fMRI Methods Research Articles

Diagnostic efficacy of diffusion-weighted imaging and semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging in salivary gland tumors.

Increased use of functional magnetic resonance imaging (MRI) methods such as diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI consisting of sequential contrast series, allows us to obtain more information on the microstructure, cellularity, interstitial distance, and vascularity of tumors, which has increased the discrimination power for benign and malignant salivary gland tumors (SGTs). In the last few years, quantitative DCE MRI data containing T1 perfusion parameters (Ktrans, Kep and Ve), were reported to contribute to the differentiation of benign or malignant subtypes in SGTs. To evaluate the diagnostic efficacy of DWI and semiquantitative and quantitative perfusion MRI parameters in SGTs. Diffusion MRI [apparent diffusion coefficient (ADC) value] with a 1.5 T MR machine, semiquantitative perfusion MRI [time intensity curve (TIC) pattern], and quantitative perfusion MRI examinations (Ktrans, Kep and Ve) of 73 tumors in 67 patients with histopathological diagnosis performed from 2017 to 2021 were retrospectively evaluated. In the ADC value and semiquantitative perfusion MRI measurements, cystic components of the tumors were not considered, and the region of interest (ROI) was manually placed through the widest axial section of the tumor. TIC patterns were divided into four groups: Type A = Tpeak > 120 s; type B = Tpeak ≤ 120 s, washout ratio (WR) ≥ 30%; type C = Tpeak ≤ 120 s, WR < 30%; and type D = flat TIC. For the quantitative perfusion MRI analysis, a 3D ROI was placed in the largest solid component of the tumor, and the Ktrans, Kep and Ve values were automatically generated. The majority of SGTs were located in the parotid glands (86.3%). Of all the SGTs, 68.5% were benign and 31.5% were malignant. Significant differences were found for ADC values among pleomorphic adenomas (PMAs), Warthin's tumors (WTs), and malignant tumors (MTs) (P < 0.001). PMAs had type A and WTs had type B TIC pattern while the vast majority of MTs and other benign tumors (OBTs) (54.5% and 45.5%, respectively) displayed type C TIC pattern. PMAs showed no washout, while the highest mean WR was observed in WTs (59% ± 11%). Ktrans values of PMAs, WTs, OBTs, and MTs were not significantly different. Kep values of PMAs and WTs were significantly different from those of OBTs and MTs. Mean Ve value of WTs was significantly different from those of PMAs, OBTs, and MTs (P < 0.001). The use of quantitative DCE parameters along with diffusion MRI and semiquantitative contrast-enhanced MRI in SGTs could improve the diagnostic accuracy.

Role of ventral subiculum neuronal ensembles in incubation of oxycodone craving after electric barrier-induced voluntary abstinence.

High relapse rate is a key feature of opioid addiction. In humans, abstinence is often voluntary due to negative consequences of opioid seeking. To mimic this human condition, we recently introduced a rat model of incubation of oxycodone craving after electric barrier-induced voluntary abstinence. Incubation of drug craving refers to time-dependent increases in drug seeking after cessation of drug self-administration. Here, we used the activity marker Fos, muscimol-baclofen (GABAa + GABAb receptor agonists) global inactivation, Daun02-selective inactivation of putative relapse-associated neuronal ensembles, and fluorescence-activated cell sorting of Fos-positive cells and quantitative polymerase chain reaction to demonstrate a key role of vSub neuronal ensembles in incubation of oxycodone craving after voluntary abstinence, but not homecage forced abstinence. We also used a longitudinal functional magnetic resonance imaging method and showed that functional connectivity changes in vSub-related circuits predict opioid relapse after abstinence induced by adverse consequences of opioid seeking.

Altered spontaneous brain activity during dobutamine challenge in healthy young adults: A resting-state functional magnetic resonance imaging study.

