A diagnostic decision tree for adult cerebellar ataxia based on pontine magnetic resonance imaging

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

MRl and MRS hints for the differentiation of cerebellar multiple system atrophy from spinocerebellar ataxia type II

Background and objectives

The differentiation of spinocerebellar ataxia type II (SCA 2) from idiopathic multiple systemic atrophy of the cerebellar type (MSA-C) is often difficult in patients with cerebellar ataxia when molecular testing is not available. Besides genetic testing, magnetic resonance imagining (MRI) and magnetic resonance spectroscopy (MRS) prove to be beneficial. Nevertheless, the characteristics observed through radiology change as the disease advances. Different radiological criteria may be needed across different stages of the disease. This study aimed to assess the radiological characteristics of MSA-C or SCA 2 patients across various stages of the disease and to identify potential distinguishing factors.

Methods

Between January 2000 and January 2020, a total of 390 patients, diagnosed with probable MSA-C according to the second consensus on MSA (317 cases) or with molecularly confirmed SCA 2 (73 cases), who had undergone at least one brain MRI and MRS targeting the cerebellar hemispheres, were enrolled in the study. The clinical parameters and neuroimaging features between these two diseases were compared and analyzed.

Results

A greater occurrence of a pontine hot cross bun sign (HCBS), higher scores on the scale for the assessment and rating of ataxia, and reduced levels of cerebellar N-acetyl aspartate (NAA)/creatine (Cr), and cerebellar choline (Cho)/Cr were found in MSA-C patients as compared with SCA 2 patients at similar disease durations. For the patients with an HCBS, a cerebellar Cho/Cr level of <0.53 was indicative of the potential presence of MSA-C, with significant level of specificity (85.96%).

Discussion

Discerning SCA2 from MSA-C using MRI and MRS appears to be plausible at various disease stages.

Pure cerebellar ataxia due to bi-allelic PRDX3 variants including recurring p.Asp202Asn

Bi-allelic variants in peroxiredoxin 3 (PRDX3) have only recently been associated with autosomal recessive spinocerebellar ataxia characterized by early onset slowly progressive cerebellar ataxia, variably associated with hyperkinetic and hypokinetic features, accompanied by cerebellar atrophy and occasional olivary and brainstem involvement. Herein, we describe a further simplex case carrying a reported PRDX3 variant as well as two additional cases with novel variants. We report the first Brazilian patient with SCAR32, replicating the pathogenic status of a known variant. All presented cases from the Brazilian and Indian populations expand the phenotypic spectrum of the disease by displaying prominent neuroradiological findings. SCAR32, although rare, should be included in the differential diagnosis of sporadic or recessive childhood and adolescent-onset pure and complex cerebellar ataxia.

Analysis and hierarchical clustering of infratentorial morphological MRI identifies SCAs phenogroups

BACKGROUND

Clinical decision-making in spinocerebellar ataxia spectrum diseases (SCAs) has mainly been based on genetic tests, not considering the SCAs' imaging and clinical heterogenicity.

OBJECTIVE

To identify SCAs phenogroups by analysis and hierarchical clustering of infratentorial morphological MRI for unveiling pathophysiological differences among common SCA subtypes.

METHODS

We prospectively enrolled 119 (62 women; mean age 37 years) genetically diagnosed SCAs (SCA1 n = 21, SCA2 n = 10, symptomatic SCA3 n = 59, presymptomatic SCA3 n = 22, SCA6 n = 7) and 35 healthy controls (HCs). All patients underwent MRI and detailed neurological and neuropsychology examinations. The width of each cerebellar peduncle (CP) and anteroposterior diameter of the spinal cord and pontine were measured. Twenty-five SCAs patients (15 women; mean age 35 years) were followed for at least a year (17 (15, 24) months), whose MRI and the Scale for the Assessment and Rating of Ataxia (SARA) were collected.

