Combined prenatal US and post-mortem fetal MRI: can they replace conventional autopsy for fetal body abnormalities?

OBJECTIVES: The acceptance of conventional autopsy (CA), the gold standard method for investigating fetal death, often remains problematic. Post-mortem magnetic resonance imaging (PMMRI) is increasingly advocated, particularly for neurologic malformations. However, PMMRI performances to diagnose non-neurologic malformations remain unclear. We aim to clarify whether a full body CA remains needed after prenatal ultrasound (US) and PMMRI in assessing non-neurologic fetal malformations. METHODS: In this retrospective IRB-approved study, during a 6-year period, all fetuses who underwent PMMRI, prenatal US, and full body CA were included. Body abnormalities were identified in US, PMMRI, and CA reports. US and PMMRI images were all reviewed. All abnormalities were graded as major (2 points) or minor (1 point). Each technique (US, PMMRI, CA) was given a score by adding all grading points. In each fetus, results were compared for both separate and combined US and PMMRI to CA. Sensitivity and specificity were calculated for detecting major abnormalities. RESULTS: Fifty fetuses were included. The score of CA, US, and PMMRI was respectively 53, 37, and 46. Compared with US-PMMRI, CA added information in 2 cases (4%) with major abnormalities and 7 cases (14%) with minor abnormalities. PMMRI and US were concordant in 36/50 (72%) fetuses. Separate US/PMMRI sensitivities and specificities for detecting major body malformations respectively were 80%/80% and 100%/94%. Combined US-PMMRI had a sensitivity of 90% and a specificity of 94%. Two cardiac malformations (2/6) were only described by CA. CONCLUSIONS: After prenatal US and PMMRI, few additional fetal body malformations are discovered with CA. Nevertheless, fetal heart autopsy remains mandatory. CLINICAL RELEVANCE STATEMENT: A cardiac conventional autopsy complemented by prenatal ultrasound and post-mortem MRI allows to detect all major fetal body abnormalities. With this efficient and much less invasive approach, a higher acceptance rate of fetal autopsy can be expected. KEY POINTS: • Excepting cardiac malformations, most major fetal body malformations can reliably be identified by prenatal US combined with post-mortem MRI. • In the post-mortem diagnosis of fetal body malformations, a conventional autopsy limited to the fetal heart might replace a full body autopsy after a well-conducted prenatal US and post-mortem MRI.

Comparison of intra- and inter-patient intensity standardization methods for multi-parametric whole-body MRI.

Objective.To test and compare different intensity standardization approaches for whole-body multi-parametric MR images, aiming to compensate voxel intensity differences between scans. These differences, common for magnetic resonance imaging, pose problems in image quantification, assessment of changes between a baseline and follow-up scan, and hinder performance of image processing and machine learning algorithms.Approach.In this work, we present a comparison on the accuracy of intensity standardization approaches with increasing complexity, for intra- and inter-patient multi-parametric whole-body MRI. Several approaches were used: z-scoring of the intensities, piecewise linear mapping and deformable mapping of intensity distributions into established reference intensity space. For each method, the impact on standardization algorithm on the use of single image or average population distribution reference; as well as, whole image and region of interest were additionally investigated. All methods were validated on a data set of 18 whole-body anatomical and diffusion-weighted MR scans consisting of baseline and follow-up examinations acquired from advanced prostate cancer patients and healthy volunteers.Main results.The piecewise linear intensity standardisation approach provided the best compromise between standardization accuracy and method stability, with average deviations in intensity profile of 0.011-0.027 and mean absolute difference of 0.29-0.37 standard score (intra-patient) and 0.014-0.056 (inter-patient), depending on the type of used MR modality.Significance.Linear piecewise approaches showed the overall best performance across multiple validation metrics, mostly because of its robustness. The inter-patient standardization proved to perform better when using population average reference image; in contrary to intra-patient approach, where the best results were achieved by standardizing towards a reference image taken as the baseline scan.

Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas, the most common primary brain tumors. However, ill-posedness of the initialization at diagnosis time and parameter estimation of such models have restrained their clinical use as a personalized predictive tool. In this work, we investigate the ability of deep convolutional neural networks (DCNNs) to address commonly encountered pitfalls in the field. Based on 1200 synthetic tumors grown over real brain geometries derived from magnetic resonance (MR) data of six healthy subjects, we demonstrate the ability of DCNNs to reconstruct a whole tumor cell-density distribution from only two imaging contours at a single time point. With an additional imaging contour extracted at a prior time point, we also demonstrate the ability of DCNNs to accurately estimate the individual diffusivity and proliferation parameters of the model. From this knowledge, the spatio-temporal evolution of the tumor cell-density distribution at later time points can ultimately be precisely captured using the model. We finally show the applicability of our approach to MR data of a real glioblastoma patient. This approach may open the perspective of a clinical application of reaction-diffusion growth models for tumor prognosis and treatment planning.

Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study.

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas. Nevertheless, these models require an initial condition: the tumor cell density distribution over the whole brain at diagnosis time. Several works have proposed to relate this distribution to abnormalities visible on magnetic resonance imaging (MRI). In this work, we verify these hypotheses by stereotactic histological analysis of a non-operated brain with glioblastoma using a 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2-FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously proposed exponential decrease of the tumor cell density with the distance to the core is reasonable but (ii) the edema outlines would not correspond to a cell density iso-contour and (iii) the suggested tumor cell density at these outlines is likely overestimated. These findings highlight the limitations of conventional MRI to derive glioma cell density maps and the need for other initialization methods for reaction-diffusion models to be used in clinical practice.

Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients.

Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosis. However, most of these studies are based on hand-crafted qualitative or semi-quantitative features extracted from the mean time activity curve within predefined volumes. Voxelwise dynamic PET data analysis could instead provide a better insight into intra-tumor heterogeneity of gliomas. In this work, we investigate the ability of principal component analysis (PCA) to extract relevant quantitative features from a large number of motion-corrected [S-methyl-11C]methionine ([11C]MET) PET frames. We first demonstrate the robustness of our methodology to noise by means of numerical simulations. We then build a PCA model from dynamic [11C]MET acquisitions of 20 glioma patients. In a distinct cohort of 13 glioma patients, we compare the parametric maps derived from our PCA model to these provided by the classical one-compartment pharmacokinetic model (1TCM). We show that our PCA model outperforms the 1TCM to distinguish characteristic dynamic uptake behaviors within the tumor while being less computationally expensive and not requiring arterial sampling. Such methodology could be valuable to assess the tumor aggressiveness locally with applications for treatment planning and response evaluation. This work further supports the added value of dynamic over static [11C]MET PET in gliomas.

Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study.

OBJECTIVES: Multicenter oncology trials increasingly include MRI examinations with apparent diffusion coefficient (ADC) quantification for lesion characterization and follow-up. However, the repeatability and reproducibility (R&R) limits above which a true change in ADC can be considered relevant are poorly defined. This study assessed these limits in a standardized whole-body (WB)-MRI protocol. METHODS: A prospective, multicenter study was performed at three centers equipped with the same 3.0-T scanners to test a WB-MRI protocol including diffusion-weighted imaging (DWI). Eight healthy volunteers per center were enrolled to undergo test and retest examinations in the same center and a third examination in another center. ADC variability was assessed in multiple organs by two readers using two-way mixed ANOVA, Bland-Altman plots, coefficient of variation (CoV), and the upper limit of the 95% CI on repeatability (RC) and reproducibility (RDC) coefficients. RESULTS: CoV of ADC was not influenced by other factors (center, reader) than the organ. Based on the upper limit of the 95% CI on RC and RDC (from both readers), a change in ADC in an individual patient must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central and peripheral zones of the prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be significant. CONCLUSIONS: This study proposes R&R limits above which ADC changes can be considered as a reliable quantitative endpoint to assess disease or treatment-related changes in the tissue microstructure in the setting of multicenter WB-MRI trials. KEY POINTS: • The present study showed the range of R&R of ADC in WB-MRI that may be achieved in a multicenter framework when a standardized protocol is deployed. • R&R was not influenced by the site of acquisition of DW images. • Clinically significant changes in ADC measured in a multicenter WB-MRI protocol performed with the same type of MRI scanner must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central zone and peripheral zone of prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be detected with a 95% confidence level.

