Cargando…

COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lu...

Descripción completa

Detalles Bibliográficos
Autores principales: Suri, Jasjit S., Agarwal, Sushant, Carriero, Alessandro, Paschè, Alessio, Danna, Pietro S. C., Columbu, Marta, Saba, Luca, Viskovic, Klaudija, Mehmedović, Armin, Agarwal, Samriddhi, Gupta, Lakshya, Faa, Gavino, Singh, Inder M., Turk, Monika, Chadha, Paramjit S., Johri, Amer M., Khanna, Narendra N., Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sobel, David W., Balestrieri, Antonella, Sfikakis, Petros P., Tsoulfas, George, Protogerou, Athanasios, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Teji, Jagjit S., Al-Maini, Mustafa, Dhanjil, Surinder K., Nicolaides, Andrew, Sharma, Aditya, Rathore, Vijay, Fatemi, Mostafa, Alizad, Azra, Krishnan, Pudukode R., Nagy, Ferenc, Ruzsa, Zoltan, Gupta, Archna, Naidu, Subbaram, Paraskevas, Kosmas I., Kalra, Mannudeep K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699928/
https://www.ncbi.nlm.nih.gov/pubmed/34943603
http://dx.doi.org/10.3390/diagnostics11122367
_version_ 1784620632767463424
author Suri, Jasjit S.
Agarwal, Sushant
Carriero, Alessandro
Paschè, Alessio
Danna, Pietro S. C.
Columbu, Marta
Saba, Luca
Viskovic, Klaudija
Mehmedović, Armin
Agarwal, Samriddhi
Gupta, Lakshya
Faa, Gavino
Singh, Inder M.
Turk, Monika
Chadha, Paramjit S.
Johri, Amer M.
Khanna, Narendra N.
Mavrogeni, Sophie
Laird, John R.
Pareek, Gyan
Miner, Martin
Sobel, David W.
Balestrieri, Antonella
Sfikakis, Petros P.
Tsoulfas, George
Protogerou, Athanasios
Misra, Durga Prasanna
Agarwal, Vikas
Kitas, George D.
Teji, Jagjit S.
Al-Maini, Mustafa
Dhanjil, Surinder K.
Nicolaides, Andrew
Sharma, Aditya
Rathore, Vijay
Fatemi, Mostafa
Alizad, Azra
Krishnan, Pudukode R.
Nagy, Ferenc
Ruzsa, Zoltan
Gupta, Archna
Naidu, Subbaram
Paraskevas, Kosmas I.
Kalra, Mannudeep K.
author_facet Suri, Jasjit S.
Agarwal, Sushant
Carriero, Alessandro
Paschè, Alessio
Danna, Pietro S. C.
Columbu, Marta
Saba, Luca
Viskovic, Klaudija
Mehmedović, Armin
Agarwal, Samriddhi
Gupta, Lakshya
Faa, Gavino
Singh, Inder M.
Turk, Monika
Chadha, Paramjit S.
Johri, Amer M.
Khanna, Narendra N.
Mavrogeni, Sophie
Laird, John R.
Pareek, Gyan
Miner, Martin
Sobel, David W.
Balestrieri, Antonella
Sfikakis, Petros P.
Tsoulfas, George
Protogerou, Athanasios
Misra, Durga Prasanna
Agarwal, Vikas
Kitas, George D.
Teji, Jagjit S.
Al-Maini, Mustafa
Dhanjil, Surinder K.
Nicolaides, Andrew
Sharma, Aditya
Rathore, Vijay
Fatemi, Mostafa
Alizad, Azra
Krishnan, Pudukode R.
Nagy, Ferenc
Ruzsa, Zoltan
Gupta, Archna
Naidu, Subbaram
Paraskevas, Kosmas I.
Kalra, Mannudeep K.
author_sort Suri, Jasjit S.
collection PubMed
description (1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPoint(TM), Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland–Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg.
format Online
Article
Text
id pubmed-8699928
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-86999282021-12-24 COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts Suri, Jasjit S. Agarwal, Sushant Carriero, Alessandro Paschè, Alessio Danna, Pietro S. C. Columbu, Marta Saba, Luca Viskovic, Klaudija Mehmedović, Armin Agarwal, Samriddhi Gupta, Lakshya Faa, Gavino Singh, Inder M. Turk, Monika Chadha, Paramjit S. Johri, Amer M. Khanna, Narendra N. Mavrogeni, Sophie Laird, John R. Pareek, Gyan Miner, Martin Sobel, David W. Balestrieri, Antonella Sfikakis, Petros P. Tsoulfas, George Protogerou, Athanasios Misra, Durga Prasanna Agarwal, Vikas Kitas, George D. Teji, Jagjit S. Al-Maini, Mustafa Dhanjil, Surinder K. Nicolaides, Andrew Sharma, Aditya Rathore, Vijay Fatemi, Mostafa Alizad, Azra Krishnan, Pudukode R. Nagy, Ferenc Ruzsa, Zoltan Gupta, Archna Naidu, Subbaram Paraskevas, Kosmas I. Kalra, Mannudeep K. Diagnostics (Basel) Article (1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPoint(TM), Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland–Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg. MDPI 2021-12-15 /pmc/articles/PMC8699928/ /pubmed/34943603 http://dx.doi.org/10.3390/diagnostics11122367 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Suri, Jasjit S.
Agarwal, Sushant
Carriero, Alessandro
Paschè, Alessio
Danna, Pietro S. C.
Columbu, Marta
Saba, Luca
Viskovic, Klaudija
Mehmedović, Armin
Agarwal, Samriddhi
Gupta, Lakshya
Faa, Gavino
Singh, Inder M.
Turk, Monika
Chadha, Paramjit S.
Johri, Amer M.
Khanna, Narendra N.
