4.36 mm. A correlation coefficient of r = 0.85 was obtained for the maximum surface and r = 0.86 for the minimum surface between the 4D flow MRI and cine-MRI. CONCLUSION: The proposed automatic approach of 4D aortic segmentation from 4D flow MRI seems to be accurate enough to contribute to the wider use of this imaging technique in the analysis of pathologies such as TAA.

Phase contrast MRI quantification of pulsatile volumes of brain arteries, veins, and cerebrospinal fluids compartments: repeatability and physiological interactions.

PURPOSE: To study measurement repeatability and physiological determinants on measurement stability for phase contrast MRI (PC-MRI) measurements of cyclic volume changes (ΔV) of brain arteries, veins, and cerebrospinal fluid (CSF) compartments. MATERIALS AND METHODS: Total cerebral blood flow (tCBF), total internal jugular flow (tJBF) and spinal CSF flow at C2-C3 level and CSF in the aqueduct was measured using five repetitions in 20 healthy subjects. After subtracting net flow, waveforms were integrated to calculate ΔV of arterial, venous, and cerebrospinal fluid compartments. The intraclass correlation coefficient (ICC) was used to measure repeatability. Systematic errors were investigated by a series of phantom measurements. RESULTS: For ΔV calculated from tCBF, tJBF and both CSF waveforms, the ICC was ≥0.85. ΔV from the tCBF waveform decreased linearly between repetitions (P = 0.012). Summed CSF and venous volume being shifted out from the cranium was correlated with ΔV calculated from the tCBF waveform (r = 0.75; P < 0.001). Systematic errors increased at resolutions <4 pixels per diameter. CONCLUSION: Repeatability of ΔV calculated from tCBF, tJBF, and CSF waveforms allows useful interpretations. The subject's time in the MR system and imaging resolution should be considered when interpreting volume changes. Summed CSF and venous volume changes was associated with arterial volume changes.

Comparison of T2 Quantification Strategies in the Abdominal-Pelvic Region for Clinical Use.

OBJECTIVES: The aim of the study was to compare different magnetic resonance imaging (MRI) acquisition strategies appropriate for T2 quantification in the abdominal-pelvic area. The different techniques targeted in the study were chosen according to 2 main considerations: performing T2 measurement in an acceptable time for clinical use and preventing/correcting respiratory motion. MATERIALS AND METHODS: Acquisitions were performed at 3 T. To select sequences for in vivo measurements, a phantom experiment was conducted, for which the T2 values obtained with the different techniques of interest were compared with the criterion standard (single-echo SE sequence, multiple acquisitions with varying echo time). Repeatability and temporal reproducibility studies for the different techniques were also conducted on the phantom. Finally, an in vivo study was conducted on 12 volunteers to compare the techniques that offer acceptable acquisition time for clinical use and either address or correct respiratory motion. RESULTS: For the phantom study, the DESS and T2-preparation techniques presented the lowest precision (ρ2 = 0.9504 and ρ2 = 0.9849 respectively), and showed a poor repeatability/reproducibility compared with the other techniques. The strategy relying on SE-EPI showed the best precision and accuracy (ρ2 = 0.9994 and Cb = 0.9995). GRAPPATINI exhibited a very good precision (ρ2 = 0.9984). For the technique relying on radial TSE, the precision was not as good as GRAPPATINI (ρ2 = 0.9872). The in vivo study demonstrated good respiratory motion management for all of the selected techniques. It also showed that T2 estimate ranges were different from one method to another. For GRAPPATINI and radial TSE techniques, there were significant differences between all the different types of organs of interest. CONCLUSIONS: To perform T2 measurement in the abdominal-pelvic region, one should favor a technique with acceptable acquisition time for clinical use, with proper respiratory motion management, with good repeatability, reproducibility, and precision. In this study, the techniques relying respectively on SE-EPI, radial TSE, and GRAPPATINI appeared as good candidates.

Fast T2-weighted liver MRI: Image quality and solid focal lesions conspicuity using a deep learning accelerated single breath-hold HASTE fat-suppressed sequence.

PURPOSE: Acceleration of MRI acquisitions and especially of T2-weighted sequences is essential to reduce the duration of MRI examinations but also kinetic artifacts in liver imaging. The purpose of this study was to compare the acquisition time and the image quality of a single-shot fat-suppressed turbo spin-echo (TSE) T2-weighted sequence with deep learning reconstruction (HASTEDL) with that of a fat-suppressed T2-weighted BLADE TSE sequence in patients with focal liver lesions. MATERIALS AND METHODS: Ninety-five patients (52 men, 43 women; mean age: 61 ± 14 [SD]; age range: 28-87 years) with 42 focal liver lesions (17 hepatocellular carcinomas, 10 sarcoidosis lesions, 9 myeloma lesions, 3 liver metastases and 3 focal nodular hyperplasias) who underwent liver MRI at 1.5 T including HASTEDL and BLADE sequences were retrospectively included. Overall image quality, noise level in the liver, lesion conspicuity and sharpness of liver lesion contours were assessed by two independent readers. Liver signal-to-noise ratio (SNR) and lesion contrast-to-noise ratio (CNR) were measured and compared between the two sequences, as well as the mean duration of the sequences (Student t-test or Wilcoxon test for paired data). RESULTS: Median overall quality on HASTEDL images (3; IQR: 3, 3) was significantly greater than that on BLADE images (2; IQR: 1, 3) (P < 0.001). Median noise level in the liver on HASTEDL images (0; IQR: 0, 0.5) was significantly lower than that on BLADE images (1; IQR: 1, 2) (P < 0.001). On HASTEDL images, mean liver SNR (107.3 ± 39.7 [SD]) and mean focal liver lesion CNR (87.0 ± 76.6 [SD]) were significantly greater than those on BLADE images (67.1 ± 23.8 [SD], P < 0.001 and 48.6 ± 43.9 [SD], P = 0.027, respectively). Acquisition time was significantly shorter with the HASTEDL sequence (18 ± [0] s; range: 18-18 s) compared to BLADE sequence (152 ± 47 [SD] s; range: 87-263 s) (P < 0.001). CONCLUSION: By comparison with the BLADE sequence, HASTEDL sequence significantly reduces acquisition time while improving image quality, liver SNR and focal liver lesions CNR.