Loading…
An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study
Background Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imagi...
Saved in:
| Published in: | Pediatric radiology 2020, Vol.50 (1), p.98-106 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites Items that cite this one |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | cdi_FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3 |
|---|---|
| cites | cdi_FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3 |
| container_end_page | 106 |
| container_issue | 1 |
| container_start_page | 98 |
| container_title | Pediatric radiology |
| container_volume | 50 |
| creator | Strnad, Benjamin S. Orlowski, Hilary L. P. Parsons, Matthew S. Salter, Amber Dahiya, Sonika Sharma, Aseem |
| description | Background
Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imaging (MRI) plays an important role in the diagnosis of MTS, and image processing of MRI is a recently studied strategy to improve its accuracy.
Objective
In a retrospective case-control study, we assessed the performance of an image processing algorithm (Correlative Image Enhancement [CIE]) for detecting MTS-related hippocampal signal abnormality in children.
Materials and methods
Twenty-seven pediatric MTS cases (9 males, 18 females; mean age: 16±standard deviation [SD] 6.7 years) were identified from a pathology database of amygdylo-hippocampectomies performed in children with epilepsy. Twenty-seven children with no seizure history (9 males, 18 females; mean age: 13.8±SD 2.8 years), and with normal brain MRI, were identified for the control group. Blinded investigators processed the MRI coronal FLAIR (fluid-attenuated inversion recovery) images with CIE, saved the processed images as a separate series, and made equivalent region of interest measurements on the processed and unprocessed series to calculate contrast-to-noise ratio. Six blinded reviewers then rated the randomized series for hippocampal signal abnormality and MTS disease status.
Results
CIE increased signal intensity and contrast-to-noise ratio in 26/27 hippocampi with pathologically confirmed MTS (96.3%) with the mean (SD) contrast-to-noise ratio of cases increasing from 14.9 (11.1) to 77.7 (58.7) after processing (
P |
| doi_str_mv | 10.1007/s00247-019-04518-x |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2300600040</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2299947074</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3</originalsourceid><addsrcrecordid>eNp9kc1O3TAQha2KqtzSvkAXyFI33aQd20kcs0OI_khI3bC3HGcSjBL7YicSvD1TLi1SF6w80nxzfGYOY58EfBUA-lsBkLWuQJgK6kZ01f0bthO1kpUwpjtiO1AgqFWbY_a-lFsAUI1Q79ixEo3uWql3bDmPPCxuQr7PyWMpIU7czVPKYb1Z-Jq4CwMfgptiKqHwNPIFS3AzX3HZp0xF8TPmp2aI3N-EecgYz7jj3hWsfIprTkSt2_Dwgb0d3Vzw4_N7wq6_X15f_Kyufv_4dXF-VXmlm7XqtdaSvGPbkUsQo2ukr3tA3UvTdm0nnYEeekTTDrpttG5636ESYpRajeqEfTnI0k53G5bVLqF4nGcXMW3Fkja0dI0aCP38H3qbthzJnJXSGFNr0DVR8kB5WrRkHO0-09XygxVg_2RhD1lYysI-ZWHvaej0WXrrFxz-jfw9PgHqABRqxQnzy9-vyD4CbpGUog</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2299947074</pqid></control><display><type>article</type><title>An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study</title><source>Springer Nature</source><creator>Strnad, Benjamin S. ; Orlowski, Hilary L. P. ; Parsons, Matthew S. ; Salter, Amber ; Dahiya, Sonika ; Sharma, Aseem</creator><creatorcontrib>Strnad, Benjamin S. ; Orlowski, Hilary L. P. ; Parsons, Matthew S. ; Salter, Amber ; Dahiya, Sonika ; Sharma, Aseem</creatorcontrib><description>Background
Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imaging (MRI) plays an important role in the diagnosis of MTS, and image processing of MRI is a recently studied strategy to improve its accuracy.
