@article{
 title = {Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 tesla endorectal, in vivo T2-weighted MR imagery},
 type = {article},
 year = {2012},
 keywords = {T2-weighted,central gland,classification,magnetic resonance imaging,peripheral zone,prostate cancer,quantitative imaging signatures,texture analysis},
 volume = {36},
 id = {ce67ad5e-c74a-3bc0-8e18-a9759418f725},
 created = {2023-10-25T08:56:40.653Z},
 file_attached = {false},
 profile_id = {eaba325f-653b-3ee2-b960-0abd5146933e},
 last_modified = {2023-10-25T08:56:40.653Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {true},
 abstract = {Purpose: To identify and evaluate textural quantitative imaging signatures (QISes) for tumors occurring within the central gland (CG) and peripheral zone (PZ) of the prostate, respectively, as seen on in vivo 3 Tesla (T) endorectal T2-weighted (T2w) MRI. Materials and Methods: This study used 22 preoperative prostate MRI data sets (16 PZ, 6 CG) acquired from men with confirmed prostate cancer (CaP) and scheduled for radical prostatectomy (RP). The prostate region-of-interest (ROI) was automatically delineated on T2w MRI, following which it was corrected for intensity-based acquisition artifacts. An expert pathologist manually delineated the dominant tumor regions on ex vivo sectioned and stained RP specimens as well as identified each of the studies as either a CG or PZ CaP. A nonlinear registration scheme was used to spatially align and then map CaP extent from the ex vivo RP sections onto the corresponding MRI slices. A total of 110 texture features were then extracted on a per-voxel basis from all T2w MRI data sets. An information theoretic feature selection procedure was then applied to identify QISes comprising T2w MRI textural features specific to CG and PZ CaP, respectively. The QISes for CG and PZ CaP were evaluated by means of Quadratic Discriminant Analysis (QDA) on a per-voxel basis against the ground truth for CaP on T2w MRI, mapped from corresponding histology. Results: The QDA classifier yielded an area under the Receiver Operating characteristic curve of 0.86 for the CG CaP studies, and 0.73 for the PZ CaP studies over 25 runs of randomized three-fold cross-validation. By comparison, the accuracy of the QDA classifier was significantly lower when (a) using all 110 texture features (with no feature selection applied), as well as (b) a randomly selected combination of texture features. Conclusion: CG and PZ prostate cancers have significantly differing textural quantitative imaging signatures on T2w endorectal in vivo MRI. © 2012 Wiley Periodicals, Inc.},
 bibtype = {article},
 author = {Viswanath, S.E. and Bloch, N.B. and Chappelow, J.C. and Toth, R. and Rofsky, N.M. and Genega, E.M. and Lenkinski, R.E. and Madabhushi, A.},
 doi = {10.1002/jmri.23618},
 journal = {Journal of Magnetic Resonance Imaging},
 number = {1}
}

{"_id":"8Rxb5i6G4JtvQu9J8","bibbaseid":"viswanath-bloch-chappelow-toth-rofsky-genega-lenkinski-madabhushi-centralglandandperipheralzoneprostatetumorshavesignificantlydifferentquantitativeimagingsignatureson3teslaendorectalinvivot2weightedmrimagery-2012","authorIDs":["4Bygm8ju5EJL5ymrQ","6QhxQnZANogYLvQK3","95yz33vzsQF4xkftF","9XZAWfqroLnhv8Yvi","MFZedjHxD2knXtEDJ","QcPeEw2JciXtbZFYv","h2B3dsR3oRk42DaEg","ikoetnssERNBFB49Z","kEjtqmTXpJD7idBiM","mKXojsM3x8movswn3","mTxR5EmKaPZT4FPRw","wqGyw5WWC92w63FBr","zmtHQr2MyDkT4KaPS","zy5Yt2FBfMrjEQLRW"],"author_short":["Viswanath, S.","Bloch, N.","Chappelow, J.","Toth, R.","Rofsky, N.","Genega, E.","Lenkinski, R.","Madabhushi, A."],"bibdata":{"title":"Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 tesla endorectal, in vivo T2-weighted MR imagery","type":"article","year":"2012","keywords":"T2-weighted,central gland,classification,magnetic resonance imaging,peripheral zone,prostate cancer,quantitative imaging signatures,texture analysis","volume":"36","id":"ce67ad5e-c74a-3bc0-8e18-a9759418f725","created":"2023-10-25T08:56:40.653Z","file_attached":false,"profile_id":"eaba325f-653b-3ee2-b960-0abd5146933e","last_modified":"2023-10-25T08:56:40.653Z","read":false,"starred":false,"authored":"true","confirmed":false,"hidden":false,"private_publication":"true","abstract":"Purpose: To identify and evaluate textural quantitative imaging signatures (QISes) for tumors occurring within the central gland (CG) and peripheral zone (PZ) of the prostate, respectively, as seen on in vivo 3 Tesla (T) endorectal T2-weighted (T2w) MRI. Materials and Methods: This