Relationship Between White Matter Abnormalities and Neuropsychological Measures in Children With ADHD.

Objective: Using Diffusion Tensor Imaging (DTI), to investigate microstructural white matter differences between ADHD and typically developing children (TDC), and their association with inhibition and working memory performance usually impaired in ADHD. Method: Fractional anisotropy (FA) and mean diffusivity (MD) were estimated in 36 noncomorbid children with a Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) diagnosis of combined type ADHD and 20 TDC. Correlations between FA/MD and Stop Signal Task and N-Back performance parameters were computed. Results: Working memory performance was significantly associated with MD in the superior longitudinal fasciculus (SLF) and the cingulum in the ADHD group. No between-group differences in FA/MD reached significance, after controlling for between-group head motion differences. Conclusion: The association between white matter integrity in the cingulum and the SLF and working memory performance confirms previous studies. Our results also show that when critical conditions are controlled (age, comorbidity, head motion), no ADHD-related structural abnormality (FA/MD) are observed, in line with prior suggestions.

Multi-atlas segmentation of the skeleton from whole-body MRI-Impact of iterative background masking.

PURPOSE: To improve multi-atlas segmentation of the skeleton from whole-body MRI. In particular, we study the effect of employing the atlas segmentations to iteratively mask tissues outside of the region of interest to improve the atlas alignment and subsequent segmentation. METHODS: An improved atlas registration scheme is proposed. Starting from a suitable initial alignment, the alignment is refined by introducing additional stages of deformable registration during which the image sampling is limited to the dilated atlas segmentation label mask. The performance of the method was demonstrated using leave-one-out cross-validation using atlases of 10 whole-body 3D-T1 images of prostate cancer patients with bone metastases and healthy male volunteers, and compared to existing state of the art. Both registration accuracy and resulting segmentation quality, using four commonly used label fusion strategies, were evaluated. RESULTS: The proposed method showed significant improvement in registration and segmentation accuracy with respect to the state of the art for all validation criteria and label fusion strategies, resulting in a Dice coefficient of 0.887 (STEPS label fusion). The average Dice coefficient for the multi-atlas segmentation showed over 11% improvement with a decrease of false positive rate from 28.3% to 13.2%. For this application, repeated application of the background masking did not lead to significant improvement of the segmentation result. CONCLUSIONS: A registration strategy, relying on the use of atlas segmentations as mask during image registration was proposed and evaluated for multi-atlas segmentation of whole-body MRI. The approach significantly improved registration and final segmentation accuracy and may be applicable to other structures of interest.

Dopamine transporter genotype modulates brain activity during a working memory task in children with ADHD.

Dopamine active transporter gene (DAT1) is a candidate gene associated with attention-deficit/hyperactivity disorder (ADHD). The DAT1 variable number tandem repeat (VNTR)-3' polymorphism is functional and 9R carriers have been shown to produce more DAT than 10R homozygotes. We used functional magnetic resonance imaging (fMRI) to investigate the effects of this polymorphism on the neural substrates of working memory (WM) in a small but selected population of children with ADHD, naïve of any psychotropic treatment and without comorbidity. MRI and genotype data were obtained for 36 children (mean age: 10,36 +/- 1,49 years) with combined-type ADHD (9R n = 15) and 25 typically developing children (TDC) (mean age: 9,55 +/- 1,25 years) (9R n = 12). WM performance was similar between conditions. We found a cross-over interaction effect between gene (9R vs. 10R) and diagnosis (TDC vs. ADHD) in the orbito-frontal gyrus, cerebellum and inferior temporal lobe. In these areas, WM-related activity was higher for 9R carriers in ADHD subjects and lower in TDC. In ADHD children only, 10R homozygotes exhibited higher WM-related activity than 9R carriers in a network encompassing the parietal and the temporal lobes, the ventral visual cortex, the orbito-frontal gyrus and the head of the caudate nucleus. There was no significant results in TDC group. Our preliminary findings suggest that DAT1 VNTR polymorphism can modulate WM-related brain activity ADHD children.

