Whole-Body Low-Dose CT in Multiple Myeloma: Diagnostic Value of Appendicular Medullary Patterns of Attenuation.

OBJECTIVE. The purpose of this article is to analyze whole-body low-dose CT-detected appendicular medullary patterns of attenuation in patients with newly diagnosed multiple myeloma and to determine the diagnostic performance of whole-body low-dose CT in detecting diffuse marrow infiltration. MATERIALS AND METHODS. A total of 76 patients with myeloma who underwent whole-body low-dose CT and spinal MRI at initial assessment were retrospectively analyzed. The medullary cavities of femurs and humeri were evaluated qualitatively and quantitatively on CT. Medullary attenuation and SD-to-mean attenuation ratio were recorded for each long bone. The pattern of marrow involvement on spinal MRI was used as reference. The chi-square test was used to evaluate the relationship between the CT-based appendicular medullary cavity pattern and the MRI pattern, and ROC analysis was performed to assess the diagnostic accuracy of CT attenuation measurements for the differentiation between diffuse and mixed CT-based appendicular medullary cavity patterns. RESULTS. Medullary attenuation differed significantly among mixed, nodular, and diffuse CT-based appendicular medullary cavity patterns in the femurs (mean, 34.23 HU and range, 15-61 HU; mean, 66.26 HU and range, 26-104 HU; mean, 92.80 HU and range, 53-127 HU, respectively) and humeri (mean, 22.18 HU and range, 9-41; mean, 61.18 HU and range, 23-93 HU; mean, 77.50 and range, 25-105 HU, respectively). To discriminate between diffuse and mixed CT-based appendicular medullary cavity patterns, optimal cutoff attenuation values were 63 HU (sensitivity, 97.7%; specificity, 100.0%) for the femurs, and 52 HU (sensitivity, 97.4%; specificity, 100.0%) for the humeri. A total of 24 of 30 (80.0%) patients with a diffuse MRI pattern showed a diffuse CT-based appendicular medullary cavity pattern on whole-body low-dose CT, and all patients with a diffuse CT-based appendicular medullary cavity pattern also showed a diffuse pattern on MRI. CONCLUSION. According to analysis of peripheral medullary patterns of attenuation, whole-body low-dose CT can identify patients with multiple myeloma with diffuse marrow involvement.

Hypomyelination with atrophy of the basal ganglia and cerebellum: further delineation of the phenotype and genotype-phenotype correlation.

Hypomyelination with atrophy of the basal ganglia and cerebellum is a rare leukoencephalopathy that was identified using magnetic resonance imaging in 2002. In 2013, whole exome sequencing of 11 patients with the disease revealed that they all had the same de novo mutation in TUBB4A, which encodes tubulin ß-4A. We investigated the mutation spectrum in a cohort of 42 patients and the relationship between genotype and phenotype. Patients were selected on the basis of clinical and magnetic resonance imaging abnormalities that are indicative of hypomyelination with atrophy of the basal ganglia and cerebellum. Genetic testing and a clinical inventory were performed, and sequential magnetic resonance images were evaluated using a standard protocol. The heterozygous TUBB4A mutation observed in the first 11 patients was the most common (25 patients). Additionally, 13 other heterozygous mutations were identified, located in different structural domains of tubulin ß-4A. We confirmed that the mutations were de novo in all but three patients. In two of these three cases we lacked parental DNA and in one the mutation was also found in the mother, most likely due to mosaicism. Patients showed a phenotypic continuum ranging from neonatal to childhood disease onset, normal to delayed early development and slow to more rapid neurological deterioration. Neurological symptomatology consisted of extrapyramidal movement abnormalities, spasticity, ataxia, cognitive deficit and sometimes epilepsy. Three patients died and the oldest living patient was 29 years of age. The patients' magnetic resonance images showed an absent or disappearing putamen, variable cerebellar atrophy and highly variable cerebral atrophy. Apart from hypomyelination, myelin loss was evident in several cases. Three severely affected patients had similar, somewhat atypical magnetic resonance image abnormalities. The study results were strongly suggestive of a genotype-phenotype correlation. The 25 patients with the common c.745G>A mutation generally had a less rapidly progressive disease course than the 17 cases with other TUBB4A mutations. Overall, this work demonstrates that the distinctive magnetic resonance imaging pattern for hypomyelination with atrophy of the basal ganglia and cerebellum defines a homogeneous clinical phenotype of variable severity. Patients almost invariably have prominent extrapyramidal movement abnormalities, which are rarely seen in patients with hypomyelination of different origin. A dominant TUBB4A mutation is also associated with dystonia type 4, in which magnetic resonance images of the brain seem normal. It is highly likely that there is a disease continuum associated with TUBB4A mutations, of which hypomyelination with atrophy of the basal ganglia and cerebellum and dystonia type 4 are the extremes. This would indicate that extrapyramidal movement abnormalities constitute the core feature of the disease spectrum related to dominant TUBB4A mutations and that all other features are variable.

