Literature DB >> 24772212

Real-Time Measurement of Functional Tumor Volume by MRI to Assess Treatment Response in Breast Cancer Neoadjuvant Clinical Trials: Validation of the Aegis SER Software Platform.

David C Newitt1, Sheye O Aliu1, Neil Witcomb2, Gal Sela2, John Kornak3, Laura Esserman4, Nola M Hylton1.   

Abstract

PURPOSE: To evaluate the Aegis software implementation for real-time calculation of functional tumor volume (FTV) in the neoadjuvant breast cancer treatment trial setting.
METHODS: The validation data set consisted of 689 contrast-enhanced magnetic resonance imaging (MRI) examinations from the multicenter American College of Radiology Imaging Network 6657 study. Subjects had stage III tumors ≥3 cm in diameter and underwent MRI before, during, and after receiving anthracycline-cyclophosphamide chemotherapy. Studies were previously analyzed by the University of California San Francisco core laboratory using the three-timepoint signal enhancement ratio (SER) FTV algorithm; FTV measurement was subsequently implemented on the Hologic (formerly Sentinelle Medical Inc) Aegis platform. All cases were processed using predefined volumes of interest with no user interaction. Spearman rank correlation was evaluated for all study sites and visits. Cox proportional hazards analysis was used to compare predictive performance of the platforms for recurrence-free survival (RFS) time.
RESULTS: Overall agreement between platforms was good; ρ varied from 0.96 to 0.98 for different study visits. Site-by-site analysis showed considerable variation, from ρ = 0.54 to near perfect agreement (ρ = 1.000) for several sites. Mean absolute difference between platforms ranged from 1.67 cm(3) pretreatment to 0.2 cm(3) posttreatment. The two platforms showed essentially identical performance for predicting RFS using pretreatment or posttreatment FTV.
CONCLUSION: Implementation of the SER FTV algorithm on a commercial platform for real-time MRI volume assessments showed very good agreement with the reference core laboratory system, but variations by site and outlier analysis point out sensitivities to implementation-specific differences.

Entities:  

Year:  2014        PMID: 24772212      PMCID: PMC3998689          DOI: 10.1593/tlo.13877

Source DB:  PubMed          Journal:  Transl Oncol        ISSN: 1936-5233            Impact factor:   4.243


  13 in total

1.  Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?

Authors:  C K Kuhl; P Mielcareck; S Klaschik; C Leutner; E Wardelmann; J Gieseke; H H Schild
Journal:  Radiology       Date:  1999-04       Impact factor: 11.105

2.  Pathology teach and tell: Castleman disease.

Authors:  Gary L Collins; M Carolina Wallis-Crespo; Enid Gilbert-Barness
Journal:  Fetal Pediatr Pathol       Date:  2004-01       Impact factor: 0.958

3.  Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL.

Authors:  Nola M Hylton; Jeffrey D Blume; Wanda K Bernreuter; Etta D Pisano; Mark A Rosen; Elizabeth A Morris; Paul T Weatherall; Constance D Lehman; Gillian M Newstead; Sandra Polin; Helga S Marques; Laura J Esserman; Mitchell D Schnall
Journal:  Radiology       Date:  2012-06       Impact factor: 11.105

4.  Mapping pathophysiological features of breast tumors by MRI at high spatial resolution.

Authors:  H Degani; V Gusis; D Weinstein; S Fields; S Strano
Journal:  Nat Med       Date:  1997-07       Impact factor: 53.440

Review 5.  MR mammography with pharmacokinetic mapping for monitoring of breast cancer treatment during neoadjuvant therapy.

Authors:  M V Knopp; G Brix; H J Junkermann; H P Sinn
Journal:  Magn Reson Imaging Clin N Am       Date:  1994-11       Impact factor: 2.266

6.  Dynamic MR imaging of the breast combined with analysis of contrast agent kinetics in the differentiation of primary breast tumours.

Authors:  S Mussurakis; D L Buckley; P J Drew; J N Fox; P J Carleton; L W Turnbull; A Horsman
Journal:  Clin Radiol       Date:  1997-07       Impact factor: 2.350

7.  Contrast-Enhanced Magnetic Resonance Imaging to Assess Tumor Histopathology and Angiogenesis in Breast Carcinoma.

Authors:  Laura Esserman; Nola Hylton; Tracy George; Noel Weidner
Journal:  Breast J       Date:  1999-01       Impact factor: 2.431

8.  Kinetic assessment of breast tumors using high spatial resolution signal enhancement ratio (SER) imaging.

Authors:  Ka-Loh Li; Roland G Henry; Lisa J Wilmes; Jessica Gibbs; Xiaoping Zhu; Ying Lu; Nola M Hylton
Journal:  Magn Reson Med       Date:  2007-09       Impact factor: 4.668

9.  Quantitative analysis of dynamic Gd-DTPA enhancement in breast tumors using a permeability model.

Authors:  P S Tofts; B Berkowitz; M D Schnall
Journal:  Magn Reson Med       Date:  1995-04       Impact factor: 4.668

10.  Can contrast-enhanced MR imaging predict survival in breast cancer?

Authors:  B Boné; B K Szabó; L G Perbeck; B Veress; P Aspelin
Journal:  Acta Radiol       Date:  2003-07       Impact factor: 1.701

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  9 in total

1.  Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.