RESULTS

Infratentorial morphological MRI measurements could significantly discriminate SCAs from HCs, even among SCA subtypes. Two mutually exclusive and clinically distinct phenogroups were identified. Despite similar (CAG)n, phenogroup 1 (n = 66, 55.5%) presented more atrophied infratentorial brain structures and more severe clinical symptoms with older age and earlier age of onset when compared with phenogroup 2. More importantly, all SCA2, most of SCA1 (76%), and symptomatic SCA3 (68%) were classified into phenogroup 1, whereas all SCA6 and all presymptomatic SCA3 were in phenogroup 2. The right middle CP had the highest diagnostic value in predicting phenogroup 2 (AUC = 0.99; P < 0.01) with high specificity (95%). Consistent with the significantly increased SARA (7.5 vs 10, P = 0.021), the bilateral inferior CP, spinal cord, and pontine tegmentum were more atrophy during the follow-up (P < 0.05).

CONCLUSION

SCAs were with significant infratentorial brain atrophy than HCs. We identified two different SCAs phenogroups associated with substantial differences in infratentorial brain atrophy, clinical presentation, and may reflect the underlying molecular profiles to some extent, paving the way for a more personalized diagnostic and treatment approach.

Diagnosis of Epstein-Barr and cytomegalovirus infections using decision trees: an effective way to avoid antibiotic overuse in paediatric tonsillopharyngitis

BACKGROUND

The incidence of tonsillopharyngitis is especially prevalent in children. Despite the fact that viruses cause the majority of infections, antibiotics are frequently used as a treatment, contrary to international guidelines. This is not only an inappropriate method of treatment for viral infections, but it also significantly contributes to the emergence of antibiotic-resistant strains. In this study, EBV and CMV-related tonsillopharyngitis were distinguished from other pathogens by using machine learning techniques to construct a classification tree based on clinical characteristics.

MATERIALS AND METHODS

In 2016 and 2017, we assessed information regarding 242 children with tonsillopharyngitis. Patients were categorized according to whether acute cytomegalovirus or Epstein-Barr virus infections were confirmed (n = 91) or not (n = 151). Based on symptoms and blood test parameters, we constructed decision trees to discriminate the two groups. The classification efficiency of the model was characterized by its sensitivity, specificity, positive predictive value, and negative predictive value. Fisher's exact and Welch's tests were used to perform univariable statistical analyses.

RESULTS

The best decision tree distinguished EBV/CMV infection from non-EBV/CMV group with 83.33% positive predictive value, 88.90% sensitivity and 90.30% specificity. GPT (U/l) was found to be the most discriminatory variable (p < 0.0001). Using the model, unnecessary antibiotic treatment could be reduced by 66.66% (p = 0.0002).

DISCUSSION

Our classification model can be used as a diagnostic decision support tool to distinguish EBC/CMV infection from non EBV/CMV tonsillopharyngitis, thereby significantly reducing the overuse of antibiotics. It is hoped that the model may become a tool worth considering in routine clinical practice and may be developed to differentiate between viral and bacterial infections.

The "Hot Cross Bun Sign" in Spinocerebellar Ataxia Types 2 and 7-Case Reports and Review of Literature

Background

The "hot cross bun" sign is a cruciform hyperintensity is seen on T2 weighted imaging within the pons. The sign is considered to be pathognomic for Multiple system atrophy type C. The clinical and radiological features of Multiple system atrophy type C overlap with the autosomal dominant inherited ataxias. We present a case series of 3 African patients with genetically proven Spinocerebellar Ataxia presenting with the Hot cross bun sign and a scoping review of similar studies.

Cases

We described the phenotypic and radiological presentation of genetically confirmed SCA-2 in two, and SCA-7 in one patient, with the "hot cross bun" sign.

Literature Review

We performed a scoping review on the Hot Cross Bun Sign.A total of 66 articles were retrieved. We describe the diverse aetiologies of the sign and associated phenotypic and radiological features. We review the Spinocerebellar Ataxias described with a Hot cross bun sign and make comparisons to Multiple System Atrophy Type C [Ref. 1,2].

Conclusions

To our knowledge this is the first description of an African cohort presenting with the Hot Cross Bun Sign. We expand the differential diagnosis of the Hot Cross Bun Sign.

