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Novel Methodology to Evaluate Renal Cysts in Polycystic Kidney Disease

Identifieur interne : 001306 ( Ncbi/Curation ); précédent : 001305; suivant : 001307

Novel Methodology to Evaluate Renal Cysts in Polycystic Kidney Disease

Auteurs : Kyongtae T. Bae [États-Unis] ; Hongliang Sun [États-Unis] ; June Goo Lee [États-Unis] ; Kyungsoo Bae [Corée du Sud] ; Jinhong Wang [États-Unis] ; Cheng Tao [États-Unis] ; Arlene B. Chapman [Géorgie (pays)] ; Vicente E. Torres [États-Unis] ; Jared J. Grantham [États-Unis] ; Michal Mrug [États-Unis] ; William M. Bennett [États-Unis] ; Michael F. Flessner [États-Unis] ; Doug P. Landsittel [États-Unis]

Source :

American journal of nephrology [ 0250-8095 ] ; 2014.

RBID : PMC:4020571

Descripteurs français

KwdFr :
- Adolescent, Adulte, Adulte d'âge moyen, Femelle, Humains, Imagerie par résonance magnétique (), Jeune adulte, Kystes (anatomopathologie), Kystes (diagnostic), Mâle, Polykystose rénale autosomique dominante (anatomopathologie), Polykystose rénale autosomique dominante (diagnostic), Reconnaissance automatique des formes, Rein (anatomopathologie), Rein (physiopathologie), Traitement d'image par ordinateur, Évolution de la maladie.
MESH :
- anatomopathologie : Kystes, Polykystose rénale autosomique dominante, Rein.
- diagnostic : Kystes, Polykystose rénale autosomique dominante.
- physiopathologie : Rein.
- Adolescent, Adulte, Adulte d'âge moyen, Femelle, Humains, Imagerie par résonance magnétique, Jeune adulte, Mâle, Reconnaissance automatique des formes, Traitement d'image par ordinateur, Évolution de la maladie.

English descriptors

KwdEn :
- Adolescent, Adult, Cysts (diagnosis), Cysts (pathology), Disease Progression, Female, Humans, Image Processing, Computer-Assisted, Kidney (pathology), Kidney (physiopathology), Magnetic Resonance Imaging (methods), Male, Middle Aged, Pattern Recognition, Automated, Polycystic Kidney, Autosomal Dominant (diagnosis), Polycystic Kidney, Autosomal Dominant (pathology), Young Adult.
MESH :
- diagnosis : Cysts, Polycystic Kidney, Autosomal Dominant.
- methods : Magnetic Resonance Imaging.
- pathology : Cysts, Kidney, Polycystic Kidney, Autosomal Dominant.
- physiopathology : Kidney.
- Adolescent, Adult, Disease Progression, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Pattern Recognition, Automated, Young Adult.

Abstract

Objective

To develop and assess a semi-automated method for segmenting and counting individual renal cysts from mid-slice MR images in patients with autosomal dominant polycystic kidney disease (ADPKD)

Materials and Methods

A semi-automated method was developed to segment and count individual renal cysts from mid-slice MR images in 241 participants with ADPKD from the Consortium for Radiologic Imaging Studies of ADPKD (CRISP). For each subject, a mid-slice MR image was selected from each set of coronal T2-weighted MR images covering the entire kidney. The selected mid-slice image was processed with the semi-automated method to segment and count individual renal cysts. The number of cysts from the mid-slice image of each kidney was also measured by manual counting. The level of agreement between the semi-automated and manual cyst counts was compared using intra-class correlation (ICC) and a Bland-Altman plot.

Results

Individual renal cysts were successfully segmented using the semi-automated method in all 241 cases. The number of cysts in each kidney measured with the semi-automated and manual counting methods correlated well (ICC=0.96 for the right or left kidney), with a small average difference (-0.52, with higher semi-automated counts, for the right and 0.13, with higher manual counts, for the left) in the semi-automated method. There was, however, substantial variation in a small number of subjects: 6 of 241 (2.5%) participants had a difference in the total cyst count of more than 15.

