PMID- 27734253
OWN - NLM
STAT- MEDLINE
DCOM- 20180223
LR  - 20220129
IS  - 1860-2002 (Electronic)
IS  - 1536-1632 (Print)
IS  - 1536-1632 (Linking)
VI  - 19
IP  - 3
DP  - 2017 Jun
TI  - A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations 
      Using Multiparametric MRI: First Results with Histological Validation.
PG  - 391-397
LID - 10.1007/s11307-016-1009-y [doi]
AB  - PURPOSE: We aimed to precisely estimate intra-tumoral heterogeneity using 
      spatially regularized spectral clustering (SRSC) on multiparametric MRI data and 
      compare the efficacy of SRSC with the previously reported segmentation techniques 
      in MRI studies. PROCEDURES: Six NMRI nu/nu mice bearing subcutaneous human 
      glioblastoma U87 MG tumors were scanned using a dedicated small animal 7T 
      magnetic resonance imaging (MRI) scanner. The data consisted of T2 weighted 
      images, apparent diffusion coefficient maps, and pre- and post-contrast T2 and 
      T2* maps. Following each scan, the tumors were excised into 2-3-mm thin slices 
      parallel to the axial field of view and processed for histological staining. The 
      MRI data were segmented using SRSC, K-means, fuzzy C-means, and Gaussian mixture 
      modeling to estimate the fractional population of necrotic, peri-necrotic, and 
      viable regions and validated with the fractional population obtained from 
      histology. RESULTS: While the aforementioned methods overestimated peri-necrotic 
      and underestimated viable fractions, SRSC accurately predicted the fractional 
      population of all three tumor tissue types and exhibited strong correlations 
      (r(necrotic) = 0.92, r(peri-necrotic) = 0.82 and r(viable) = 0.98) with the 
      histology. CONCLUSIONS: The precise identification of necrotic, peri-necrotic and 
      viable areas using SRSC may greatly assist in cancer treatment planning and add a 
      new dimension to MRI-guided tumor biopsy procedures.
FAU - Katiyar, Prateek
AU  - Katiyar P
AUID- ORCID: 0000-0002-3062-9366
AD  - Werner Siemens Imaging Center, Department of Preclinical Imaging and 
      Radiopharmacy, Eberhard Karls University Tuebingen, Roentgenweg 13, 72076, 
      Tuebingen, Germany. prateek.katiyar@med.uni-tuebingen.de.
AD  - Max Planck Institute for Intelligent Systems, Tuebingen, Germany. 
      prateek.katiyar@med.uni-tuebingen.de.
FAU - Divine, Mathew R
AU  - Divine MR
AD  - Werner Siemens Imaging Center, Department of Preclinical Imaging and 
      Radiopharmacy, Eberhard Karls University Tuebingen, Roentgenweg 13, 72076, 
      Tuebingen, Germany.
FAU - Kohlhofer, Ursula
AU  - Kohlhofer U
AD  - Institute of Pathology and Neuropathology, Eberhard Karls University Tuebingen 
      and Comprehensive Cancer Center, University Hospital Tuebingen, Tuebingen, 
      Germany.
FAU - Quintanilla-Martinez, Leticia
AU  - Quintanilla-Martinez L
AD  - Institute of Pathology and Neuropathology, Eberhard Karls University Tuebingen 
      and Comprehensive Cancer Center, University Hospital Tuebingen, Tuebingen, 
      Germany.
FAU - Scholkopf, Bernhard
AU  - Scholkopf B
AD  - Max Planck Institute for Intelligent Systems, Tuebingen, Germany.
FAU - Pichler, Bernd J
AU  - Pichler BJ
AD  - Werner Siemens Imaging Center, Department of Preclinical Imaging and 
      Radiopharmacy, Eberhard Karls University Tuebingen, Roentgenweg 13, 72076, 
      Tuebingen, Germany.
FAU - Disselhorst, Jonathan A
AU  - Disselhorst JA
AD  - Werner Siemens Imaging Center, Department of Preclinical Imaging and 
      Radiopharmacy, Eberhard Karls University Tuebingen, Roentgenweg 13, 72076, 
      Tuebingen, Germany.
LA  - eng
GR  - 323196/ERC_/European Research Council/International
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Mol Imaging Biol
JT  - Molecular imaging and biology
JID - 101125610
RN  - 0 (Biomarkers, Tumor)
SB  - IM
MH  - *Algorithms
MH  - Animals
MH  - Biomarkers, Tumor/metabolism
MH  - Cluster Analysis
MH  - *Image Processing, Computer-Assisted
MH  - Magnetic Resonance Imaging/*methods
MH  - Mice, Nude
MH  - Neoplasms/*pathology
MH  - Reproducibility of Results
PMC - PMC5332060
MID - EMS70451
OTO - NOTNLM
OT  - Fuzzy C-means
OT  - Gaussian mixture modeling
OT  - K-means
OT  - Multiparametric MRI
OT  - Spectral clustering
OT  - Tumor heterogeneity
COIS- CONFLICT OF INTEREST: The authors declare that they have no conflict of interest. 
      ETHICAL APPROVAL: All applicable institutional and/or national guidelines for the 
      care and use of animals were followed.
EDAT- 2016/10/14 06:00
MHDA- 2018/02/24 06:00
PMCR- 2016/10/12
CRDT- 2016/10/14 06:00
PHST- 2016/10/14 06:00 [pubmed]
PHST- 2018/02/24 06:00 [medline]
PHST- 2016/10/14 06:00 [entrez]
PHST- 2016/10/12 00:00 [pmc-release]
AID - 10.1007/s11307-016-1009-y [pii]
AID - 1009 [pii]
AID - 10.1007/s11307-016-1009-y [doi]
PST - ppublish
SO  - Mol Imaging Biol. 2017 Jun;19(3):391-397. doi: 10.1007/s11307-016-1009-y.