Parkinson‘s disease and GIT involvement

Involvement of the upper part of the gastrointestinal tract in patients with Parkinson disease is reported less frequently than the involvement of the lower part. Its clinical impact is, however, substantial because dysphagic symptoms considerably decrease the quality of life and may lead to life threatening complications. Even though the clinical symptoms related to esophageal motility disorders as a result of Parkinson disease are more common in the advanced stages of the disease, these could be diagnosed much earlier using high resolution manometry. The authors describe the basic principles of diagnostic management of dysphagia in patients with Parkinson disease and in the clinical part they present an analysis of their patient cohort. They found out that nonspecific and diverse motility disorders are present in most patients, even without dysphagic symptoms. In the experimental part, we outlined new possibilities for diagnostic procedures using the most up-to-date methods for the detection of pathological forms of alpha-synuclein and advanced microscopic methods. Key words: esophageal motility disorders – manometry – Parkinson disease – alpha-synuclein – FLIM analysis – immunohistochemistry

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Faculty Opinions recommendation of High-Resolution Manometry Improves the Diagnosis of Esophageal Motility Disorders in Patients With Dysphagia: A Randomized Multicenter Study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726113534.793515539 ◽

2016 ◽

Author(s):

Milli Gupta

Keyword(s):

High Resolution ◽

Multicenter Study ◽

Esophageal Motility ◽

Esophageal Motility Disorders ◽

Motility Disorders ◽

High Resolution Manometry

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How to Cope with Big Data in Functional Analysis of the Esophagus

Visceral Medicine ◽

10.1159/000511931 ◽

2020 ◽

Vol 36 (6) ◽

pp. 439-442

Author(s):

Alissa Jell ◽

Christina Kuttler ◽

Daniel Ostler ◽

Norbert Hüser

Keyword(s):

Esophageal Motility ◽

Learning Algorithm ◽

Supervised Machine Learning ◽

Esophageal Motility Disorders ◽

Motility Disorders ◽

High Resolution Manometry ◽

Evaluation Time ◽

Core Evaluation

Introduction: Esophageal motility disorders have a severe impact on patients’ quality of life. While high-resolution manometry (HRM) is the gold standard in the diagnosis of esophageal motility disorders, intermittently occurring muscular deficiencies often remain undiscovered if they do not lead to an intense level of discomfort or cause suffering in patients. Ambulatory long-term HRM allows us to study the circadian (dys)function of the esophagus in a unique way. With the prolonged examination period of 24 h, however, there is an immense increase in data which requires personnel and time for evaluation not available in clinical routine. Artificial intelligence (AI) might contribute here by performing an autonomous analysis. Methods: On the basis of 40 previously performed and manually tagged long-term HRM in patients with suspected temporary esophageal motility disorders, we implemented a supervised machine learning algorithm for automated swallow detection and classification. Results: For a set of 24 h of long-term HRM by means of this algorithm, the evaluation time could be reduced from 3 days to a core evaluation time of 11 min for automated swallow detection and clustering plus an additional 10–20 min of evaluation time, depending on the complexity and diversity of motility disorders in the examined patient. In 12.5% of patients with suggested esophageal motility disorders, AI-enabled long-term HRM was able to reveal new and relevant findings for subsequent therapy. Conclusion: This new approach paves the way to the clinical use of long-term HRM in patients with temporary esophageal motility disorders and might serve as an ideal and clinically relevant application of AI.

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