Authors:  Wen Li; David C Newitt; Lisa J Wilmes; Ella F Jones; Vignesh Arasu; Jessica Gibbs; Bo La Yun; Elizabeth Li; Savannah C Partridge; John Kornak; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2019-04-26       Impact factor: 4.813

2.  Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial.

Authors:  David C Newitt; Zheng Zhang; Jessica E Gibbs; Savannah C Partridge; Thomas L Chenevert; Mark A Rosen; Patrick J Bolan; Helga S Marques; Sheye Aliu; Wen Li; Lisa Cimino; Bonnie N Joe; Heidi Umphrey; Haydee Ojeda-Fournier; Basak Dogan; Karen Oh; Hiroyuki Abe; Jennifer Drukteinis; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2018-10-22       Impact factor: 4.813

3.  Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis.

Authors:  John Virostko; Allison Hainline; Hakmook Kang; Lori R Arlinghaus; Richard G Abramson; Stephanie L Barnes; Jeffrey D Blume; Sarah Avery; Debra Patt; Boone Goodgame; Thomas E Yankeelov; Anna G Sorace
Journal:  J Med Imaging (Bellingham)       Date:  2017-11-24

4.  Prognostic influence of 3-dimensional tumor volume on breast cancer compared to conventional 1-dimensional tumor size.

Authors:  Ki-Tae Hwang; Wonshik Han; Sang Mok Lee; Jaewoo Choi; Jongjin Kim; Jiyoung Rhu; Young A Kim; Dong-Young Noh
Journal:  Ann Surg Treat Res       Date:  2018-09-28       Impact factor: 1.859

5.  Breast cancer: influence of tumour volume estimation method at MRI on prediction of pathological response to neoadjuvant chemotherapy.

Authors:  Shelley A Henderson; Nazleen Muhammad Gowdh; Colin A Purdie; Lee B Jordan; Andrew Evans; Tracy Brunton; Alastair M Thompson; Sarah Vinnicombe
Journal:  Br J Radiol       Date:  2018-05-02       Impact factor: 3.039

Review 6.  Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.

Authors:  Amita Shukla-Dave; Nancy A Obuchowski; Thomas L Chenevert; Sachin Jambawalikar; Lawrence H Schwartz; Dariya Malyarenko; Wei Huang; Susan M Noworolski; Robert J Young; Mark S Shiroishi; Harrison Kim; Catherine Coolens; Hendrik Laue; Caroline Chung; Mark Rosen; Michael Boss; Edward F Jackson
Journal:  J Magn Reson Imaging       Date:  2018-11-19       Impact factor: 5.119

7.  Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial.

Authors:  David C Newitt; Ghoncheh Amouzandeh; Savannah C Partridge; Helga S Marques; Benjamin A Herman; Brian D Ross; Nola M Hylton; Thomas L Chenevert; Dariya I Malyarenko
Journal:  Tomography       Date:  2020-06

8.  Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Authors:  Wen Li; David C Newitt; Jessica Gibbs; Lisa J Wilmes; Ella F Jones; Vignesh A Arasu; Fredrik Strand; Natsuko Onishi; Alex Anh-Tu Nguyen; John Kornak; Bonnie N Joe; Elissa R Price; Haydee Ojeda-Fournier; Mohammad Eghtedari; Kathryn W Zamora; Stefanie A Woodard; Heidi Umphrey; Wanda Bernreuter; Michael Nelson; An Ly Church; Patrick Bolan; Theresa Kuritza; Kathleen Ward; Kevin Morley; Dulcy Wolverton; Kelly Fountain; Dan Lopez-Paniagua; Lara Hardesty; Kathy Brandt; Elizabeth S McDonald; Mark Rosen; Despina Kontos; Hiroyuki Abe; Deepa Sheth; Erin P Crane; Charlotte Dillis; Pulin Sheth; Linda Hovanessian-Larsen; Dae Hee Bang; Bruce Porter; Karen Y Oh; Neda Jafarian; Alina Tudorica; Bethany L Niell; Jennifer Drukteinis; Mary S Newell; Michael A Cohen; Marina Giurescu; Elise Berman; Constance Lehman; Savannah C Partridge; Kimberly A Fitzpatrick; Marisa H Borders; Wei T Yang; Basak Dogan; Sally Goudreau; Thomas Chenevert; Christina Yau; Angela DeMichele; Don Berry; Laura J Esserman; Nola M Hylton
Journal:  NPJ Breast Cancer       Date:  2020-11-27

9.  Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer.

Authors:  Wen Li; David C Newitt; Bo La Yun; Ella F Jones; Vignesh Arasu; Lisa J Wilmes; Jessica Gibbs; Alex Anh-Tu Nguyen; Natsuko Onishi; John Kornak; Bonnie N Joe; Laura J Esserman; Nola M Hylton
Journal:  Tomography       Date:  2020-06
  9 in total

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