There is a growing interest in exploring brain-heart interactions. However, few studies have investigated the brain-heart interactions in healthy populations, especially in healthy young adults. The aim of this study was to explore the association between cardiovascular and spontaneous brain activities during dobutamine infusion in healthy young adults. Forty-eight right-handed healthy participants (43 males and 5 females, range: 22-34 years) underwent vital signs monitoring, cognitive function assessment and brain MRI scans. Cardiovascular function was evaluated using blood pressure and heart rate, while two resting-state functional magnetic resonance imaging (rs-fMRI) methods-regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF)-were used together to reflect the local neural activity of the brain. Logistic regression was used to model the association between brain and heart. Results showed that blood pressure and heart rate significantly increased after dobutamine infusion, and the performance in brain functional activity was the decrease in ReHo in the left gyrus rectus and in ALFF in the left frontal superior orbital. The results of logistic regression showed that the difference of diastolic blood pressure (DBP) had significant positive relationship with the degree of change of ReHo, while the difference of systolic blood pressure (SBP) had significant negative impact on the degree of change in ALFF. These findings suggest that the brain-heart interactions exist in healthy young adults under acute cardiovascular alterations, and more attention should be paid to blood pressure changes in young adults and assessment of frontal lobe function to provide them with more effective health protection management.

Cortical areas involved in grasping and reaching actions with and without visual information: An ALE meta-analysis of neuroimaging studies.

The functional specialization of the ventral stream in Perception and the dorsal stream in Action is the cornerstone of the leading model proposed by Goodale and Milner in 1992. This model is based on neuropsychological evidence and has been a matter of debate for almost three decades, during which the dual-visual stream hypothesis has received much attention, including support and criticism. The advent of functional magnetic resonance imaging (fMRI) has allowed investigating the brain areas involved in Perception and Action, and provided useful data on the functional specialization of the two streams. Research on this topic has been quite prolific, yet no meta-analysis so far has explored the spatial convergence in the involvement of the two streams in Action. The present meta-analysis (N=53 fMRI and PET studies) was designed to reveal the specific neural activations associated with Action (i.e., grasping and reaching movements), and the extent to which visual information affects the involvement of the two streams during motor control. Our results provide a comprehensive view of the consistent and spatially convergent neural correlates of Action based on neuroimaging studies conducted over the past two decades. In particular, occipital-temporal areas showed higher activation likelihood in the Vision compared to the No vision condition, but no difference between reach and grasp actions. Frontal-parietal areas were consistently involved in both reach and grasp actions regardless of visual availability. We discuss our results in light of the well-established dual-visual stream model and frame these findings in the context of recent discoveries obtained with advanced fMRI methods, such as multivoxel pattern analysis.

Effect of Acoustic fMRI-Scanner Noise on the Human Resting State

Our knowledge about the human resting state is predominantly based on either electroencephalographic (EEG) or functional magnetic resonance imaging (fMRI) methods. While EEG recordings can be performed in seated posture in quiet conditions, the fMRI environment presents a substantial contrast with supine and restricted posture in a narrow tube that is filled with acoustic scanner noise (ASN) at a chainsaw-like volume level. However, the influence of these diverging conditions on resting-state brain activation is neither well studied nor broadly discussed. In order to promote data as a source of sharper hypotheses for future studies, we investigated alterations in EEG-frequency-band power (delta, theta, alpha, beta, gamma) and spatial power distribution as well as cortical vigilance measures in different postures and ASN surroundings over the course of time. Participants (N = 18) underwent three consecutive resting-state EEG recordings with a fixed posture and ASN setting sequence; seated, supine, and supine with ASN (supnoise) using an MRI simulator. The results showed that compared to seated, supnoise, the last instance within the posture sequence, was characterized by lower power and altered spatial power distribution in all assessed frequency bands. This might also have been an effect of time alone. In delta, theta, alpha, and beta, the power of supnoise was also reduced compared to supine, as well as the corresponding distribution maps. The vigilance analysis revealed that in supine and supnoise, the highest and lowest vigilance stages were more dominant compared to the seated and earliest posture condition within the sequence. Hence, our results demonstrate that the differences in recording settings and progress of time are related to changes in cortical arousal and vigilance regulation, findings that should be taken into account more profoundly for hypothesis generation as well as analytic strategies in future resting-state studies.