Conclusion

We have developed a semi-automated method to segment individual renal cysts from mid-slice of MR images in ADPKD kidneys for a quantitative indicator of characterization and disease progression of ADPKD.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4020571

DOI: 10.1159/000358604
PubMed: 24576800
PubMed Central: 4020571

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Cysts (diagnosis)</term>
<term>Cysts (pathology)</term>
<term>Disease Progression</term>
<term>Female</term>
<term>Humans</term>
<term>Image Processing, Computer-Assisted</term>
<term>Kidney (pathology)</term>
<term>Kidney (physiopathology)</term>
<term>Magnetic Resonance Imaging (methods)</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pattern Recognition, Automated</term>
<term>Polycystic Kidney, Autosomal Dominant (diagnosis)</term>
<term>Polycystic Kidney, Autosomal Dominant (pathology)</term>
<term>Young Adult</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Femelle</term>
<term>Humains</term>
<term>Imagerie par résonance magnétique ()</term>
<term>Jeune adulte</term>
<term>Kystes (anatomopathologie)</term>
<term>Kystes (diagnostic)</term>
<term>Mâle</term>
<term>Polykystose rénale autosomique dominante (anatomopathologie)</term>
<term>Polykystose rénale autosomique dominante (diagnostic)</term>
<term>Reconnaissance automatique des formes</term>
<term>Rein (anatomopathologie)</term>
<term>Rein (physiopathologie)</term>
<term>Traitement d'image par ordinateur</term>
<term>Évolution de la maladie</term>
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<keywords scheme="MESH" qualifier="anatomopathologie" xml:lang="fr"><term>Kystes</term>
<term>Polykystose rénale autosomique dominante</term>
<term>Rein</term>
</keywords>
<keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Cysts</term>
<term>Polycystic Kidney, Autosomal Dominant</term>
</keywords>
<keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Kystes</term>
<term>Polykystose rénale autosomique dominante</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Magnetic Resonance Imaging</term>
</keywords>
<keywords scheme="MESH" qualifier="pathology" xml:lang="en"><term>Cysts</term>
<term>Kidney</term>
<term>Polycystic Kidney, Autosomal Dominant</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathologie" xml:lang="fr"><term>Rein</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Kidney</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Disease Progression</term>
<term>Female</term>
<term>Humans</term>
<term>Image Processing, Computer-Assisted</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pattern Recognition, Automated</term>
<term>Young Adult</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Femelle</term>
<term>Humains</term>
<term>Imagerie par résonance magnétique</term>
<term>Jeune adulte</term>
<term>Mâle</term>
<term>Reconnaissance automatique des formes</term>
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<front><div type="abstract" xml:lang="en"><sec id="S1"><title>Objective</title>
<p id="P1">To develop and assess a semi-automated method for segmenting and counting individual renal cysts from mid-slice MR images in patients with autosomal dominant polycystic kidney disease (ADPKD)</p>
</sec>
<sec id="S2"><title>Materials and Methods</title>
<p id="P2">A semi-automated method was developed to segment and count individual renal cysts from mid-slice MR images in 241 participants with ADPKD from the Consortium for Radiologic Imaging Studies of ADPKD (CRISP). For each subject, a mid-slice MR image was selected from each set of coronal T2-weighted MR images covering the entire kidney. The selected mid-slice image was processed with the semi-automated method to segment and count individual renal cysts. The number of cysts from the mid-slice image of each kidney was also measured by manual counting. The level of agreement between the semi-automated and manual cyst counts was compared using intra-class correlation (ICC) and a Bland-Altman plot.</p>
</sec>
<sec id="S3"><title>Results</title>
<p id="P3">Individual renal cysts were successfully segmented using the semi-automated method in all 241 cases. The number of cysts in each kidney measured with the semi-automated and manual counting methods correlated well (ICC=0.96 for the right or left kidney), with a small average difference (-0.52, with higher semi-automated counts, for the right and 0.13, with higher manual counts, for the left) in the semi-automated method. There was, however, substantial variation in a small number of subjects: 6 of 241 (2.5%) participants had a difference in the total cyst count of more than 15.</p>
</sec>
<sec id="S4"><title>Conclusion</title>
<p id="P4">We have developed a semi-automated method to segment individual renal cysts from mid-slice of MR images in ADPKD kidneys for a quantitative indicator of characterization and disease progression of ADPKD.</p>
</sec>
</div>
</front>
</TEI>
</record>

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Novel Methodology to Evaluate Renal Cysts in Polycystic Kidney Disease

Novel Methodology to Evaluate Renal Cysts in Polycystic Kidney Disease

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