Mavrogeni, Sophie
Laird, John R.
Pareek, Gyan
Miner, Martin
Sobel, David W.
Balestrieri, Antonella
Sfikakis, Petros P.
Tsoulfas, George
Protogerou, Athanasios
Misra, Durga Prasanna
Agarwal, Vikas
Kitas, George D.
Teji, Jagjit S.
Al-Maini, Mustafa
Dhanjil, Surinder K.
Nicolaides, Andrew
Sharma, Aditya
Rathore, Vijay
Fatemi, Mostafa
Alizad, Azra
Krishnan, Pudukode R.
Nagy, Ferenc
Ruzsa, Zoltan
Gupta, Archna
Naidu, Subbaram
Paraskevas, Kosmas I.
Kalra, Mannudeep K.
COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title_full COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title_fullStr COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title_full_unstemmed COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title_short COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts
title_sort covlias 1.0 vs. medseg: artificial intelligence-based comparative study for automated covid-19 computed tomography lung segmentation in italian and croatian cohorts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699928/
https://www.ncbi.nlm.nih.gov/pubmed/34943603
http://dx.doi.org/10.3390/diagnostics11122367
work_keys_str_mv AT surijasjits covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT agarwalsushant covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT carrieroalessandro covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT paschealessio covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT dannapietrosc covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT columbumarta covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT sabaluca covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT viskovicklaudija covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT mehmedovicarmin covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT agarwalsamriddhi covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT guptalakshya covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT faagavino covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT singhinderm covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT turkmonika covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT chadhaparamjits covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT johriamerm covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT khannanarendran covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT mavrogenisophie covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT lairdjohnr covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT pareekgyan covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT minermartin covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT sobeldavidw covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT balestrieriantonella covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT sfikakispetrosp covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT tsoulfasgeorge covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT protogerouathanasios covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT misradurgaprasanna covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT agarwalvikas covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT kitasgeorged covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT tejijagjits covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT almainimustafa covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT dhanjilsurinderk covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT nicolaidesandrew covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT sharmaaditya covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT rathorevijay covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT fatemimostafa covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT alizadazra covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT krishnanpudukoder covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT nagyferenc covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT ruzsazoltan covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT guptaarchna covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT naidusubbaram covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT paraskevaskosmasi covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts
AT kalramannudeepk covlias10vsmedsegartificialintelligencebasedcomparativestudyforautomatedcovid19computedtomographylungsegmentationinitalianandcroatiancohorts