Literature DB >> 24784395

Longitudinal, intermodality registration of quantitative breast PET and MRI data acquired before and during neoadjuvant chemotherapy: preliminary results.

Nkiruka C Atuegwu1, Xia Li2, Lori R Arlinghaus2, Richard G Abramson3, Jason M Williams1, A Bapsi Chakravarthy4, Vandana G Abramson5, Thomas E Yankeelov6.   

Abstract

PURPOSE: The authors propose a method whereby serially acquired DCE-MRI, DW-MRI, and FDG-PET breast data sets can be spatially and temporally coregistered to enable the comparison of changes in parameter maps at the voxel level.
METHODS: First, the authors aligned the PET and MR images at each time point rigidly and nonrigidly. To register the MR images longitudinally, the authors extended a nonrigid registration algorithm by including a tumor volume-preserving constraint in the cost function. After the PET images were aligned to the MR images at each time point, the authors then used the transformation obtained from the longitudinal registration of the MRI volumes to register the PET images longitudinally. The authors tested this approach on ten breast cancer patients by calculating a modified Dice similarity of tumor size between the PET and MR images as well as the bending energy and changes in the tumor volume after the application of the registration algorithm.
RESULTS: The median of the modified Dice in the registered PET and DCE-MRI data was 0.92. For the longitudinal registration, the median tumor volume change was -0.03% for the constrained algorithm, compared to -32.16% for the unconstrained registration algorithms (p = 8 × 10(-6)). The medians of the bending energy were 0.0092 and 0.0001 for the unconstrained and constrained algorithms, respectively (p = 2.84 × 10(-7)).
CONCLUSIONS: The results indicate that the proposed method can accurately spatially align DCE-MRI, DW-MRI, and FDG-PET breast images acquired at different time points during therapy while preventing the tumor from being substantially distorted or compressed.

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Year:  2014        PMID: 24784395      PMCID: PMC4000383          DOI: 10.1118/1.4870966

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  28 in total

1.  The adaptive bases algorithm for intensity-based nonrigid image registration.

Authors:  Gustavo K Rohde; Akram Aldroubi; Benoit M Dawant
Journal:  IEEE Trans Med Imaging       Date:  2003-11       Impact factor: 10.048

2.  Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi
Journal:  J Magn Reson Imaging       Date:  1999-01       Impact factor: 4.813

3.  Clinically relevant modeling of tumor growth and treatment response.

Authors:  Thomas E Yankeelov; Nkiruka Atuegwu; David Hormuth; Jared A Weis; Stephanie L Barnes; Michael I Miga; Erin C Rericha; Vito Quaranta
Journal:  Sci Transl Med       Date:  2013-05-29       Impact factor: 17.956

Review 4.  Modeling tracer kinetics in dynamic Gd-DTPA MR imaging.

Authors:  P S Tofts
Journal:  J Magn Reson Imaging       Date:  1997 Jan-Feb       Impact factor: 4.813

5.  Multimodality image registration by maximization of mutual information.

Authors:  F Maes; A Collignon; D Vandermeulen; G Marchal; P Suetens
Journal:  IEEE Trans Med Imaging       Date:  1997-04       Impact factor: 10.048

6.  A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer.

Authors:  Xia Li; E Brian Welch; Lori R Arlinghaus; A Bapsi Chakravarthy; Lei Xu; Jaime Farley; Mary E Loveless; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie A Means-Powell; Vandana G Abramson; Ana M Grau; John C Gore; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2011-08-12       Impact factor: 3.609

7.  Motion correction in diffusion-weighted MRI of the breast at 3T.

Authors:  Lori R Arlinghaus; E Brian Welch; A Bapsi Chakravarthy; Lei Xu; Jaime S Farley; Vandana G Abramson; Ana M Grau; Mark C Kelley; Ingrid A Mayer; Julie A Means-Powell; Ingrid M Meszoely; John C Gore; Thomas E Yankeelov
Journal:  J Magn Reson Imaging       Date:  2011-05       Impact factor: 4.813

8.  Comparison of different SUV-based methods for monitoring cytotoxic therapy with FDG PET.

Authors:  A Stahl; K Ott; M Schwaiger; W A Weber
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-07-15       Impact factor: 9.236

9.  DCE-MRI analysis methods for predicting the response of breast cancer to neoadjuvant chemotherapy: pilot study findings.

