Literature DB >> 25096888

Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors.

Paolo Belli1, Melania Costantini, Enida Bufi, Giuseppe Giovanni Giardina, Pierluigi Rinaldi, Gianluca Franceschini, Lorenzo Bonomo.   

Abstract

PURPOSE: This study was done to investigate the correlation between the apparent diffusion coefficient (ADC) and prognostic factors of breast cancer.
MATERIALS AND METHODS: From January 2008 to June 2011, all consecutive patients with breast cancer who underwent breast magnetic resonance imaging (MRI) and subsequent surgery in our hospital were enrolled in our study. The MRI protocol included a diffusion-weighted imaging sequence with b values of 0 and 1,000 s/mm(2). For each target lesion in the breast, the ADC value was compared with regard to major prognostic factors: histology, tumour grade, tumour size, lymph node status, and age.
RESULTS: A total of 289 patients with a mean age of 53.49 years were included in the study. The mean ADC value of malignant lesions was 1.02 × 10(-3) mm(2)/s. In situ carcinomas, grade 1 lesions, and tumours without lymph nodal involvement had mean ADC values that were significantly higher than those of invasive carcinomas (p = 0.009), grade 2/3 lesions (p < 0.001), and tumours with nodal metastases (p = 0.001). No significant differences were observed in ADC values among tumours of different sizes or among patient age groups.
CONCLUSIONS: ADC values appear to correlate with tumour grade and some major prognostic factors.

Entities:  

Mesh:

Year:  2014        PMID: 25096888     DOI: 10.1007/s11547-014-0442-8

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  37 in total

1.  Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors.

Authors:  Sibel Kul; Aysegul Cansu; Etem Alhan; Hasan Dinc; Gurbuz Gunes; Abdulkadir Reis
Journal:  AJR Am J Roentgenol       Date:  2011-01       Impact factor: 3.959

2.  Diffusion-weighted imaging in breast cancer: relationship between apparent diffusion coefficient and tumour aggressiveness.

Authors:  M Costantini; P Belli; P Rinaldi; E Bufi; G Giardina; G Franceschini; G Petrone; L Bonomo
Journal:  Clin Radiol       Date:  2010-09-24       Impact factor: 2.350

3.  Breast cancer prognostic factors: evaluation guidelines.

Authors:  W L McGuire
Journal:  J Natl Cancer Inst       Date:  1991-02-06       Impact factor: 13.506

4.  Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value.

Authors:  Savannah C Partridge; Wendy B DeMartini; Brenda F Kurland; Peter R Eby; Steven W White; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2009-12       Impact factor: 3.959

5.  Cancer associated fibroblasts: the dark side of the coin.

Authors:  Paolo Cirri; Paola Chiarugi
Journal:  Am J Cancer Res       Date:  2011-03-12       Impact factor: 6.166

Review 6.  Modern classification of breast cancer: should we stick with morphology or convert to molecular profile characteristics.

Authors:  Emad A Rakha; Ian O Ellis
Journal:  Adv Anat Pathol       Date:  2011-07       Impact factor: 3.875

7.  Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors.

Authors:  Sung Hun Kim; Eun Suk Cha; Hyeon Sook Kim; Bong Joo Kang; Jae Jeong Choi; Ji Han Jung; Yong Gyu Park; Young Jin Suh
Journal:  J Magn Reson Imaging       Date:  2009-09       Impact factor: 4.813

8.  Classification and grading of invasive breast carcinoma.

Authors:  C W Elston
Journal:  Verh Dtsch Ges Pathol       Date:  2005

9.  Hormone receptor status, tumor characteristics, and prognosis: a prospective cohort of breast cancer patients.

Authors:  Lisa K Dunnwald; Mary Anne Rossing; Christopher I Li
Journal:  Breast Cancer Res       Date:  2007       Impact factor: 6.466

10.  Redefining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease-specific survival than estrogen receptor or HER-2 across all tumor subtypes.