Foreground and Background in Mental Models.

Foreground and Background in Mental Models.

Role of Functional MRI in Liver SBRT: Current Use and Future Directions.

Stereotactic body radiation therapy (SBRT) is an emerging treatment for liver cancers whereby large doses of radiation can be delivered precisely to target lesions in 3-5 fractions. The target dose is limited by the dose that can be safely delivered to the non-tumour liver, which depends on the baseline liver functional reserve. Current liver SBRT guidelines assume uniform liver function in the non-tumour liver. However, the assumption of uniform liver function is false in liver disease due to the presence of cirrhosis, damage due to previous chemo- or ablative therapies or irradiation, and fatty liver disease. Anatomical information from magnetic resonance imaging (MRI) is increasingly being used for SBRT planning. While its current use is limited to the identification of target location and size, functional MRI techniques also offer the ability to quantify and spatially map liver tissue microstructure and function. This review summarises and discusses the advantages offered by functional MRI methods for SBRT treatment planning and the potential for adaptive SBRT workflows.

Robust high spatio-temporal line-scanning fMRI in humans at 7T using multi-echo readouts, denoising and prospective motion correction

BackgroundFunctional magnetic resonance imaging (fMRI), typically using blood oxygenation level-dependent (BOLD) contrast weighted imaging, allows the study of brain function with millimeter spatial resolution and temporal resolution of one to a few seconds. At a mesoscopic scale, neurons in the human brain are spatially organized in structures with dimensions of hundreds of micrometers, while they communicate at the millisecond timescale. For this reason, it is important to develop an fMRI method with simultaneous high spatial and temporal resolution. Line-scanning promises to reach this goal at the cost of volume coverage. New methodHere, we release a comprehensive update to human line-scanning fMRI. First, we investigated multi-echo line-scanning with five different protocols varying the number of echoes and readout bandwidth while keeping the TR constant. In these, we compared different echo combination approaches in terms of BOLD activation (sensitivity) and temporal signal-to-noise ratio. Second, we implemented an adaptation of NOise reduction with DIstribution Corrected principal component analysis (NORDIC) thermal noise removal for line-scanning fMRI data. Finally, we tested three image-based navigators for motion correction and investigated different ways of performing fMRI analysis on the timecourses which were influenced by the insertion of the navigators themselves. ResultsThe presented improvements are relatively straightforward to implement; multi-echo readout and NORDIC denoising together, significantly improve data quality in terms of tSNR and t-statistical values, while motion correction makes line-scanning fMRI more robust. Comparison with existing methodsMulti-echo acquisitions and denoising have previously been applied in 3D magnetic resonance imaging. Their combination and application to 1D line-scanning is novel. The current proposed method greatly outperforms the previous line-scanning acquisitions with single-echo acquisition, in terms of tSNR (4.0 for single-echo line-scanning and 36.2 for NORDIC-denoised multi-echo) and t-statistical values (3.8 for single-echo line-scanning and 25.1 for NORDIC-denoised multi-echo line-scanning). ConclusionsLine-scanning fMRI was advanced compared to its previous implementation in order to improve sensitivity and reliability. The improved line-scanning acquisition could be used, in the future, for neuroscientific and clinical applications.

Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression.

Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method among physicians. This paper presents an SZ and ADHD intelligent detection method of resting-state fMRI (rs-fMRI) modality using a new deep learning method. The University of California Los Angeles dataset, which contains the rs-fMRI modalities of SZ and ADHD patients, has been used for experiments. The FMRIB software library toolbox first performed preprocessing on rs-fMRI data. Then, a convolutional Autoencoder model with the proposed number of layers is used to extract features from rs-fMRI data. In the classification step, a new fuzzy method called interval type-2 fuzzy regression (IT2FR) is introduced and then optimized by genetic algorithm, particle swarm optimization, and gray wolf optimization (GWO) techniques. Also, the results of IT2FR methods are compared with multilayer perceptron, k-nearest neighbors, support vector machine, random forest, and decision tree, and adaptive neuro-fuzzy inference system methods. The experiment results show that the IT2FR method with the GWO optimization algorithm has achieved satisfactory results compared to other classifier methods. Finally, the proposed classification technique was able to provide 72.71% accuracy.

Review Paper: Reporting Practices for Task fMRI Studies.

What are the standards for the reporting methods and results of fMRI studies, and how have they evolved over the years? To answer this question we reviewed 160 papers published between 2004 and 2019. Reporting styles for methods and results of fMRI studies can differ greatly between published studies. However, adequate reporting is essential for the comprehension, replication and reuse of the study (for instance in a meta-analysis). To aid authors in reporting the methods and results of their task-based fMRI study the COBIDAS report was published in 2016, which provides researchers with clear guidelines on how to report the design, acquisition, preprocessing, statistical analysis and results (including data sharing) of fMRI studies (Nichols et al. inBest Practices in Data Analysis and Sharing in Neuroimaging using fMRI,2016). In the past reviews have been published that evaluate how fMRI methods are reported based on the 2008 guidelines, but they did not focus on how task based fMRI results are reported. This review updates reporting practices of fMRI methods, and adds an extra focus on how fMRI results are reported. We discuss reporting practices about the design stage, specific participant characteristics, scanner characteristics, data processing methods, data analysis methods and reported results.

The current status and trend of the functional magnetic resonance combined with stimulation in animals.

As a non-radiative, non-invasive imaging technique, functional magnetic resonance imaging (fMRI) has excellent effects on studying the activation of blood oxygen levels and functional connectivity of the brain in human and animal models. Compared with resting-state fMRI, fMRI combined with stimulation could be used to assess the activation of specific brain regions and the connectivity of specific pathways and achieve better signal capture with a clear purpose and more significant results. Various fMRI methods and specific stimulation paradigms have been proposed to investigate brain activation in a specific state, such as electrical, mechanical, visual, olfactory, and direct brain stimulation. In this review, the studies on animal brain activation using fMRI combined with different stimulation methods were retrieved. The instruments, experimental parameters, anesthesia, and animal models in different stimulation conditions were summarized. The findings would provide a reference for studies on estimating specific brain activation using fMRI combined with stimulation.

Investigation of the functional pathogenesis of mild cognitive impairment by localisation-based locus coeruleus resting-state fMRI.

Dementia as one of the most prevalent diseases urges for a better understanding of the central mechanisms responsible for clinical symptoms, and necessitates improvement of actual diagnostic capabilities. The brainstem nucleus locus coeruleus (LC) is a promising target for early diagnosis because of its early structural alterations and its relationship to the functional disturbances in the patients. In this study, we applied our improved method of localisation-based LC resting-state fMRI to investigate the differences in central sensory signal processing when comparing functional connectivity (fc) of a patient group with mild cognitive impairment (MCI, n=28) and an age-matched healthy control group (n=29). MCI and control participants could be differentiated in their Mini-Mental-State-Examination (MMSE) scores (p < .001) and LC intensity ratio (p=.010). In the fMRI, LC fc to anterior cingulate cortex (FDR p < .001) and left anterior insula (FDR p=.012) was elevated, and LC fc to right temporoparietal junction (rTPJ, FDR p=.012) and posterior cingulate cortex (PCC, FDR p=.021) was decreased in the patient group. Importantly, LC to rTPJ connectivity was also positively correlated to MMSE scores in MCI patients (p=.017). Furthermore, we found a hyperactivation of the left-insula salience network in the MCI patients. Our results and our proposed disease model shed new light on the functional pathogenesis of MCI by directing to attentional network disturbances, which could aid new therapeutic strategies and provide a marker for diagnosis and prediction of disease progression.