Objective
In a retrospective case-control study, we assessed the performance of an image processing algorithm (Correlative Image Enhancement [CIE]) for detecting MTS-related hippocampal signal abnormality in children.
Materials and methods
Twenty-seven pediatric MTS cases (9 males, 18 females; mean age: 16±standard deviation [SD] 6.7 years) were identified from a pathology database of amygdylo-hippocampectomies performed in children with epilepsy. Twenty-seven children with no seizure history (9 males, 18 females; mean age: 13.8±SD 2.8 years), and with normal brain MRI, were identified for the control group. Blinded investigators processed the MRI coronal FLAIR (fluid-attenuated inversion recovery) images with CIE, saved the processed images as a separate series, and made equivalent region of interest measurements on the processed and unprocessed series to calculate contrast-to-noise ratio. Six blinded reviewers then rated the randomized series for hippocampal signal abnormality and MTS disease status.
Results
CIE increased signal intensity and contrast-to-noise ratio in 26/27 hippocampi with pathologically confirmed MTS (96.3%) with the mean (SD) contrast-to-noise ratio of cases increasing from 14.9 (11.1) to 77.7 (58.7) after processing (
P
<0.001). Contrast-to-noise ratio increased in 1/54 normal control hippocampi (1.9%), with no significant change in the mean contrast-to-noise ratio of the control group after processing (
P
=0.57). Mean (SD) reader sensitivity for detecting abnormal signal intensity increased from 83.3% (14.2) to 94.8% (3.3) after processing. Mean specificity for abnormal signal intensity increased from 94.4% (7.3) to 96.3% (0). While sensitivity improved after processing for detection of MTS disease status in 4/6 readers, the mean reader sensitivity and specificity for MTS detection increased only minimally after processing, from 79.6% to 80.7% and from 95.7% to 96.3%, respectively.
Conclusion
The CIE image processing algorithm selectively increased the contrast-to-noise ratio of hippocampi affected by MTS, improved reader performance in detecting MTS-related hippocampal signal abnormality and could have high impact on pediatric patients undergoing work-up for seizures.</description><identifier>ISSN: 0301-0449</identifier><identifier>EISSN: 1432-1998</identifier><identifier>DOI: 10.1007/s00247-019-04518-x</identifier><identifier>PMID: 31578627</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Adolescent ; Adult ; Algorithms ; Case-Control Studies ; Child ; Child, Preschool ; Children ; Diagnosis ; Epilepsy ; Epilepsy, Temporal Lobe - diagnostic imaging ; Epilepsy, Temporal Lobe - pathology ; Female ; Females ; Hippocampus ; Humans ; Image contrast ; Image detection ; Image enhancement ; Image Interpretation, Computer-Assisted - methods ; Image processing ; Imaging ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Male ; Males ; Medical diagnosis ; Medical imaging ; Medicine ; Medicine & Public Health ; Neuroimaging ; Neuroradiology ; NMR ; Noise ; Noise control ; Noise intensity ; Nuclear magnetic resonance ; Nuclear Medicine ; Oncology ; Original Article ; Pediatrics ; Radiology ; Reproducibility of Results ; Retrospective Studies ; Sclerosis ; Seizures ; Sensitivity ; Sensitivity and Specificity ; Signal processing ; Temporal Lobe - diagnostic imaging ; Temporal Lobe - pathology ; Ultrasound ; Young Adult</subject><ispartof>Pediatric radiology, 2020, Vol.50 (1), p.98-106</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Pediatric Radiology is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3</citedby><cites>FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3</cites><orcidid>0000-0003-2308-1299</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31578627$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Strnad, Benjamin S.</creatorcontrib><creatorcontrib>Orlowski, Hilary L. P.</creatorcontrib><creatorcontrib>Parsons, Matthew S.</creatorcontrib><creatorcontrib>Salter, Amber</creatorcontrib><creatorcontrib>Dahiya, Sonika</creatorcontrib><creatorcontrib>Sharma, Aseem</creatorcontrib><title>An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study</title><title>Pediatric radiology</title><addtitle>Pediatr Radiol</addtitle><addtitle>Pediatr Radiol</addtitle><description>Background
Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imaging (MRI) plays an important role in the diagnosis of MTS, and image processing of MRI is a recently studied strategy to improve its accuracy.