Authors:  Golareh Habibi; Samuel Leung; Jennifer H Law; Karen Gelmon; Hamid Masoudi; Dmitry Turbin; Michael Pollak; Torsten O Nielsen; David Huntsman; Sandra E Dunn
Journal:  Breast Cancer Res       Date:  2008-10-16       Impact factor: 6.466

View more
  16 in total

1.  Correlation between minimum apparent diffusion coefficient values and the histological grade of breast invasive ductal carcinoma.

Authors:  Suhong Zhao; Weihua Guo; Ru Tan; Peipei Chen; Zhaohua Li; Fengguo Sun; Guangrui Shao
Journal:  Oncol Lett       Date:  2018-03-23       Impact factor: 2.967

2.  Is there any relationship between adc values of diffusion-weighted imaging and the histopathological prognostic factors of invasive ductal carcinoma?

Authors:  Hale Aydin; Bahar Guner; Isil Esen Bostanci; Zarife Melda Bulut; Bilgin Kadri Aribas; Lutfi Dogan; Mehmet Ali Gulcelik
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

3.  Diagnostic Value of Diffusion-weighted Imaging and Apparent Diffusion Coefficient Values in the Differentiation of Breast Lesions, Histpathologic Subgroups and Correlatıon with Prognostıc Factors using 3.0 Tesla MR.

Authors:  Yasin Akın; M Ümit Uğurlu; Handan Kaya; Erkin Arıbal
Journal:  J Breast Health       Date:  2016-07-01

4.  Apparent diffusion coefficient in estrogen receptor-positive and lymph node-negative invasive breast cancers at 3.0T DW-MRI: A potential predictor for an oncotype Dx test recurrence score.

Authors:  Sunitha B Thakur; Manuela Durando; Soledad Milans; Gene Y Cho; Lucas Gennaro; Elizabeth J Sutton; Dilip Giri; Elizabeth A Morris
Journal:  J Magn Reson Imaging       Date:  2017-06-22       Impact factor: 4.813

5.  Diffusion tensor magnetic resonance imaging of breast cancer: associations between diffusion metrics and histological prognostic factors.

Authors:  Jin You Kim; Jin Joo Kim; Suk Kim; Ki Seok Choo; Ahrong Kim; Taewoo Kang; Heesung Park
Journal:  Eur Radiol       Date:  2018-04-30       Impact factor: 5.315

6.  Pretreatment Apparent Diffusion Coefficient Cannot Predict Histopathological Features and Response to Neoadjuvant Radiochemotherapy in Rectal Cancer: A Meta-Analysis.

Authors:  Alexey Surov; Maciej Pech; Maciej Powerski; Katja Woidacki; Andreas Wienke
Journal:  Dig Dis       Date:  2021-03-04       Impact factor: 2.404

7.  Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.

Authors:  Colleen Bailey; Bernard Siow; Eleftheria Panagiotaki; John H Hipwell; Thomy Mertzanidou; Julie Owen; Patrycja Gazinska; Sarah E Pinder; Daniel C Alexander; David J Hawkes
Journal:  NMR Biomed       Date:  2016-12-21       Impact factor: 4.044

8.  Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers.

Authors:  Ken Yamaguchi; Takahiko Nakazono; Ryoko Egashira; Yoshiaki Komori; Jun Nakamura; Tomoyuki Noguchi; Hiroyuki Irie
Journal:  Magn Reson Med Sci       Date:  2016-11-16       Impact factor: 2.471

9.  Can diffusion-weighted imaging add information in the evaluation of breast lesions considered suspicious on magnetic resonance imaging?

Authors:  Camila Souza Guatelli; Almir Galvão Vieira Bitencourt; Cynthia Aparecida Bueno de Toledo Osório; Luciana Graziano; Alessandra Araújo de Castro; Juliana Alves de Souza; Elvira Ferreira Marques; Rubens Chojniak
Journal:  Radiol Bras       Date:  2017 Sep-Oct

Review 10.  Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer.

Authors:  Apekshya Chhetri; Xin Li; Joseph V Rispoli
Journal:  Front Med (Lausanne)       Date:  2020-05-12
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.