MRI pattern characterization of cerebral cardioembolic lesions following atrial fibrillation ablation.

Background: Recognizing etiology is essential for treatment and secondary prevention of cerebral ischemic events. A magnetic resonance imaging (MRI) pattern suggestive of an embolic etiology has been described but, to date, there are no uniformly accepted criteria. Aim: The purpose of the study is to describe MRI features of ischemic cerebral lesions occurring after transcatheter ablation of atrial fibrillation (AF). Methods: A systematic review and meta-analysis of studies performing brain imaging investigations before and after AF transcatheter ablation was performed. The incidence of cerebral ischemic lesions after AF transcatheter ablation was the primary endpoint. The co-primary endpoints were the prevalence of the different neuroimaging features regarding the embolic cerebral ischemic lesions. Results: A total of 25 studies, encompassing 3,304 patients, were included in the final analysis. The incidence of ischemic cerebral lesions following AF transcatheter ablation was 17.2% [95% confidence interval (CI) 12.2%-23.8%], of which a minimal fraction was symptomatic [0.60% (95% CI 0.09%-3.9%)]. Only 1.6% of the lesions (95% CI 0.9%-3.0%) had a diameter >10 mm, and in 20.5% of the cases the lesions were multiple (95% CI 17.1%-24.4%). Brain lesions were equally distributed across the two hemispheres and the different lobes; cortical location was more frequent [64.0% (95% CI 42.9%-80.8%)] while the middle cerebral artery territory was the most involved 37.0% (95% CI 27.3-48.0). Conclusions: The prevailing MRI pattern comprises a predominance of small (<10 mm) cortical lesions, more prevalent in the territory of the middle cerebral artery.

Approaches to diagnosis for individuals with a suspected inherited white matter disorder.

Leukodystrophies are heritable disorders with white matter abnormalities observed on central nervous system magnetic resonance imaging. Pediatric leukodystrophies have long been known for their classically high, "unsolved" rate. Indeed, these disorders provide a diagnostic dilemma for many clinicians as over 100 genetic disorders alone may present with white matter abnormalities, with this figure not taking into account the substantial number of infectious agents, toxicities, and acquired disorders that may affect the white matter of the brain. Achieving a diagnosis may be the single most important step in the clinical course of a leukodystrophy-affected individual, with important implications for care and quality of life. For certain disorders, prompt recognition can direct therapeutic intervention with significant implications and requires urgent recognition. In this review, we cover newborn screening efforts, standard-of-care testing methodologies, and next generation sequencing approaches that continue to change the landscape of leukodystrophy diagnosis. Early studies have shown that next generation sequencing approaches, particularly exome and now genome sequencing have proven to be powerful in helping resolve many cases that were refractory to a single gene or linkage analysis approach. In addition, other methods are required for cases that remain persistently unsolved after next generation sequencing methods have been used. In the past more than half of affected individuals never achieved an etiologic diagnosis, and when they did, the reported times to diagnosis were >5 years although molecular testing has allowed this to be reduced to closer to 16 months. For affected families, next generation sequencing technologies have finally provided a way to fill gaps in diagnosis.

MRI-based deep learning for differentiating between bipolar and major depressive disorders.

Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest changes in brain structure that can be detected using structural magnetic resonance imaging (MRI). Although structural MRI is a promising diagnostic tool, prevailing diagnostic criteria for BD and MDD are predominantly subjective, sometimes leading to misdiagnosis. This challenge is compounded by a limited understanding of the underlying causes of these disorders. In response, we present SE-ResNet, a Residual Network (ResNet)-based framework designed to discriminate between BD, MDD, and healthy controls (HC) using structural MRI data. Our approach extends the traditional Squeeze-and-Excitation (SE) layer by incorporating a dedicated branch for spatial attention map generation, equipped with soft-pooling, a 7 × 7 convolution, and a sigmoid function, intended to detect complex spatial patterns. The fusion of channel and spatial attention maps through element-wise addition aims to enhance the model's ability to discriminate features. Unlike conventional methods that use max-pooling for downsampling, our methodology employs soft-pooling, which aims to preserve a richer representation of input features and reduce data loss. When evaluated on a proprietary dataset comprising 303 subjects, the SE-ResNet achieved an accuracy of 85.8 %, a recall of 85.7 %, a precision of 85.9 %, and an F1 score of 85.8 %. These performance metrics suggest that the SE-ResNet framework has potential as a tool for detecting psychiatric disorders using structural MRI data.

Magnetic resonance imaging pattern variability in dysferlinopathy.

The widespread use of magnetic resonance imaging (MRI) in the diagnosis of myopathies has made it possible to clarify the typical MRI pattern of dysferlinopathy. However, sufficient attention has not been given to the variability of MRI patterns in dysferlinopathy. MATERIALS AND METHODS: Twenty-five patients with the clinical manifestations of dysferlinopathy were examined. For all patients, creatine phosphokinase levels were measured and molecular genetics were examined. In two patients, immunohistochemical examinations of muscle biopsies were performed. MRI scanning was included T2 multi-slice multi-echo, T1 weighted, T2 weighted and Short Tau Inversion Recovery T2 weighted sequences. Quantitative and semi-quantitative evaluations of fatty replacement and swelling of the muscles were undertaken. RESULTS: Variability in the MRI patterns was lowest in the pelvis and leg muscles and highest in the thigh muscles. Three main types of MRI patterns were distinguished: posterior-dominant (80%), anterior-dominant (16%), and diffuse (4%). Among patients with the anterior-dominant pattern, the collagen-like variant (4%), proximal variant (4%) and pseudo-myositis (8%) were separately distinguished. CONCLUSIONS: Awareness of atypical MRI patterns in dysferlinopathy is important for increasing the efficiency of routine diagnostics and optimizing the search for causative gene mutations.

Neuroimaging Patterns and Function in Cerebral Palsy-Application of an MRI Classification.

Background: Cerebral palsy (CP) is a disorder of movement and posture and every child with CP has a unique composition of neurological symptoms, motor severity, and associated impairments, constituting the functional profile. Although not part of the CP definition, magnetic resonance imaging (MRI) sheds light on the localization, nature, and severity of brain compromise. The MRI classification system (MRICS), developed by the Surveillance of Cerebral Palsy in Europe (SCPE), describes typical MRI patterns associated with specific timing of vulnerability in different areas of the brain. The classification has proven to be reliable and easy to use. Aims: The aim of this study is to apply the MRICS on a large dataset and describe the functional profile associated with the different MRI patterns of the MRICS. Materials and Methods: Data on children with CP born in 1999-2009 with a post-neonatal MRI from 20 European registers in the JRC-SCPE Central Registry was included. The CP classification and the MRICS was applied, and The Gross Motor Function Classification (GMFCS) and the Bimanual Fine Motor Function (BFMF) classification were used. The following associated impairments were documented: intellectual impairment, active epilepsy, visual impairment, and hearing impairment. An impairment index was used to characterize severity of impairment load. Results: The study included 3,818 children with post-neonatal MRI. Distribution of CP type, motor, and associated impairments differed by neuroimaging patterns. Functional profiles associated with neuroimaging patterns were described, and the impairment index showed that bilateral findings were associated with a more severe outcome both regarding motor impairment and associated impairments than unilateral compromise. The results from this study, particularly the differences in functional severity regarding uni- and bilateral brain compromise, may support counseling and service planning of support of children with CP.

Natural history of Krabbe disease - a nationwide study in Germany using clinical and MRI data.