Systematic Review and Meta-analysis: Task-based fMRI Studies in Youths With Irritability

Childhood irritability, operationalized as disproportionate and frequent temper tantrums and low frustration tolerance relative to peers, is a transdiagnostic symptom across many pediatric disorders. Studies using task-dependent functional magnetic resonance imaging (fMRI) to probe neural dysfunction in irritability have increased. However, an integrated review summarizing the published methods and synthesized fMRI results remains lacking. We conducted a systematic search using irritability terms and task functional neuroimaging in key databases in March 2021, and identified 30 studies for our systematic review. Sample characteristics and fMRI methods were summarized. A subset of 28 studies met the criteria for extracting coordinate-based data for quantitative meta-analysis. Ten activation-likelihood estimations were performed to examine neural convergence across irritability measures and fMRI task domains. Systematic review revealed small sample sizes (median= 58, mean age range= 8-16 years) with heterogeneous sample characteristics, irritability measures, tasks, and analytical procedures. Meta-analyses found no evidence for neural activation convergence of irritability across neurocognitive functions related to emotional reactivity, cognitive control, and reward processing, or within each domain. Sensitivity analyses partialing out variances driven by heterogeneous tasks, irritability measures, stimulus types, and developmental ages all yielded null findings. Results were compared with a review on irritability-related structural anomalies from 11 studies. The lack of neural convergence suggests a need for common, standardized irritability assessments and more homogeneous fMRI tasks. Thoughtfully designed fMRI studies probing commonly defined neurocognitive functions may be more fruitful to elucidate the neural mechanisms of irritability. Open science practices, data mining in large neuroscience databases, and standardized analytical methods promote meaningful collaboration in irritability research.

Whole-Brain Dynamic Resting-State Functional Network Analysis in Benign Epilepsy With Centrotemporal Spikes.

Benign epilepsy with centrotemporal spikes (BECTS), the most common type of epilepsy among children, is considered a network disorder. Both fMRI and EEG source imaging (ESI) studies have indicated that BECTS is associated with static resting-state functional network (SFN) alterations (e.g., decreased global efficiency) in source space. However, we find that the abovementioned alterations are not significant when the SFN calculations are performed in the scalp space using only clinical routine low-density (e.g., 19 channels) EEG recordings (shown in our results). In the context of EEG microstates, it is clear that networks in the scalp space with resting-state EEG recordings dynamically reconfigure in a well-organized way based on different functional states. We are therefore inspired to propose a whole-brain dynamic resting-state functional network (DFN) computation method based on resting-state low-density EEG recordings with four classical microstates in scalp space. Notably, on the one hand, this approach is suitable for clinical conditions, and, on the other hand, the dynamic alternations calculated with a DFN may promote our understanding of how the networks change in BECTS. We analysed the changes in a DFN in six frequency bands (δ, θ, αlow, αhigh, β, and γ) in patients with BECTS compared to those for healthy controls. Superior to traditional SFNs, the proposed DFN can reveal significant differences between individuals with BECTS and healthy controls (e.g., lower global efficiency), thus matching traditional fMRI and ESI methods in the source space. Our method directly performs DFN computations from low-density EEG recordings and avoids complex ESI computations, making it promising for clinical applications, especially in the outpatient diagnosis stage.

