• 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • 2021-03
  • br Montagna E Bagnardi V Viale G


    18. Montagna E, Bagnardi V, Viale G, et al. Changes in PgR and Ki-67 in residual tumour and outcome of breast cancer patients treated with neo-adjuvant chemotherapy. Ann Oncol 2015; 26:307–313.
    19. Luo N, Su D, Jin G, et al. Apparent Puromycin coefficient ratio between axillary lymph node with primary tumor to detect nodal metastasis in breast cancer patients. J Magn Reson Imaging 2013; 38:824–828. 
    21. Shin JK, Kim JY. Dynamic contrast-enhanced and diffusion-weighted MRI of estrogen receptor-positive invasive breast cancers: associations between quantitative MR parameters and Ki-67 proliferation status. J Magn Reson Imaging 2017; 45:94–102.
    22. Nakashoji A, Matsui A, Nagayama A, et al. Clinical predictors of patho-logical complete response to neoadjuvant chemotherapy in triple-nega-tive breast cancer. Oncol Lett 2017; 14:4135–4141.
    23. Ma Y, Zhang S, Zang L, et al. Combination of shear wave elastography and Ki-67 index as a novel predictive modality for the pathological response to neoadjuvant chemotherapy in patients with invasive breast cancer. Eur J Cancer 2016; 69:86–101.
    24. Horimoto Y, Arakawa A, Tanabe M, et al. Ki67 expression and the effect of neo-adjuvant chemotherapy on luminal HER2-negative breast cancer. BMC Cancer 2014; 14:550.
    25. Tokuda E, Horimoto Y, Arakawa A, et al. Differences in Ki67 expres-sions between pre- and post-neoadjuvant chemotherapy specimens might predict early recurrence of breast cancer. Hum Pathol 2017; 63:40–45.
    26. Le BD, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161:401–407.
    28. Martincich L, Deantoni V, Bertotto I, et al. Correlations between diffu-sion-weighted imaging and breast cancer biomarkers. Eur Radiol 2012; 22:1519–1528.
    29. Jeh SK, Kim SH, Kim HS, et al. Correlation of the apparent diffusion coefficient value and dynamic magnetic resonance imaging findings with prognostic factors in invasive ductal carcinoma. J Magn Reson Imaging 2011; 33:102–109.
    30. Suo S, Cheng F, Cao M, et al. Multiparametric diffusion-weighted imag-ing in breast lesions: association with pathologic diagnosis and prognos-tic factors. J Magn Reson Imaging 2017; 46:740–750.
    Contents lists available at ScienceDirect
    Physics and Imaging in Radiation Oncology
    journal homepage:
    Original Research Article
    Changes in apparent diffusion coefficient radiomics features during dose- T painted radiotherapy and high dose rate brachytherapy for prostate cancer
    Sangjune Laurence Leea,b, Jenny Leea,b, Tim Craiga,b, Alejandro Berlina,b, Peter Chunga,b, Cynthia Ménarda,b,c, Warren D. Foltza,b, a Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada b Department of Radiation Oncology, University of Toronto, Toronto, Canada c Centre de Recherche du Centre Hospitalier de l Université de Montréal (CRCHUM), Montréal, Canada
    Diffusion-weighted MRI
    Apparent diffusion coefficient
    Prostate cancer
    Dose-painted radiotherapy
    High dose rate brachytherapy 
    Background and purpose: Dose escalation has improved cancer outcomes for patients with localized prostate cancer. Targeting subprostatic tumor regions for dose intensification may further improve outcomes. Apparent Diffusion Coefficient (ADC) maps may enable early radiation response assessment and dose adaptation. This study was a proof-of-principle investigation of early changes in ADC radiomics features for patients undergoing radiotherapy with dose escalation to the gross tumor volume (GTV).
    Materials and methods: Fifty-nine patients were enrolled on a prospective tumor dose-escalation trial. Multi-parametric MRI was performed at baseline and week six, corresponding to the time of peak ADC change. GTV and prostate contours were deformably registered between baseline and week six T2-weighted images, and applied to ADC maps, to account for diminished image contrast post-EBRT and possible differences in prostate gland volume, shape, and orientation. A total of 101 radiomics features were tested for significant change post-EBRT using two-tailed Student’s t-test. All ADC features of the prostate and GTV volumes were correlated using Pearson’s coefficient (p < 0.00008, based on Bonferroni correction).
    Results: ADC feature extraction was insensitive to b = 0 s/mm2 exclusion, and to gradient non-linearity bias. GTV presented predominant changes in first-order features, particularly 10Percentile, and prostate volumes presented predominant changes in second-order features. Changes in both first and second-order features of GTV and prostate ROIs were strongly correlated. Conclusions: Our data confirmed significant changes in numerous GTV and prostate features assessed from ADC and T2-weighted images during radiotherapy; all of which may be potential biomarkers of early radiation re-sponse.