BACKGROUND: Krabbe disease or globoid cell leukodystrophy is a severe neurodegenerative disorder caused by a defect in the GALC gene leading to a deficiency of the enzyme ß-galactocerebrosidase. The aim of this work was to describe the natural disease course covering the whole spectrum of the disease. METHODS: Natural history data were collected with a standardized questionnaire, supplemented by medical record data. We defined different forms of the disease according to Abdelhalim et al. (2014). Developmental and disease trajectories were described based on the acquisition and loss of milestones as well as the time of first clearly identifiable symptoms and needs such as spasticity, seizures and tube feeding. MRI was assessed using the scoring system by Loes et al. (1999) and in addition a pattern recognition approach, based on Abdelhalim et al. (2014). RESULTS: Thirty-eight patients were identified, from 27 of these patients 40 MRIs were available; 30 (79%) had an infantile onset, showing first symptoms in their first year of life, almost all (27 out of 30) starting in the first six months. A later onset after the first year of life was observed in 8 patients (21%, range 18 months to 60 years). Irritability, abnormalities in movement pattern as well as general developmental regression were the first symptoms in the infantile group; disease course was severe with rapid progression, e.g. loss of visual fixation, need for tube feeding and then an early death. Gait disorders were the first symptoms in all patients of the later onset groups; progression was variable. The different forms of the disease were characterized by different MRI patterns (infantile: diffuse white matter involvement and cerebellar structures specifically affected, later onset: parieto-occipital white matter and splenium affected, adult: motor tracts specifically affected). CONCLUSION: This is the first description of the natural history of Krabbe disease in a larger European cohort using developmental, clinical and MRI data. We would like to highlight the very different clinical and MRI characteristics of the later onset forms. These data are important for counselling affected patients and families and may serve as a basis for future treatment trials.

Automated cortical thickness and skewness feature selection in bipolar disorder using a semi-supervised learning method.

BACKGROUND: Bipolar disorder (BD) broadly affects brain structure, in particular areas involved in emotion processing and cognition. In the last years, the psychiatric field's interest in machine learning approaches has been steadily growing, thanks to the potentiality of automatically discriminating patients from healthy controls. METHODS: In this work, we employed cortical thickness of 58 regions of interest obtained from magnetic resonance imaging scans of 41 BD patients and 34 healthy controls, to automatically identify the regions which are mostly involved with the disease. We used a semi-supervised method, addressing the criticisms on supervised methods, related to the fact that the diagnosis is not unaffected by uncertainty. RESULTS: Our results confirm findings in previous studies, with a classification accuracy of about 75% when mean thickness and skewness of up to five regions are considered. We obtained that the parietal lobe and some areas in the temporal sulcus were the regions which were the most involved with BD. LIMITATIONS: The major limitation of our work is the limited size or our dataset, but in line with other recent machine learning works in the field. Moreover, we considered chronic patients, whose brain characteristics may thus be affected. CONCLUSIONS: The automatic selection of the brain regions most involved in BD may be of great importance when dealing with the pathogenesis of the disorder. Our method selected regions which are known to be involved with BD, indicating that damage to the identified areas can be considered as a marker of disease.

The Diagnostic Value of MRI Pattern Recognition in Distal Myopathies.

Objective: Distal myopathies are a diagnostically challenging group of diseases. We wanted to understand the value of MRI in the current clinical setting and explore the potential for optimizing its clinical application. Methods: We retrospectively audited the diagnostic workup in a distal myopathy patient cohort, reassessing the diagnosis, whilst documenting the usage of MRI. We established a literature based distal myopathies MRI pattern template and assessed its diagnostic utility in terms of sensitivity, specificity, and potential impact on the diagnostic workup. Results: Fifty-five patients were included; in 38 with a comprehensive set of data the diagnostic work-up was audited. The median time from symptoms onset to diagnosis was 12.1 years. The initial genetic diagnostic rate was 39%; 18% were misdiagnosed as neuropathies and 13% as inclusion body myositis (IBM). Based on 21 publications we established a MRI pattern template. Its overall sensitivity (50%) and specificity (32%) were low. However in some diseases (e.g., MYOT-related myopathy, TTN-HMERF) MRI correctly identified the causative gene. The number of genes suggested by MRI pattern analysis was smaller compared to clinical work up (median 1 vs. 9, p < 0.0001) but fewer genes were correctly predicted (5/10 vs. 7/10). MRI analysis ruled out IBM in all cases. Conclusion: In the diagnostic work-up of distal myopathies, MRI is useful in assisting genetic testing and avoiding misdiagnosis (IBM). The overall low sensitivity and specificity limits its generalized use when traditional single gene test methods are applied. However, in the context of next generation sequencing MRI may represent a valuable tool for interpreting complex genetic results.

RMND1-Related Leukoencephalopathy With Temporal Lobe Cysts and Hearing Loss-Another Mendelian Mimicker of Congenital Cytomegalovirus Infection.