Objective
In a retrospective case-control study, we assessed the performance of an image processing algorithm (Correlative Image Enhancement [CIE]) for detecting MTS-related hippocampal signal abnormality in children.
Materials and methods
Twenty-seven pediatric MTS cases (9 males, 18 females; mean age: 16±standard deviation [SD] 6.7 years) were identified from a pathology database of amygdylo-hippocampectomies performed in children with epilepsy. Twenty-seven children with no seizure history (9 males, 18 females; mean age: 13.8±SD 2.8 years), and with normal brain MRI, were identified for the control group. Blinded investigators processed the MRI coronal FLAIR (fluid-attenuated inversion recovery) images with CIE, saved the processed images as a separate series, and made equivalent region of interest measurements on the processed and unprocessed series to calculate contrast-to-noise ratio. Six blinded reviewers then rated the randomized series for hippocampal signal abnormality and MTS disease status.
Results
CIE increased signal intensity and contrast-to-noise ratio in 26/27 hippocampi with pathologically confirmed MTS (96.3%) with the mean (SD) contrast-to-noise ratio of cases increasing from 14.9 (11.1) to 77.7 (58.7) after processing (
P
<0.001). Contrast-to-noise ratio increased in 1/54 normal control hippocampi (1.9%), with no significant change in the mean contrast-to-noise ratio of the control group after processing (
P
=0.57). Mean (SD) reader sensitivity for detecting abnormal signal intensity increased from 83.3% (14.2) to 94.8% (3.3) after processing. Mean specificity for abnormal signal intensity increased from 94.4% (7.3) to 96.3% (0). While sensitivity improved after processing for detection of MTS disease status in 4/6 readers, the mean reader sensitivity and specificity for MTS detection increased only minimally after processing, from 79.6% to 80.7% and from 95.7% to 96.3%, respectively.
Conclusion
The CIE image processing algorithm selectively increased the contrast-to-noise ratio of hippocampi affected by MTS, improved reader performance in detecting MTS-related hippocampal signal abnormality and could have high impact on pediatric patients undergoing work-up for seizures.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Case-Control Studies</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Diagnosis</subject><subject>Epilepsy</subject><subject>Epilepsy, Temporal Lobe - diagnostic imaging</subject><subject>Epilepsy, Temporal Lobe - pathology</subject><subject>Female</subject><subject>Females</subject><subject>Hippocampus</subject><subject>Humans</subject><subject>Image contrast</subject><subject>Image detection</subject><subject>Image enhancement</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Imaging</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Males</subject><subject>Medical diagnosis</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Neuroimaging</subject><subject>Neuroradiology</subject><subject>NMR</subject><subject>Noise</subject><subject>Noise control</subject><subject>Noise intensity</subject><subject>Nuclear magnetic resonance</subject><subject>Nuclear Medicine</subject><subject>Oncology</subject><subject>Original Article</subject><subject>Pediatrics</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Sclerosis</subject><subject>Seizures</subject><subject>Sensitivity</subject><subject>Sensitivity and Specificity</subject><subject>Signal processing</subject><subject>Temporal Lobe - diagnostic imaging</subject><subject>Temporal Lobe - pathology</subject><subject>Ultrasound</subject><subject>Young Adult</subject><issn>0301-0449</issn><issn>1432-1998</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kc1O3TAQha2KqtzSvkAXyFI33aQd20kcs0OI_khI3bC3HGcSjBL7YicSvD1TLi1SF6w80nxzfGYOY58EfBUA-lsBkLWuQJgK6kZ01f0bthO1kpUwpjtiO1AgqFWbY_a-lFsAUI1Q79ixEo3uWql3bDmPPCxuQr7PyWMpIU7czVPKYb1Z-Jq4CwMfgptiKqHwNPIFS3AzX3HZp0xF8TPmp2aI3N-EecgYz7jj3hWsfIprTkSt2_Dwgb0d3Vzw4_N7wq6_X15f_Kyufv_4dXF-VXmlm7XqtdaSvGPbkUsQo2ukr3tA3UvTdm0nnYEeekTTDrpttG5636ESYpRajeqEfTnI0k53G5bVLqF4nGcXMW3Fkja0dI0aCP38H3qbthzJnJXSGFNr0DVR8kB5WrRkHO0-09XygxVg_2RhD1lYysI-ZWHvaej0WXrrFxz-jfw9PgHqABRqxQnzy9-vyD4CbpGUog</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Strnad, Benjamin S.