Assessment of cardiac-driven liver movements with filtered harmonic phase image representation, optical flow quantification, and motion amplification.

PURPOSE: To characterize cardiac-driven liver movements using a harmonic phase image representation (HARP) with an optical flow quantification and motion amplification method. The method was applied to define the cardiac trigger delay providing minimal signal losses in liver DWI images. METHODS: The 16-s breath-hold balanced-SSFP time resolved 20 images/s were acquired at 3T in coronal and sagittal orientations. A peripheral pulse unit signal was recorded. Cardiac-triggered DWI images were acquired after different peripheral pulse unit delays. A steerable pyramid decomposition with multiple orientations and spatial frequencies was applied. The liver motion field-map was derived from temporal variations of the HARP representation filtered around the cardiac frequency. Liver displacements were quantified with an optical flow method; moreover the right liver motion was amplified. RESULTS: The largest displacements were observed in the left liver (feet-head:3.70 ± 1.06 mm; anterior-posterior: 2.35 ± 0.51 mm). Displacements were statistically significantly weaker in the middle right liver (0.47 ± 0.11 mm; P = 0.0156). The average error was 0.013 ± 0.022 mm (coronal plane) and 0.021 ± 0.041 mm (sagittal plane). The velocity field demonstrated opposing movements of the right liver extremities during the cardiac cycle. DWI signal loss was minimized in regions and instants of smallest amplitude of both velocity and velocity gradient. CONCLUSION: Cardiac-driven liver movements were quantified with combined cardiac frequency-filtered HARP and optical flow methods. A motion phase opposition between right liver extremities was demonstrated. Displacement amplitude and velocity were larger in the left liver especially along the vertical direction. Motion amplification visually emphasized cardiac-driven right liver displacements. The optimal cardiac timing minimizing signal loss in liver DWI images was derived.

Assessment of response to chemotherapy in pancreatic ductal adenocarcinoma: Comparison between diffusion-weighted MR quantitative parameters and RECIST.

PURPOSE: To prospectively assess chemotherapy-induced changes in pancreatic ductal adenocarcinoma (PDA) with diffusion-weighted (DW)-MR quantitative metrics, including apparent diffusion coefficient (ADC) and histogram-derived parameters, compared with RECIST 1.1. METHODS: 24 patients underwent DW-MR at baseline, week-2 and week-8 after chemotherapy initiation. Tumour diameter was assessed on T2-weighted images. Regions-of-interest (ROI) were drawn on ADC map for ROI-ADC. Volume segmentation (b = 1000 s/mm2 images) provided DW-volume and histogram-derived diffusion parameters (H-ADC, H-D and H-PF). All variables and their relative change were compared to baseline or between responders and non-responders. Discriminant analysis was performed. RESULTS: 15/24 patients were responders. RECIST 1.1 correctly characterized 6/15 responders at week-8. At week-2, in responders DW-volume decreased (P = .002); ROI-ADC mean H-D increased (P = .047; P = .048;). The 25th percentile H-D increased in responders and decreased in non-responders (P = .016; P = .048). At week-8 in responders DW-volume decreased and ROI-ADC mean, 25th, 50th, 75th percentiles of H-ADC and H-D increased (P < .05). No changes were observed in non-responders (P > .05). At week-2, 25th percentile of H-D and H-PF relative change correctly classified 20/24 patients (P = .003); at week-8, DW-volume relative change correctly classified 22/24 patients (P < .0001). CONCLUSIONS: ROI-ADC, DW-volume and histogram-derived diffusion parameters are more accurate to categorize responding and non-responding PDA patients treated with chemotherapy compared with RECIST 1.1.