BACKGROUND: Leukoencephalopathy with temporal lobe cysts may be associated with monogenetic conditions such as Aicardi-Goutières syndrome or RNASET2 mutations and with congenital infections such as cytomegalovirus. In view of the fact that congenital cytomegalovirus is difficult to confirm outside the neonatal period, excluding a Mendelian disorder is extremely relevant, changing family planning and medical management in affected families. We performed diagnostic testing in individuals with leukoencephalopathy with temporal lobe cysts without a definitive diagnosis of congenital cytomegalovirus infection. METHODS: We reviewed a large-scale biorepository of patients with unsolved leukodystrophies and identified two individuals with required for meiotic nuclear division 1 (RMND1) mutations and similar magnetic resonance imaging (MRI) features, including temporal lobe cysts. Ten additional subjects with confirmed RMND1 mutations were identified as part of a separate disease specific cohort. Brain MRIs from all 12 individuals were reviewed for common neuroradiological features. RESULTS: MRI features in RMND1 mutations included temporal lobe swelling, with rarefaction and cystic evolution, enlarged tips of the temporal lobes, and multifocal subcortical white matter changes with confluent periatrial T2 signal hyperintensity. A combination of these features was present in ten of the 12 individuals reviewed. CONCLUSIONS: Despite the small number of reported individuals with RMND1 mutations, a clinically recognizable phenotype of leukoencephalopathy with temporal lobe swelling, rarefaction, and cystic changes has emerged in a subset of individuals. Careful clinical phenotyping, including for lactic acidosis, deafness, and severe muscle involvement seen in RMND1 mutation positive individuals, and MRI pattern recognition will be important in differentiating these patients from children with congenital infections like cytomegalovirus.

Muscle imaging in patients with tubular aggregate myopathy caused by mutations in STIM1.

Tubular aggregate myopathy is a genetically heterogeneous disease characterized by tubular aggregates as the hallmark on muscle biopsy. Mutations in STIM1 have recently been identified as one genetic cause in a number of tubular aggregate myopathy cases. To characterize the pattern of muscle involvement in this disease, upper and lower girdles and lower limbs were imaged in five patients with mutations in STIM1, and the scans were compared with two patients with tubular aggregate myopathy not caused by mutations in STIM1. A common pattern of involvement was found in STIM1-mutated patients, although with variable extent and severity of lesions. In the upper girdle, the subscapularis muscle was invariably affected. In the lower limbs, all the patients showed a consistent involvement of the flexor hallucis longus, which is very rarely affected in other muscle diseases, and a diffuse involvement of thigh and posterior leg with sparing of gracilis, tibialis anterior and, to a lesser extent, short head of biceps femoris. Mutations in STIM1 are associated with a homogeneous involvement on imaging despite variable clinical features. Muscle imaging can be useful in identifying STIM1-mutated patients especially among other forms of tubular aggregate myopathy.

Correlation between MRI appearances and serum alkaline phosphatase levels in Osteogenic sarcoma.

INTRODUCTION: Magnetic resonance imaging is a pictorial depiction of the patho-anatomy of a bony lesion. As different parts of the tumor in Osteogenic sarcoma concurrently undergo various biological processes i.e. osteoblastic new bone formation, cell death, necrosis, bony destruction and revascularization etc., we hypothesized that the image seen in MRI could be used to assess the tumor behavior at that time. This study was done as a preliminary study with the aim to find whether the MRI pictures can have identifiable patterns and if present whether they can be linked to biological behavior. We could identify 2 distinct patterns in T2 weighted images which correlated well with serum alkaline phosphatase a serum marker and the duration of symptoms and so we are reporting our observations. MATERIAL AND METHOD: T2 weighted MRI pictures of 15 cases of Osteogenic sarcoma were studied for identifiable patterns in matrix. These patterns if found were to be linked to biological behavior in the form of serum alkaline phosphatase levels and duration of symptoms. RESULTS: We could identify 2 unique patterns named by us as Group 1 Heterogeneous type (4 cases) which had a raised serum alkaline phosphatase level and had a history at presentation of less than 3 months duration. In Group 2 homogenous type (5 cases) the serum alkaline phosphatase levels were low and the cases presented after 6 months. As we could not identify any logical pattern in rest of the cases we labeled them as miscellaneous. DISCUSSION: MRI patterns can be used as markers of disease activity as there are 2 clear poles correlating well with serum alkaline phosphatase levels (high or low). Intermediate patterns may be the natural biological behavior and waxing and waning of the tumor disease activity.