Authors:  Xia Li; Lori R Arlinghaus; Gregory D Ayers; A Bapsi Chakravarthy; Richard G Abramson; Vandana G Abramson; Nkiruka Atuegwu; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Ana M Grau; Melinda Sanders; Sandeep R Bhave; Thomas E Yankeelov
Journal:  Magn Reson Med       Date:  2013-05-09       Impact factor: 4.668

10.  Dynamic and static approaches to quantifying 18F-FDG uptake for measuring cancer response to therapy, including the effect of granulocyte CSF.

Authors:  Robert K Doot; Lisa K Dunnwald; Erin K Schubert; Mark Muzi; Lanell M Peterson; Paul E Kinahan; Brenda F Kurland; David A Mankoff
Journal:  J Nucl Med       Date:  2007-05-15       Impact factor: 10.057

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  13 in total

1.  Measuring Glucose Uptake in Primary Invasive Breast Cancer Using Simultaneous Time-of-Flight Breast PET/MRI: A Method Comparison Study with Prone PET/CT.

Authors:  Amy M Fowler; Manoj Kumar; Leah Henze Bancroft; Kelley Salem; Jacob M Johnson; Jillian Karow; Scott B Perlman; Tyler J Bradshaw; Samuel A Hurley; Alan B McMillan; Roberta M Strigel
Journal:  Radiol Imaging Cancer       Date:  2021-01-15

Review 2.  Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting.

Authors:  Anna G Sorace; Sara Harvey; Anum Syed; Thomas E Yankeelov
Journal:  Semin Oncol Nurs       Date:  2017-09-15       Impact factor: 2.315

3.  Comparison of prone versus supine 18F-FDG-PET of locally advanced breast cancer: Phantom and preliminary clinical studies.

Authors:  Jason M Williams; Sudheer D Rani; Xia Li; Lori R Arlinghaus; Tzu-Cheng Lee; Lawrence R MacDonald; Savannah C Partridge; Hakmook Kang; Jennifer G Whisenant; Richard G Abramson; Hannah M Linden; Paul E Kinahan; Thomas E Yankeelov
Journal:  Med Phys       Date:  2015-07       Impact factor: 4.071

4.  Towards real-time topical detection and characterization of FDG dose infiltration prior to PET imaging.

Authors:  Jason M Williams; Lori R Arlinghaus; Sudheer D Rani; Martha D Shone; Vandana G Abramson; Praveen Pendyala; A Bapsi Chakravarthy; William J Gorge; Joshua G Knowland; Ronald K Lattanze; Steven R Perrin; Charles W Scarantino; David W Townsend; Richard G Abramson; Thomas E Yankeelov
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-08-25       Impact factor: 9.236

Review 5.  Breast PET/MR Imaging.

Authors:  Amy Melsaether; Linda Moy
Journal:  Radiol Clin North Am       Date:  2017-02-01       Impact factor: 2.303

Review 6.  Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting.

Authors:  Angela M Jarrett; Anum S Kazerouni; Chengyue Wu; John Virostko; Anna G Sorace; Julie C DiCarlo; David A Hormuth; David A Ekrut; Debra Patt; Boone Goodgame; Sarah Avery; Thomas E Yankeelov
Journal:  Nat Protoc       Date:  2021-09-22       Impact factor: 13.491

7.  Direct Regularization From Co-Registered Contrast MRI Improves Image Quality of MRI-Guided Near-Infrared Spectral Tomography of Breast Lesions.

Authors:  Limin Zhang; Shudong Jiang; Yan Zhao; Jinchao Feng; Brian W Pogue; Keith D Paulsen
Journal:  IEEE Trans Med Imaging       Date:  2018-05       Impact factor: 10.048

8.  Predicting the Response of Breast Cancer to Neoadjuvant Therapy Using a Mechanically Coupled Reaction-Diffusion Model.

Authors:  Jared A Weis; Michael I Miga; Lori R Arlinghaus; Xia Li; Vandana Abramson; A Bapsi Chakravarthy; Praveen Pendyala; Thomas E Yankeelov
Journal:  Cancer Res       Date:  2015-09-02       Impact factor: 12.701

9.  Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results.

Authors:  Angela M Jarrett; David A Hormuth; Stephanie L Barnes; Xinzeng Feng; Wei Huang; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2018-05-17       Impact factor: 3.609

10.  Evaluation of the role of dynamic contrast-enhanced MR imaging for patients with BI-RADS 3-4 microcalcifications.

Authors:  Yanni Jiang; Jianjuan Lou; Siqi Wang; Yi Zhao; Cong Wang; Dehang Wang
Journal:  PLoS One       Date:  2014-06-13       Impact factor: 3.240

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