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Diagnosis of Sanfilippo disease correlating clinical, radiological and biochemical findings-a case report.

ABSTRACT: Mucopolysaccharidoses (MPS) are a group of genetic diseases and its diagnosis is a challenging task due to multiple differential diagnosis. We had combined clinical findings, radiological and ophthalmological features. Biochemical test for urine glycosaminoglycans (GAG) was done for confirmation of diagnosis in the patient. The case of Sanfilippo disease was characterized by slowly progressive, severe CNS involvement with mild somatic disease. Radiological features were suggestive of Sanfilippo disease and urine GAG test for MPS was positive in the case. With the clinical features we had multiple differential diagnoses. The radiological investigations minimized the list and the biochemical test confirmed GAG in urine. In this case the combination of clinical, radiological and biochemical findings confirmed the diagnosis of Sanfilippo disease.

SUBMITTER: Agrawal U

PROVIDER: S-EPMC3477452 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Diagnosis of Sanfilippo disease correlating clinical, radiological and biochemical findings-a case report.

Agrawal Udit U Meshram Ajay A Vagha Jayant J Swarnkar Kirti K Palandurkar Kamlesh K

Indian journal of clinical biochemistry : IJCB 20120503 4

Mucopolysaccharidoses (MPS) are a group of genetic diseases and its diagnosis is a challenging task due to multiple differential diagnosis. We had combined clinical findings, radiological and ophthalmological features. Biochemical test for urine glycosaminoglycans (GAG) was done for confirmation of diagnosis in the patient. The case of Sanfilippo disease was characterized by slowly progressive, severe CNS involvement with mild somatic disease. Radiological features were suggestive of Sanfilippo ...[more]

PMID: 24082472

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Project description:BackgroundChest X-ray offers high sensitivity and acceptable specificity as a tuberculosis screening tool, but in areas with a high burden of tuberculosis, there is often a lack of radiological expertise to interpret chest X-ray. Computer-aided detection systems based on artificial intelligence are therefore increasingly used to screen for tuberculosis-related abnormalities on digital chest radiographies. The CAD4TB software has previously been shown to demonstrate high sensitivity for chest X-ray tuberculosis-related abnormalities, but it is not yet calibrated for the detection of non-tuberculosis abnormalities. When screening for tuberculosis, users of computer-aided detection need to be aware that other chest pathologies are likely to be as prevalent as, or more prevalent than, active tuberculosis. However, non--tuberculosis chest X-ray abnormalities detected during chest X-ray screening for tuberculosis remain poorly characterized in the sub-Saharan African setting, with only minimal literature.Case presentationIn this case series, we report on four cases with non-tuberculosis abnormalities detected on CXR in TB TRIAGE + ACCURACY (ClinicalTrials.gov Identifier: NCT04666311), a study in adult presumptive tuberculosis cases at health facilities in Lesotho and South Africa to determine the diagnostic accuracy of two potential tuberculosis triage tests: computer-aided detection (CAD4TB v7, Delft, the Netherlands) and C-reactive protein (Alere Afinion, USA). The four Black African participants presented with the following chest X-ray abnormalities: a 59-year-old woman with pulmonary arteriovenous malformation, a 28-year-old man with pneumothorax, a 20-year-old man with massive bronchiectasis, and a 47-year-old woman with aspergilloma.ConclusionsSolely using chest X-ray computer-aided detection systems based on artificial intelligence as a tuberculosis screening strategy in sub-Saharan Africa comes with benefits, but also risks. Due to the limitation of CAD4TB for non-tuberculosis-abnormality identification, the computer-aided detection software may miss significant chest X-ray abnormalities that require treatment, as exemplified in our four cases. Increased data collection, characterization of non-tuberculosis anomalies and research on the implications of these diseases for individuals and health systems in sub-Saharan Africa is needed to help improve existing artificial intelligence software programs and their use in countries with high tuberculosis burden.

Dataset Information

Diagnosis of Sanfilippo disease correlating clinical, radiological and biochemical findings-a case report.

Publications

Diagnosis of Sanfilippo disease correlating clinical, radiological and biochemical findings-a case report.

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