Neuropathology of SCA34 showing widespread oligodendroglial pathology with vacuolar white matter degeneration: a case study

Spinocerebellar ataxia type 34 (SCA34) is an autosomal dominant inherited ataxia due to mutations in ELOVL4, which encodes one of the very long-chain fatty acid elongases. SCA38, another spinocerebellar ataxia, is caused by mutations in ELOVL5, a gene encoding another elongase. However, there have been no previous studies describing the neuropathology of either SCA34 or 38. This report describes the neuropathological findings of an 83-year-old man with SCA34 carrying a pathological ELOVL4 mutation (NM_022726, c.736T>G, p.W246G). Macroscopic findings include atrophies in the pontine base, cerebellum, and cerebral cortices. Microscopically, marked neuronal and pontocerebellar fiber loss was observed in the pontine base. In addition, in the pontine base, accumulation of CD68-positive macrophages laden with periodic acid-Schiff (PAS)-positive material was observed. Many vacuolar lesions were found in the white matter of the cerebral hemispheres and, to a lesser extent, in the brainstem and spinal cord white matter. Immunohistological examination and ultrastructural observations with an electron microscope suggest that these vacuolar lesions are remnants of degenerated oligodendrocytes. Electron microscopy also revealed myelin sheath destruction. Unexpectedly, aggregation of the four-repeat tau was observed in a spatial pattern reminiscent of progressive supranuclear palsy. The tau lesions included glial fibrillary tangles resembling tuft-shaped astrocytes and neurofibrillary tangles and pretangles. This is the first report to illustrate that a heterozygous missense mutation in ELOVL4 leads to neuronal loss accompanied by macrophages laden with PAS-positive material in the pontine base and oligodendroglial degeneration leading to widespread vacuoles in the white matter in SCA34.

Vertical pons hyperintensity and hot cross bun sign in cerebellar-type multiple system atrophy and spinocerebellar ataxia type 3

Background

The “hot cross bun” (HCB) sign, a cruciform hyperintensity in the pons on magnetic resonance imaging (MRI), has gradually been identified as a typical finding in multiple system atrophy, cerebellar-type (MSA-C). Few reports have evaluated the sensitivity of an HCB, including a cruciform hyperintensity and vertical line in the pons, which precedes a cruciform hyperintensity, in the early stages of MSA-C. Moreover, the difference in frequency and timing of appearance of an HCB between MSA-C and spinocerebellar ataxia type 3 (SCA3) has not been fully investigated.

Methods

This study investigated the time at which an HCB and orthostatic hypotension (OH) appeared in 41 patients with MSA-C, based on brain MRI and head-up tilt test. The MRI findings were compared with those of 26 patients with SCA3. The pontine signal findings on T2-weighted MRI were graded as 0 (no change), 1 (a vertical T2 high-intensity line), or 2 (a cruciform T2 high-intensity line), with grades 1 or 2 considered as an HCB. OH 30/15 was defined as a decrease in systolic blood pressure of > 30 mmHg or diastolic blood pressure of > 15 mmHg.

Results

Among the 24 patients with MSA-C within 2 years from the onset of motor symptoms, an HCB was detected in 91.7%, whereas OH 30/15 was present in 60.0%. Among the 36 patients with MSA-C within 3 years from the onset of motor symptoms, a grade 2 HCB was detected in 66.7% of those with MSA-C but in none of those with SCA-3.

Conclusions

HCB is a highly sensitive finding for MSA-C, even in the early stages of the disease. A grade 2 HCB in the early stage is an extremely specific finding for differentiating MSA-C from SCA-3.

A decision tree to improve identification of pathogenic mutations in clinical practice

BACKGROUND

A variant of unknown significance (VUS) is a variant form of a gene that has been identified through genetic testing, but whose significance to the organism function is not known. An actual challenge in precision medicine is to precisely identify which detected mutations from a sequencing process have a suitable role in the treatment or diagnosis of a disease. The average accuracy of pathogenicity predictors is 85%. However, there is a significant discordance about the identification of mutational impact and pathogenicity among them. Therefore, manual verification is necessary for confirming the real effect of a mutation in its casuistic.