</creator><creator>Orlowski, Hilary L. P.</creator><creator>Parsons, Matthew S.</creator><creator>Salter, Amber</creator><creator>Dahiya, Sonika</creator><creator>Sharma, Aseem</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2308-1299</orcidid></search><sort><creationdate>2020</creationdate><title>An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study</title><author>Strnad, Benjamin S. ; Orlowski, Hilary L. P. ; Parsons, Matthew S. ; Salter, Amber ; Dahiya, Sonika ; Sharma, Aseem</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Algorithms</topic><topic>Case-Control Studies</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Diagnosis</topic><topic>Epilepsy</topic><topic>Epilepsy, Temporal Lobe - diagnostic imaging</topic><topic>Epilepsy, Temporal Lobe - pathology</topic><topic>Female</topic><topic>Females</topic><topic>Hippocampus</topic><topic>Humans</topic><topic>Image contrast</topic><topic>Image detection</topic><topic>Image enhancement</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image processing</topic><topic>Imaging</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Males</topic><topic>Medical diagnosis</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Neuroimaging</topic><topic>Neuroradiology</topic><topic>NMR</topic><topic>Noise</topic><topic>Noise control</topic><topic>Noise intensity</topic><topic>Nuclear magnetic resonance</topic><topic>Nuclear Medicine</topic><topic>Oncology</topic><topic>Original Article</topic><topic>Pediatrics</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Sclerosis</topic><topic>Seizures</topic><topic>Sensitivity</topic><topic>Sensitivity and Specificity</topic><topic>Signal processing</topic><topic>Temporal Lobe - diagnostic imaging</topic><topic>Temporal Lobe - pathology</topic><topic>Ultrasound</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Strnad, Benjamin S.</creatorcontrib><creatorcontrib>Orlowski, Hilary L. P.</creatorcontrib><creatorcontrib>Parsons, Matthew S.</creatorcontrib><creatorcontrib>Salter, Amber</creatorcontrib><creatorcontrib>Dahiya, Sonika</creatorcontrib><creatorcontrib>Sharma, Aseem</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Consumer Database (Proquest)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Pediatric radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Strnad, Benjamin S.</au><au>Orlowski, Hilary L. P.</au><au>Parsons, Matthew S.</au><au>Salter, Amber</au><au>Dahiya, Sonika</au><au>Sharma, Aseem</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study</atitle><jtitle>Pediatric radiology</jtitle><stitle>Pediatr Radiol</stitle><addtitle>Pediatr Radiol</addtitle><date>2020</date><risdate>2020</risdate><volume>50</volume><issue>1</issue><spage>98</spage><epage>106</epage><pages>98-106</pages><issn>0301-0449</issn><eissn>1432-1998</eissn><abstract>Background
Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imaging (MRI) plays an important role in the diagnosis of MTS, and image processing of MRI is a recently studied strategy to improve its accuracy.
Objective
In a retrospective case-control study, we assessed the performance of an image processing algorithm (Correlative Image Enhancement [CIE]) for detecting MTS-related hippocampal signal abnormality in children.