The current development of the non-medicine treatment of Epilepsy involved EEG and the Expectation

Since Jacquces Vidal first proposed the concept of the brain-computer interface in 1973, more and more scientific researches have been involved in the study of BCI, leading to the rapid development of BCI technology. Brain-computer interface refers to establishing a direct connection between the human brain and the external machine, which enables the brain to directly interact with the outside world based on the behaviours and movement of muscle tissue regulated by peripheral nerves or the communication of language and characters. BCI can achieve direct contact with external devices without relying on normal brain output pathways, which brings hope to patients with normal thinking but a severe neuromuscular injury that BCI can restore their ability to move or communicate with the environment and improve the quality of life of patients. There are mainly EEG, MEG, ECoG and FMRI methods to record neural signals of brain physiological activities. EEG is the bioelectrical activity of cortical neurons, which can reflect different brain states well and is widely used to apply brain-computer interface technology. At present, BCI technology is developing towards the real-time and practical direction. This paper summarizes the progress of EEG based brain-computer interface and an overview of epilepsy. These results shed light on further exploring the application potential of BCI in repairing major brain diseases.

Visual neuroprosthesis: present and future perspectives.

The purpose of this study is to provide an overview of the replacements used in lost vision in the form of the bionic eye, to show their deficiencies and outline other possibilities for non-invasive stimulation of functional areas of the visual cortex. The review highlights the damage not only to the primary altered cellular structures, but also to all other horizontally and vertically localised structures. Based on the results of a large number of functional magnetic resonance imaging and electrophysiological methods, the authors focus on the pathology of the entire visual pathway in pigmentary retinopathy (PR) and age-related macular degeneration (AMD). This study provides a recent overview of the possible systems used to replace lost vision. These range from stimulation with intraocular implants, through stimulation of the optic nerve and lateral geniculate nucleus to the visual cortex. The second part deals with the design of image processing technology and its transformation into the form of transcranial stimulation of undamaged parts of the brain, which is protected by a patent. This is comprehensive overview of the current possibilities of replacement of lost vision and a proposal for a new non-invasive methods of stimulation of functional neurons of the visual cortex.

A Study of Spontaneous Brain Activity on Resting-State Functional Magnetic Resonance Imaging in Adults with MRI-Negative Temporal Lobe Epilepsy.

PurposePatients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE-N) represent an important subgroup of temporal lobe epilepsy (TLE). Here, we aimed to combine three voxel-based local brain area analysis methods of resting-state functional MRI (rs-fMRI), to examine the TLE-N patients’ resting brain function based on neural synchronization and intensity of local brain areas.MethodsThe study included 47 patients with TLE, including 28 cases of drug-controlled TLE (cTLE-N) and 19 cases of drug-resistant TLE-N (rTLE-N), as well as 30 participants in the healthy control (HC) group. To comprehensively assess the altered brain function associated with TLE-N patients, we analyzed three data-driven rs-fMRI algorithms for amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo).ResultsCompared to the HC group, the distribution of abnormal functional brain areas in cTLE-N patients was dominated by occipital lobe activation, as measured by increased fALFF values in the superior occipital gyrus (SOG) and increased ReHo values in the lingual gyrus (Lin), fusiform gyrus, and middle occipital gyrus. Patients with rTLE-N exhibited a diffuse distribution of abnormal functional brain areas, showing increased fALFF values in the SOG, Lin, superior temporal gyrus, and postcentral gyrus, and decreased fALFF values in the inferior frontal gyrus orbital, parahippocampal gyrus, and superior frontal gyrus orbital. The ReHo values were reduced in the orbital region of the middle frontal gyrus, the precuneus, and the parietal inferior angular gyrus; while ReHo values were elevated values in several frontal, temporal, occipital, and subcortical brain areas.ConclusionPatients with rTLE-N have local brain activity changes in the prefrontal limbic system and default model network dysfunction, while cTLE-N patients have local brain activity changes in the visual functional areas. Different epilepsy networks exist between cTLE-N and rTLE-N.

Functional Localizers for Motor Areas of the Brain Using fMRI.