study used 22 preoperative prostate MRI data sets (16 PZ, 6 CG) acquired from men with confirmed prostate cancer (CaP) and scheduled for radical prostatectomy (RP). The prostate region-of-interest (ROI) was automatically delineated on T2w MRI, following which it was corrected for intensity-based acquisition artifacts. An expert pathologist manually delineated the dominant tumor regions on ex vivo sectioned and stained RP specimens as well as identified each of the studies as either a CG or PZ CaP. A nonlinear registration scheme was used to spatially align and then map CaP extent from the ex vivo RP sections onto the corresponding MRI slices. A total of 110 texture features were then extracted on a per-voxel basis from all T2w MRI data sets. An information theoretic feature selection procedure was then applied to identify QISes comprising T2w MRI textural features specific to CG and PZ CaP, respectively. The QISes for CG and PZ CaP were evaluated by means of Quadratic Discriminant Analysis (QDA) on a per-voxel basis against the ground truth for CaP on T2w MRI, mapped from corresponding histology. Results: The QDA classifier yielded an area under the Receiver Operating characteristic curve of 0.86 for the CG CaP studies, and 0.73 for the PZ CaP studies over 25 runs of randomized three-fold cross-validation. By comparison, the accuracy of the QDA classifier was significantly lower when (a) using all 110 texture features (with no feature selection applied), as well as (b) a randomly selected combination of texture features. Conclusion: CG and PZ prostate cancers have significantly differing textural quantitative imaging signatures on T2w endorectal in vivo MRI. © 2012 Wiley Periodicals, Inc.","bibtype":"article","author":"Viswanath, S.E. and Bloch, N.B. and Chappelow, J.C. and Toth, R. and Rofsky, N.M. and Genega, E.M. and Lenkinski, R.E. and Madabhushi, A.","doi":"10.1002/jmri.23618","journal":"Journal of Magnetic Resonance Imaging","number":"1","bibtex":"@article{\n title = {Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 tesla endorectal, in vivo T2-weighted MR imagery},\n type = {article},\n year = {2012},\n keywords = {T2-weighted,central gland,classification,magnetic resonance imaging,peripheral zone,prostate cancer,quantitative imaging signatures,texture analysis},\n volume = {36},\n id = {ce67ad5e-c74a-3bc0-8e18-a9759418f725},\n created = {2023-10-25T08:56:40.653Z},\n file_attached = {false},\n profile_id = {eaba325f-653b-3ee2-b960-0abd5146933e},\n last_modified = {2023-10-25T08:56:40.653Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {true},\n abstract = {Purpose: To identify and evaluate textural quantitative imaging signatures (QISes) for tumors occurring within the central gland (CG) and peripheral zone (PZ) of the prostate, respectively, as seen on in vivo 3 Tesla (T) endorectal T2-weighted (T2w) MRI. Materials and Methods: This study used 22 preoperative prostate MRI data sets (16 PZ, 6 CG) acquired from men with confirmed prostate cancer (CaP) and scheduled for radical prostatectomy (RP). The prostate region-of-interest (ROI) was automatically delineated on T2w MRI, following which it was corrected for intensity-based acquisition artifacts. An expert pathologist manually delineated the dominant tumor regions on ex vivo sectioned and stained RP specimens as well as identified each of the studies as either a CG or PZ CaP. A nonlinear registration scheme was used to spatially align and then map CaP extent from the ex vivo RP sections onto the corresponding MRI slices. A total of 110 texture features were then extracted on a per-voxel basis from all T2w MRI data sets. An information theoretic feature selection procedure was then applied to identify QISes comprising T2w MRI textural features specific to CG and PZ CaP, respectively. The QISes for CG and PZ CaP were evaluated by means of Quadratic Discriminant Analysis (QDA) on a per-voxel basis against the ground truth for CaP on T2w MRI, mapped from corresponding histology. Results: The QDA classifier yielded an area under the Receiver Operating characteristic curve of 0.86 for the CG CaP studies, and 0.73 for the PZ CaP studies over 25 runs of randomized three-fold cross-validation. By comparison, the accuracy of the QDA classifier was significantly lower when (a) using all 110 texture features (with no feature selection applied), as well as (b) a randomly selected combination of texture features. 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