2018
DOI: 10.1371/journal.pone.0195756
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Preoperative dynamic breast magnetic resonance imaging kinetic features using computer-aided diagnosis: Association with survival outcome and tumor aggressiveness in patients with invasive breast cancer

Abstract: ObjectivesTo evaluate whether preoperative breast dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging kinetic features, assessed using computer-aided diagnosis (CAD), can predict survival outcome and tumor aggressiveness in patients with invasive breast cancer.Materials and methodsBetween March and December 2011, 301 women who underwent preoperative DCE MR imaging for invasive breast cancer, with CAD data, were identified. All MR images were retrospectively evaluated using a commercially available … Show more

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Cited by 21 publications
(16 citation statements)
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“…Among the kinetic parameters, peak enhancement is known to reflect contrast concentrations both in intra-and extravascular interstitial spaces [36]. Nam et al have reported that higher peak enhancement is associated with poorer disease-free survival rates and greater tumor aggressiveness [37]. We speculate that these prior results might explain the relationship between a peak enhancement and histologic upgrade of a DCIS.…”
Section: Discussionmentioning
confidence: 70%
“…Among the kinetic parameters, peak enhancement is known to reflect contrast concentrations both in intra-and extravascular interstitial spaces [36]. Nam et al have reported that higher peak enhancement is associated with poorer disease-free survival rates and greater tumor aggressiveness [37]. We speculate that these prior results might explain the relationship between a peak enhancement and histologic upgrade of a DCIS.…”
Section: Discussionmentioning
confidence: 70%
“…Prior studies have shown that early peak enhancement and delayed washout pattern at MRI are the most important prognostic indicators for both malignancy and more aggressive nature of tumors (1,4,8,9). Kim and colleagues add another potential value of these two DCE MRI parameters, offering greater potential in predicting distant metastasis-free survival at initial staging.…”
Section: Riham H El Khouli MD Phd • Michael a Jacobs Phdmentioning
confidence: 99%
“…Recently, research regarding convolutional neural networks (CNNs) for CAD has expanded to include chest X-rays, computed tomography (CT), and high-resolution CT (HR-CT) [3]. Furthermore, several studies have investigated the application of CAD based on magnetic resonance imaging (MRI) and functional MRI, as well as ultrasound images, infrared thermography, electroencephalography (EEG), digital histopathology, and endoscopy photographs [4,5,6,7]. Previous research has demonstrated that CAD is useful for diagnosing [8] and characterizing patterns [9] of tuberculosis, with decent diagnostic accuracy.…”
Section: Introductionmentioning
confidence: 99%