Neuroimaging researchers increasingly take advantage of the known functional properties of brain regions to localize motor regions in the brain and investigate changes in their activity under various conditions. Using this noninvasive functional MRI (fMRI) method makes it possible to identify and localize brain activation. There are many localizers that can be used to identify brain areas, namely, motor areas such as functional localizer, anatomical localizer, or Atlas mask. Eighteen right-handed participants were recruited for this research to test the reliability of five localizers for primary motor cortex (M1), supplementary motor area (SMA), premotor cortex (PMC), motor cerebellum, and motor thalamus. Motor execution task, namely, hand clenching was used to activate M1, SMA, and motor cerebellum. A combined action observation and motor imagery (AOMI) task was used to functionally activate PMC. Finally, a mask based on Talairach coordinates Atlas was created and used to identify the motor thalamus. Our results show that all localizers were successfully activated in the desired regions of interest. Motor execution successfully activated M1, SMA, and motor cerebellum. A novel localizer based on AOMI was successfully activated in PMC, and the motor thalamus mask obtained from the thalamus mask was successfully implemented on each participant. In conclusion, all five localizers tested in this research were reliable and can be used for rt-fMRI neurofeedback research to define the regions of interest.

School-age structural and functional MRI and lung function in children following lung resection for congenital lung malformation in infancy

BackgroundThe management of asymptomatic congenital lung malformations is debated. Particularly, there is a lack of information regarding long-term growth and development of the remaining lung in children following lung resection for congenital lung malformations. In addition to conventional pulmonary function tests, we used novel functional magnetic resonance imaging (MRI) methods to measure perfusion and ventilation.ObjectiveTo assess functionality of the remaining lung expanded into the thoracic cavity after resection of congenital lung malformations.Materials and methodsA prospective, cross-sectional pilot study in five children who had surgery for congenital lung malformations during infancy. Participants had structural and functional MRI as well as spirometry, body plethysmography and multiple breath washout at school age.ResultsStructural MRI showed an expansion of the remaining lung in all cases. Fractional ventilation and relative perfusion of the expanded lung were locally decreased in functional MRI. In all other parts of the lungs, fractional ventilation and relative perfusion were normal in all children. There was an association between overall impairment of perfusion and elevated lung clearance index. The results of spirometry and body plethysmography varied between patients, including normal lung function, restriction and obstruction.ConclusionFractional ventilation and relative perfusion maps from functional MRI specifically locate impairment of the remaining lung after lung resection. These changes are not captured by conventional measures such as structural MRI and standard pulmonary function tests. Therefore, following lung resection for congenital lung malformation, children should be investigated more systematically with functional lung MRI.

Future of kidney imaging: Functional magnetic resonance imaging and kidney disease progression.

Chronic kidney disease (CKD) which is a common cause of death has an increasing trend, but there is no established approach for predicting CKD progression yet. Functional magnetic resonance imaging (fMRI) studies such as blood oxygenation level-dependent MRI (BOLD-MRI), diffusion-weighted MRI (DWI-MRI), diffusion-tensor MRI (DTI-MRI) and arterial spin labelling MRI (ASL-MRI) are rising methods for the assessment of kidney functions in native and transplanted kidneys as well as the estimation of CKD progression. Systematic literature review was performed through the Embase (Elsevier), Cochrane Central Register of Controlled Trials (Wiley), PubMed/Medline and Web of Science databases, and studies investigating the role of fMRI methods assessing kidney functions in native and transplanted kidneys, as well as the value of fMRI methods to predict CKD progression, were included. Working mechanisms, advantages and limitations of the fMRI modalities were reviewed, and three studies investigating the role of fMRI studies in kidney functions were analysed. BOLD-MRI signal was found to be inversely correlated with annual eGFR change, and DWI/ADC (apparent diffusion coefficient map) values were shown to be correlated with annual eGFR decline. fMRI methods which are currently used for other systems can be utilized to provide more detailed information about kidney functions, and doctors should be ready to interpret kidney MRIs.