Quantitative characterizations of ultrashort echo (UTE) images for supporting air-bone separation in the head

Shu-Hui Hsu, Yue Cao, Theodore S. Lawrence, Christina Tsien, Mary Feng, David M. Grodzki, James M. Balter

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus 'true' regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944±0.012 to 0.976±0.003 for UTE images, and from 0.850±0.022 to 0.887±0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1 mm air mask expansion yielded AUC increases of 1 and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both post-processed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data.

Original languageEnglish (US)
Pages (from-to)2869-2880
Number of pages12
JournalPhysics in Medicine and Biology
Volume60
Issue number7
DOIs
StatePublished - Apr 7 2015
Externally publishedYes

Fingerprint

Air
Head
Bone and Bones
ROC Curve
Radiation Oncology
Workflow
Masks
Area Under Curve
Dilatation
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Quantitative characterizations of ultrashort echo (UTE) images for supporting air-bone separation in the head. / Hsu, Shu-Hui; Cao, Yue; Lawrence, Theodore S.; Tsien, Christina; Feng, Mary; Grodzki, David M.; Balter, James M.

In: Physics in Medicine and Biology, Vol. 60, No. 7, 07.04.2015, p. 2869-2880.

Research output: Contribution to journalArticle

Hsu, Shu-Hui ; Cao, Yue ; Lawrence, Theodore S. ; Tsien, Christina ; Feng, Mary ; Grodzki, David M. ; Balter, James M. / Quantitative characterizations of ultrashort echo (UTE) images for supporting air-bone separation in the head. In: Physics in Medicine and Biology. 2015 ; Vol. 60, No. 7. pp. 2869-2880.
@article{86f504a3852f4c7e9a391895d776d911,
title = "Quantitative characterizations of ultrashort echo (UTE) images for supporting air-bone separation in the head",
abstract = "Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus 'true' regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944±0.012 to 0.976±0.003 for UTE images, and from 0.850±0.022 to 0.887±0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1 mm air mask expansion yielded AUC increases of 1 and 4{\%} for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both post-processed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data.",
author = "Shu-Hui Hsu and Yue Cao and Lawrence, {Theodore S.} and Christina Tsien and Mary Feng and Grodzki, {David M.} and Balter, {James M.}",
year = "2015",
month = "4",
day = "7",
doi = "10.1088/0031-9155/60/7/2869",
language = "English (US)",
volume = "60",
pages = "2869--2880",
journal = "Physics in Medicine and Biology",
issn = "0031-9155",
publisher = "IOP Publishing Ltd.",
number = "7",

}

TY - JOUR

T1 - Quantitative characterizations of ultrashort echo (UTE) images for supporting air-bone separation in the head

AU - Hsu, Shu-Hui

AU - Cao, Yue

AU - Lawrence, Theodore S.

AU - Tsien, Christina

AU - Feng, Mary

AU - Grodzki, David M.

AU - Balter, James M.

PY - 2015/4/7

Y1 - 2015/4/7

N2 - Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus 'true' regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944±0.012 to 0.976±0.003 for UTE images, and from 0.850±0.022 to 0.887±0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1 mm air mask expansion yielded AUC increases of 1 and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both post-processed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data.

AB - Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus 'true' regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944±0.012 to 0.976±0.003 for UTE images, and from 0.850±0.022 to 0.887±0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1 mm air mask expansion yielded AUC increases of 1 and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both post-processed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data.

UR - http://www.scopus.com/inward/record.url?scp=84925639689&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84925639689&partnerID=8YFLogxK

U2 - 10.1088/0031-9155/60/7/2869

DO - 10.1088/0031-9155/60/7/2869

M3 - Article

VL - 60

SP - 2869

EP - 2880

JO - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

IS - 7

ER -