Materials and methods
Twenty-seven pediatric MTS cases (9 males, 18 females; mean age: 16±standard deviation [SD] 6.7 years) were identified from a pathology database of amygdylo-hippocampectomies performed in children with epilepsy. Twenty-seven children with no seizure history (9 males, 18 females; mean age: 13.8±SD 2.8 years), and with normal brain MRI, were identified for the control group. Blinded investigators processed the MRI coronal FLAIR (fluid-attenuated inversion recovery) images with CIE, saved the processed images as a separate series, and made equivalent region of interest measurements on the processed and unprocessed series to calculate contrast-to-noise ratio. Six blinded reviewers then rated the randomized series for hippocampal signal abnormality and MTS disease status.
Results
CIE increased signal intensity and contrast-to-noise ratio in 26/27 hippocampi with pathologically confirmed MTS (96.3%) with the mean (SD) contrast-to-noise ratio of cases increasing from 14.9 (11.1) to 77.7 (58.7) after processing (
P
<0.001). Contrast-to-noise ratio increased in 1/54 normal control hippocampi (1.9%), with no significant change in the mean contrast-to-noise ratio of the control group after processing (
P
=0.57). Mean (SD) reader sensitivity for detecting abnormal signal intensity increased from 83.3% (14.2) to 94.8% (3.3) after processing. Mean specificity for abnormal signal intensity increased from 94.4% (7.3) to 96.3% (0). While sensitivity improved after processing for detection of MTS disease status in 4/6 readers, the mean reader sensitivity and specificity for MTS detection increased only minimally after processing, from 79.6% to 80.7% and from 95.7% to 96.3%, respectively.
Conclusion
The CIE image processing algorithm selectively increased the contrast-to-noise ratio of hippocampi affected by MTS, improved reader performance in detecting MTS-related hippocampal signal abnormality and could have high impact on pediatric patients undergoing work-up for seizures.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>31578627</pmid><doi>10.1007/s00247-019-04518-x</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-2308-1299</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0301-0449 |
| ispartof | Pediatric radiology, 2020, Vol.50 (1), p.98-106 |
| issn | 0301-0449 1432-1998 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2300600040 |
| source | Springer Nature |
| subjects | Adolescent Adult Algorithms Case-Control Studies Child Child, Preschool Children Diagnosis Epilepsy Epilepsy, Temporal Lobe - diagnostic imaging Epilepsy, Temporal Lobe - pathology Female Females Hippocampus Humans Image contrast Image detection Image enhancement Image Interpretation, Computer-Assisted - methods Image processing Imaging Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Males Medical diagnosis Medical imaging Medicine Medicine & Public Health Neuroimaging Neuroradiology NMR Noise Noise control Noise intensity Nuclear magnetic resonance Nuclear Medicine Oncology Original Article Pediatrics Radiology Reproducibility of Results Retrospective Studies Sclerosis Seizures Sensitivity Sensitivity and Specificity Signal processing Temporal Lobe - diagnostic imaging Temporal Lobe - pathology Ultrasound Young Adult |
| title | An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T01%3A51%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20image%20processing%20algorithm%20to%20aid%20diagnosis%20of%20mesial%20temporal%20sclerosis%20in%20children:%20a%20case-control%20study&rft.jtitle=Pediatric%20radiology&rft.au=Strnad,%20Benjamin%20S.&rft.date=2020&rft.volume=50&rft.issue=1&rft.spage=98&rft.epage=106&rft.pages=98-106&rft.issn=0301-0449&rft.eissn=1432-1998&rft_id=info:doi/10.1007/s00247-019-04518-x&rft_dat=%3Cproquest_cross%3E2299947074%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c375t-b7772301e6886201fa52c4b0e7b2968682a90b0bee96d765775bc8e311f273f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2299947074&rft_id=info:pmid/31578627&rfr_iscdi=true |