The Breast Tumor Strain Ratio Is a Predictive Parameter for Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer

Kim, Jin Joo; Shin, Jong Ki; Lee, Suck Hong

doi:10.2214/ajr.14.14269

Cited by 24 publications

(13 citation statements)

References 27 publications

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“…Several studies reported SUVmax on 18 F-FDG PET/CT or breast tumor strain ratio on ultrasound elastography as imaging biomarker for ALNM. [ 8 , 9 ] Higher SUVmax (≥4.25) was independent predictor for ALNM especially in ER-positive/HER2-negative and HER2-positive subtypes but not in triple negative subtype. [ 9 ] In this study, we measured not only SUVmax but also SUVmean, MTV, and TLG.…”

Section: Discussionmentioning

confidence: 99%

“…As an imaging biomarker, the breast tumor strain ratio on ultrasound elastography has been reported to be an independent predictor for ALNM in patients with invasive breast cancer. [ 8 ] The strain ratio was significantly higher in tumors with ALNM than in those without ALNM. The strain ratio was independent predictor for ALNM along with lymphovascular invasion and higher expression of Ki-67 (>14%) on multivariate analysis.…”

Section: Introductionmentioning

confidence: 99%

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Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis

Kang²,

Jung³

et al. 2017

Medicine

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The purpose of our study was to evaluate the association between metabolic parameters on FDG PET/CT and axillary lymph node metastasis (ALNM) in patients with invasive breast cancer.From January 2012 to December 2012, we analyzed 173 patients with invasive ductal carcinoma (IDC) who underwent both initial breast magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) examinations. All metabolic parameters were measured from the tumor volume segmented by a gradient-based method. Once the primary target lesion was segmented, maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated automatically by the MIMvista software.Mean age of 173 patients was 49 years. Of 173 patients, 45 (26%) showed ALNM. On univariate analysis, larger tumor size (>2.2 cm; P = .002), presence of lymphovascular invasion (P < .001), higher SUVmax (>2.82; P = .038), higher SUVmean (>1.2; P = .027), higher MTV (>2.38; P < .001), and higher TLG (>3.98; P = .007) were associated with a higher probability of ALNM. On multivariate analysis, presence of lymphovascular invasion (adjusted odds ratio [OR], 11.053; 95% CI, 4.403–27.751; P < .001) and higher MTV (>2.38) (adjusted OR, 2.696; 95% CI, 1.079–6.739; P = .034) maintained independent significance in predicting ALNM. In subgroup analysis of T2/T3 breast cancer, lymphovascular invasion (adjusted OR, 20.976; 95% CI, 5.431–81.010; P < .001) and higher MTV (>2.38) (adjusted OR, 4.906; 95% CI, 1.616–14.896; P = .005) were independent predictors of ALNM. However in T1 breast cancer, lymphovascular invasion (adjusted OR, 16.096; 95% CI, 2.517–102.939; P = .003) and larger SUV mean (>1.2) (adjusted OR, 13.275; 95% CI, 1.233–142.908; P = .033) were independent predictors while MTV was not.MTV may be associated with ALNM in patients with invasive breast cancer, particularly T2 and T3 stages. In T1 breast cancer, SUVmean was associated with ALNM.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis

Kang²,

Jung³

et al. 2017

Medicine

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“…Recently, tissue stiffness reflected by conventional US strain elastography (SE), strain ratio on elastography, or virtual touch tissue quantification (VTQ) imaging has been found to be associated with LNM 32–35 . However, these techniques have several limitations.…”

Section: Discussionmentioning

confidence: 99%

A Risk Model based on Ultrasound, Ultrasound Elastography, and Histologic Parameters for Predicting Axillary Lymph Node Metastasis in Breast Invasive Ductal Carcinoma

et al. 2017

Sci Rep

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To develop a risk model for predicting axillary lymph node metastasis (LNM) in patients with breast invasive ductal carcinoma (IDCs) using ultrasound (US), US elastography of virtual touch tissue imaging (VTI) and virtual touch tissue imaging & quantification (VTIQ), and histologic parameters. This study included 162 breast IDCs in 162 patients. Univariate and multivariate analyses were used to identify the risk factors and a risk model was created. The results found that 64 (39.5%) of 162 patients had axillary LNMs. The risk score (RS) for axillary LNM was defined as following: RS = 1.3 × (if lesion size ≥20 mm) + 2.6 × (if taller than wide shape) + 2.2 × (if VTI score ≥5) + 3.9 × (if histological grade III) + 1.9 × (if positive C-erbB-2). The rating system was divided into 6 stages (i.e. Stage I, Stage II, Stage III, Stage IV, Stage V, and Stage VI) and the associated risk rates in terms of axillary LNM were 0% (0/19), 6.1% (2/33), 7.7% (3/39), 65.5% (19/29), 92.3% (24/26), and 100% (16/16), respectively. The risk model for axillary LNM established in the study may facilitate subsequent treatment planning and management in patients with breast IDCs.

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“… 145 A high ratio of lymphovascular invasion and high expression of Ki67 are independently predictive of ALD metastases. 146 Another potential biomarker, cytoplasmic chromosome segregation 1 Like is significantly associated with ALD metastases although it appears to have no regulatory effects on ALD metastases. 147 …”

Section: Lymph-node Metastasismentioning

confidence: 99%

Organotropism: new insights into molecular mechanisms of breast cancer metastasis

et al. 2018

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Metastasis accounts for 90% of breast cancer mortality. Despite the significant progress made over the past decade in cancer medicine our understanding of metastasis remains limited, therefore preventing and targeting metastasis is not yet possible. Breast cancer cells preferentially metastasize to specific organs, known as “organotropic metastasis”, which is regulated by subtypes of breast cancer, host organ microenvironment, and cancer cells-organ interactions. The cross-talk between cancer cells and host organs facilitates the formation of the premetastatic niche and is augmented by factors released from cancer cells prior to the cancer cells’ arrival at the host organ. Moreover, host microenvironment and specific organ structure influence metastatic niche formation and interactions between cancer cells and local resident cells, regulating the survival of cancer cells and formation of metastatic lesions. Understanding the molecular mechanisms of organotropic metastasis is essential for biomarker-based prediction and prognosis, development of innovative therapeutic strategy, and eventual improvement of patient outcomes. In this review, we summarize the molecular mechanisms of breast cancer organotropic metastasis by focusing on tumor cell molecular alterations, stemness features, and cross-talk with the host environment. In addition, we also update some new progresses on our understanding about genetic and epigenetic alterations, exosomes, microRNAs, circulating tumor cells and immune response in breast cancer organotropic metastasis.

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The Breast Tumor Strain Ratio Is a Predictive Parameter for Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer

Abstract: The breast tumor strain ratio on ultrasound elastography is associated independently with axillary lymph node metastasis in patients with invasive breast cancer.

Cited by 24 publications

References 27 publications

Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis

Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis

A Risk Model based on Ultrasound, Ultrasound Elastography, and Histologic Parameters for Predicting Axillary Lymph Node Metastasis in Breast Invasive Ductal Carcinoma

Organotropism: new insights into molecular mechanisms of breast cancer metastasis

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