Total choline quantification measured by 1H MR spectroscopy as early predictor of response after neoadjuvant treatment for locally advanced breast cancer: The impact of immunohistochemical status.

BACKGROUND: Validation of new biomarkers is essential for the early evaluation of neoadjuvant treatments. PURPOSE: To determine whether measurements of total choline (tCho) by 1H spectroscopy could predict morphological or pathological complete response (pCR) of neoadjuvant treatment and whether breast cancer subgroups are related to prediction accuracy. STUDY TYPE: Prospective, nonrandomized, monocentric, diagnostic study. POPULATION: Sixty patients were initially included with 39 women participating in the final cohort. FIELD STRENGTH/SEQUENCE: A 1.5T scanner was used for acquisition and MRS was performed using the syngo GRACE sequence. ASSESSMENT: MRS and MRI examinations were performed at baseline (TP1), 24-72 hours after first chemotherapy (TP2), after the end of anthracycline treatment (TP3), and MRI only after the end of taxane treatment (TP4). Early (EMR) and late (LMR) morphological response were defined as %ΔDmax13 or %ΔDmax14, respectively. Responders were patients with %ΔDmax >30. Pathological complete response (pCR) patients achieved a residual cancer burden score of 0. STATISTICAL TESTS: T-test, receiver operating characteristic (ROC) curves, multiple regression, logistic regression, one-way analysis of variance (ANOVA) analysis were used for the analysis. RESULTS: At TP1 there was a significant difference between response groups for tCho1 concerning EMR prediction (P = 0.05) and pCR (P < 0.05) and for Kep 1 (P = 0.03) concerning LMR prediction. At TP2, no modification of tCho and other parameters could predict response. At TP3, ΔtCho, ΔDmax, and ΔVol could predict LMR (P < 0.05 for all parameters), pCR (P < 0.05 for all parameters), and ΔKtrans could predict only pCR (P = 0.04). Logistic regression at baseline showed the highest area under the curve (AUC) of 0.9 for prediction of pCR. The triple negative (TN) subgroup showed significantly higher tCho at baseline (P = 0.02) and higher ΔtCho levels at TP3 (P < 0.05). DATA CONCLUSION: Baseline measurements of tCho in combination with clinicopathological criteria could predict non-pCR with a high AUC. Furthermore, tCho quantification for prediction of pCR was more sensitive for TN tumors. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:982-993.

Hyperactivity in motor response inhibition networks in unmedicated children with attention deficit-hyperactivity disorder.

OBJECTIVES: Hypo/reduced activity in motor response inhibition (RI) cerebral networks was recently proposed as a promising specific neurobiological marker of attention deficit-hyperactivity disorder (ADHD). Before adopting such a pattern as a key diagnosis tool, we aim to replicate in an independent study the mechanisms underlying reduced RI-related activity in ADHD, after controlling for potentially confounding effects. METHODS: In this fMRI study, we investigated the neural networks mediating successful and failed motor RI in children with ADHD and typically developing children (TDC) using the stop-signal task (SST) paradigm. RESULTS: In contrast to hypofrontality predictions, children with ADHD exhibit increased neural activity during successful response inhibition in an RI-related brain network encompassing the indirect and/or hyperdirect pathways between the basal ganglia and cortex. Voxel-based morphometry analyses have further evidenced reduced grey matter volume in the left caudate in children with ADHD, which paralleled higher functional responses. Finally, connectivity analyses disclosed tighter coupling between a set of cortical regions and the right caudate as well as the right IFG, networks involved in successful RI. CONCLUSIONS: Hypo/reduced activity in RI cerebral networks in children with ADHD cannot at this time be considered as a systematic biomarker for ADHD.

TumourMetrics: a comprehensive clinical solution for the standardization of DCE-MRI analysis in research and routine use.