METHODS

In this work, we use variables categorization and selection for building a decision tree model, and later we measure and compare its accuracy with four known mutation predictors and seventeen supervised machine-learning (ML) algorithms.

RESULTS

The results showed that the proposed tree reached the highest precision among all tested variables: 91% for True Neutrals, 8% for False Neutrals, 9% for False Pathogenic, and 92% for True Pathogenic.

CONCLUSIONS

The decision tree exceptionally demonstrated high classification precision with cancer data, producing consistently relevant forecasts for the sample tests with an accuracy close to the best ones achieved from supervised ML algorithms. Besides, the decision tree algorithm is easier to apply in clinical practice by non-IT experts. From the cancer research community perspective, this approach can be successfully applied as an alternative for the determination of potential pathogenicity of VOUS.

Differential value of brain magnetic resonance imaging in multiple system atrophy cerebellar phenotype and spinocerebellar ataxias

Clinically differentiating multiple system atrophy cerebellar (MSA-C) phenotype and spinocerebellar ataxias (SCAs) is challenging especially in the early stage. We assessed diagnostic value of brain magnetic resonance imaging (MRI) in differentiating MSA-C and SCAs based at different disease stages (<3, 3–7, and >7 years of disease duration). Overall, 186 patients with probable MSA-C and 117 with genetically confirmed SCAs were included. Hot cross bun (HCB) signs and middle cerebellar peduncle (MCP) hyperintensities were exclusively prevalent in MSA-C compared to SCAs at <3 years (HCB, 44.6% versus 0.9%; MCP hyperintensities, 38.3% versus 0.9%, respectively). Sensitivity, specificity, and positive predictive value (PPV) for HCB signs to differentiate MSA-C from SCAs were 45%, 99%, and 99% and those for MCP hyperintensities were 68%, 99%, and 99%, respectively; considering both HCB signs and MCP hyperintensities, specificity and PPV were 100%. However, the differential value of MRI signs decreased over time. MCP widths were smaller and showed more significant decrease in MSA-C than in SCAs. In conclusion, pontine and MCP changes were exclusively prominent in early stage MSA-C rather than in SCAs. Therefore, we should consider disease duration when interpreting pontine and MCP changes in brain MRIs, which will help better differentiate MSA-C and SCAs.

Clinical and Imaging Features of Multiple System Atrophy: Challenges for an Early and Clinically Definitive Diagnosis

Multiple system atrophy (MSA) is an adult-onset, progressive neurodegenerative disorder. Patients with MSA show various phenotypes during the course of their illness, including parkinsonism, cerebellar ataxia, autonomic failure, and pyramidal signs. Patients with MSA sometimes present with isolated autonomic failure or motor symptoms/ signs. The median duration from onset to the concomitant appearance of motor and autonomic symptoms is approximately 2 years but can range up to 14 years. As the presence of both motor and autonomic symptoms is essential for the current diagnostic criteria, early diagnosis is difficult when patients present with isolated autonomic failure or motor symptoms/signs. In contrast, patients with MSA may show severe autonomic failure and die before the presentation of motor symptoms/signs, which are currently required for the diagnosis of MSA. Recent studies have also revealed that patients with MSA may show nonsupporting features of MSA such as dementia, hallucinations, and vertical gaze palsy. To establish early diagnostic criteria and clinically definitive categorization for the successful development of disease-modifying therapy or symptomatic interventions for MSA, research should focus on the isolated phase and atypical symptoms to develop specific clinical, imaging, and fluid biomarkers that satisfy the requirements for objectivity, for semi- or quantitative measurements, and for uncomplicated, worldwide availability. Several novel techniques, such as automated compartmentalization of the brain into multiple parcels for the quantification of gray and white matter volumes on an individual basis and the visualization of α-synuclein and other candidate serum and cerebrospinal fluid biomarkers, may be promising for the early and clinically definitive diagnosis of MSA.