Endoflip vs high‐definition manometry in the assessment of fecal incontinence: A data‐driven unsupervised comparison

Background How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function. Aims The goal was to compare the diagnostic utility...

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Published inNeurogastroenterology and motility Vol. 30; no. 12; pp. e13462 - n/a
Main Authors Zifan, Ali, Sun, Catherine, Gourcerol, Guillaume, Leroi, Anne M., Mittal, Ravinder K.
Format Journal Article
LanguageEnglish
Published England Wiley Subscription Services, Inc 01.12.2018
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Abstract Background How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function. Aims The goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis. Methods: Blinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine‐learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high‐pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested. Results Intramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001). Conclusion Defective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary. High‐definition anal manometry and functional luminal imaging probe (Endoflip) are two novel techniques to assess the anal closure function; however, their sensitivity and specificity in diagnosing fecal incontinence (FI) are not clear. We used machine‐learning tools to determine the ideal parameters provided by HDAM and Endoflip and performed blinded analysis on a group of FI patients and normal subjects to determine the sensitivity and specificity of two techniques in diagnosing FI. Our data show that both of these techniques are moderately sensitive but highly specific in the FI diagnosing, but they are not complimentary.
AbstractList BackgroundHow much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function.AimsThe goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis. Methods: Blinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine‐learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high‐pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested.ResultsIntramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001).ConclusionDefective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary.
High definition anal manometry and functional luminal imaging probe (endoflip) are two novel techniques to assess the anal closure function, however their sensitivity and specificity in diagnosing fecal incontinence (FI) is not clear. • We used machine learning tools to determine the ideal parameters provided by HDAM and endoflip; and performed blinded analysis on a group of FI patients and normal subjects to determine the sensitivity and specificity of two techniques in diagnosing FI. Our data show that both of these techniques are moderately sensitive but highly specific in the FI diagnosing; but they are not complimentary.
How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function.BACKGROUNDHow much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function.The goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis.AIMSThe goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis.Blinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine-learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high-pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested.METHODSBlinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine-learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high-pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested.Intramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001).RESULTSIntramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001).Defective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary.CONCLUSIONDefective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary.
Background How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function. Aims The goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis. Methods: Blinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine‐learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high‐pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested. Results Intramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001). Conclusion Defective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary. High‐definition anal manometry and functional luminal imaging probe (Endoflip) are two novel techniques to assess the anal closure function; however, their sensitivity and specificity in diagnosing fecal incontinence (FI) are not clear. We used machine‐learning tools to determine the ideal parameters provided by HDAM and Endoflip and performed blinded analysis on a group of FI patients and normal subjects to determine the sensitivity and specificity of two techniques in diagnosing FI. Our data show that both of these techniques are moderately sensitive but highly specific in the FI diagnosing, but they are not complimentary.
How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function. The goal was to compare the diagnostic utility of HDAM and Endoflip using optimal feature(s) in each modality for FI diagnosis. Blinded classification was carried out on 70 female subjects (32 FI & 38 controls), using 3 prominent machine-learning clustering techniques, with 3 distance metrics. For HDAM, descriptive statistics, shape, and textural features characterizing the spatial relationship of pixels in the HDAM high-pressure zone, and for Endoflip, permutations of pressure and CSA combinations (ie, multiplication, division, or individually) at rest and squeeze were tested. Intramodality: (a) Endoflip: Best clustering was obtained using the combination of the ratio of CSA over pressure at 40 and 50 mL at rest, which had significantly better specificity (P < 0.001) than using only pressure at 50 mL, no difference in sensitivity (P = 0.68). (b) HDAM: clustering using textural information at rest had significantly higher specificity compared to using only the maximal pressure at rest (P < 0.001). Intermodality: Clustering results using optimal features were not significantly different with respect to sensitivity or specificity (P > 0.05). Optimal Endoflip feature set differed significantly in specificity compared to HDAM maximal pressure at both rest (P < 0.001) and squeeze (P < 0.001). Defective anal closure function is fairly sensitive and highly specific in diagnosing FI. Using optimal feature sets, HDAM and Endoflip perform in a similar fashion in diagnosing FI, but are not complementary.
Author Leroi, Anne M.
Gourcerol, Guillaume
Mittal, Ravinder K.
Zifan, Ali
Sun, Catherine
AuthorAffiliation 1 Department of Medicine, Division of Gastroenterology, University of California, LA Jolla, CA, USA
2 INSERM U1073, Service de Physiologie Digestive, CHU Rouen, INSERM CIC 1404 Rouen, F-76000
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Keywords cluster analysis
functional luminal imaging probe
high-definition anorectal monetary
unsupervised learning
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Author Contributions: AZ: Data analysis, figure preparation, and wrote the manuscript; CS: Data analysis, figure preparation; AML: Data Acquisition, data analysis; GG: Data Acquisition, data analysis; RKM: Data analysis, co-wrote the manuscript.
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Snippet Background How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional...
How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal...
BackgroundHow much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High‐definition anorectal manometry (HDAM) and functional...
High definition anal manometry and functional luminal imaging probe (endoflip) are two novel techniques to assess the anal closure function, however their...
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StartPage e13462
SubjectTerms Adult
Anorectal
cluster analysis
Fecal incontinence
Fecal Incontinence - diagnosis
Female
functional luminal imaging probe
high‐definition anorectal monetary
Human health and pathology
Humans
Imaging, Three-Dimensional - methods
Learning algorithms
Life Sciences
Machine Learning
Manometry - instrumentation
Manometry - methods
Middle Aged
Pressure
Sensitivity and Specificity
Sphincter
Tissues and Organs
unsupervised learning
Young Adult
Title Endoflip vs high‐definition manometry in the assessment of fecal incontinence: A data‐driven unsupervised comparison
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fnmo.13462
https://www.ncbi.nlm.nih.gov/pubmed/30216661
https://www.proquest.com/docview/2135827533
https://www.proquest.com/docview/2105051685
https://normandie-univ.hal.science/hal-02345194
https://pubmed.ncbi.nlm.nih.gov/PMC6249043
Volume 30
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