BACKGROUND: A reliable analysis methodology is needed to provide valuable imaging biomarkers for clinical trials, with particular regards to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) application using pharmacokinetic (PK) model analysis. In order to address this scientific challenge, we provided a comprehensive analysis solution that could overcome the impediments to clinical research and routine use. METHODS: TumourMetrics has been designed to meet the Quantitative Imaging Biomarkers Alliance (QIBA) v.1.0 profile. The quality performance was assessed using the QIBA test data and our customizable numeric phantom. The analysis workflow is made customizable to facilitate standardization of optimized protocol across centers. RESULTS: Our quantification workflow estimated the PK model parameters accurately. The method is robust, almost fully automatic and allows a direct integration of the results into the diagnostic workflow. CONCLUSIONS: The analysis is easy-to-use and accessible for routine implementation of DCE-MRI into clinical practice.

Absence of clinical cerebellar syndrome after serial injections of more than 20 doses of gadoterate, a macrocyclic GBCA: a monocenter retrospective study.

Sound evidence of gadolinium accumulation in brain has been recently provided after repeated administrations of linear gadolinium-based contrast agents (GBCAs), especially at the cerebellum level. Although data regarding brain accumulation of macrocyclic GBCAs are more reassuring, there is now a genuine concern ("gadolinium-phobia") about possible long-term consequences of gadolinium deposits, especially in terms of cerebellar sequelae. We, therefore, questioned about the clinical impact of serial administration of gadoterate meglumine, a macrocyclic GBCA. In this retrospective study (2000-2016) of medical files of patients who received more than 20 administrations of gadoterate, we searched for cerebellar symptoms and signs developing during the regular follow-up. We reviewed medical files of ten patients (mean age 34.4 ± 20.8 years; 4 males, 6 females) who received 28.2 ± 5.3 doses of gadoterate (average total dose of GBCA 518 ± 226 ml; range 185-785 ml). Patients were examined by at least two medical specialists depending on initial diagnosis, and at least once by a neurosurgeon. Mean follow-up time was 91 months (range 49-168) and six out of ten patients experienced new symptoms or signs. No clinician reported the appearance of a rising cerebellar syndrome, nor newly appeared symptoms or signs suggested cerebellar toxicity. This retrospective clinical study shows no de novo clinical cerebellar syndrome following repeated administrations of gadoterate. Our results argue against a cerebellar toxicity of this macrocyclic agent. Still, confirmation in a larger number of subjects is required, as well as clinical studies concerning linear GBCAs whose structure and in vivo stability are distinct.

Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/no-go task by healthy participants.

The ability to suppress responses that are inappropriate, as well as the mechanisms monitoring the accuracy of actions in order to compensate for errors, is central to human behavior. Neural alterations that prevent stopping an inaccurate response, combined with a decreased ability of error monitoring, are considered to be prominent features of alcohol abuse. Moreover, (i) alterations of these processes have been reported in heavy social drinkers (i.e. young healthy individuals who do not yet exhibit a state of alcohol dependence); and (ii) through longitudinal studies, these alterations have been shown to underlie subsequent disinhibition that may lead to future alcohol use disorders. In the present functional magnetic resonance imaging study, using a contextual Go/No-Go task, we investigated whether different neural networks subtended correct inhibitions and monitoring mechanisms of failed inhibitory trials in light versus heavy social drinkers. We show that, although successful inhibition did not lead to significant changes, neural networks involved in error monitoring are different in light versus heavy drinkers. Thus, while light drinkers exhibited activations in their right inferior frontal, right middle cingulate and left superior temporal areas; heavy drinkers exhibited activations in their right cerebellum, left caudate nucleus, left superior occipital region, and left amygdala. These data are functionally interpreted as reflecting a "visually-driven emotional strategy" vs. an "executive-based" neural response to errors in heavy and light drinkers, respectively. Such a difference is interpreted as a key-factor that may subtend the transition from a controlled social heavy consumption to a state of clinical alcohol dependence.