Literature DB >> 24305976

Does shear wave ultrasound independently predict axillary lymph node metastasis in women with invasive breast cancer?

Andrew Evans1, Petra Rauchhaus, Patsy Whelehan, Kim Thomson, Colin A Purdie, Lee B Jordan, Caroline O Michie, Alastair Thompson, Sarah Vinnicombe.   

Abstract

Shear wave elastography (SWE) shows promise as an adjunct to greyscale ultrasound examination in assessing breast masses. In breast cancer, higher lesion stiffness on SWE has been shown to be associated with features of poor prognosis. The purpose of this study was to assess whether lesion stiffness at SWE is an independent predictor of lymph node involvement. Patients with invasive breast cancer treated by primary surgery, who had undergone SWE examination were eligible. Data were retrospectively analysed from 396 consecutive patients. The mean stiffness values were obtained using the Aixplorer® ultrasound machine from SuperSonic Imagine Ltd. Measurements were taken from a region of interest positioned over the stiffest part of the abnormality. The average of the mean stiffness value obtained from each of two orthogonal image planes was used for analysis. Associations between lymph node involvement and mean lesion stiffness, invasive cancer size, histologic grade, tumour type, ER expression, HER-2 status and vascular invasion were assessed using univariate and multivariate logistic regression. At univariate analysis, invasive size, histologic grade, HER-2 status, vascular invasion, tumour type and mean stiffness were significantly associated with nodal involvement. Nodal involvement rates ranged from 7 % for tumours with mean stiffness <50 kPa to 41 % for tumours with a mean stiffness of >150 kPa. At multivariate analysis, invasive size, tumour type, vascular invasion, and mean stiffness maintained independent significance. Mean stiffness at SWE is an independent predictor of lymph node metastasis and thus can confer prognostic information additional to that provided by conventional preoperative tumour assessment and staging.

Entities:  

Mesh:

Year:  2013        PMID: 24305976      PMCID: PMC4363519          DOI: 10.1007/s10549-013-2747-z

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


Introduction

Several large studies have shown that the addition of shear wave elastography (SWE) to greyscale ultrasound improves the performance of ultrasound examination in differentiating benign from malignant breast masses [1-3]. SWE is quantitative and highly reproducible, in contrast to static elastography [3-6]. The combination of SWE and greyscale ultrasound has been shown to be highly sensitive; that is, if both are negative, malignancy is extremely unlikely (no false-negative cases in a series of 111 published in 2012) [3]. It is therefore likely that SWE will be increasingly used in routine clinical practise. It has been shown that large invasive size, high histological grade and vascular invasion are independently associated with increased stiffness at SWE [7, 8]. These studies did not show lesion stiffness to be an independent predictor of nodal status but given the relatively small numbers, they may have been underpowered for this outcome. Lymph node status is the most powerful prognostic indicator in breast cancer [9] and knowledge of lymph node status influences both surgical management and the use of systemic therapy (adjuvant and neoadjuvant). More accurate identification of likely lymph node metastases at diagnosis could minimise the need for a subsequent surgical procedure to clear the axilla following initial surgery and sentinel node biopsy. A second operation carries costs and risks, in addition to an inevitable delay in time to initiation of adjuvant chemotherapy, which should be given in a timely fashion to optimise long-term patient outcome [10]. The aim of this study was to determine, in a large series of patients with primary invasive breast cancer treated initially by surgery, whether SWE findings could independently predict lymph node status when taking known predictors of nodal status such as invasive size, histological grade and vascular invasion status [11, 12] into account. If SWE finding are predictive of lymph node involvement this may be clinically useful in selecting patients for neo-adjuvant chemotherapy (NACT), as the established predictors of nodal involvement are only definitively available post operatively, and ultrasound guided percutaneous biopsy of nodes with abnormal ultrasound morphology only establishes a diagnosis of nodal metastases in around 50 % of cases shown to be positive at surgery [13].

Patients and methods

SWE has been part of routine breast ultrasound examinations at our institution since November 2009. In accordance with the applicable UK National Research Ethics Service guidance [14], ethical approval for the study was not required. Consecutive patients with invasive breast cancer identified during ultrasound scans using the Aixplorer® ultrasound system (SuperSonic Imagine, Aix en Provence, France) between 19/04/2010 and 12/12/2012 and treated by primary surgery were included in this study. The sample included women with symptoms and women with screen-detected abnormalities. All women were scanned and biopsied by one of three breast radiologists or an advanced radiography practitioner trained to perform and interpret breast ultrasonography. These practitioners had between 5 and 20 years of breast ultrasound experience and had at least 3 months experience of performing SWE of solid breast lesions. Greyscale and elastography images were obtained during the standard ultrasound appointment. The elastography colour map findings were taken into account in the diagnostic management of the patients but the quantitative measurements were produced and analysed later to minimise impact on workflow. The elasticity values were obtained by moving a delineated region of interest (ROI) over the colour map. As the ROI moves, the readings change in real time so the ROI can be positioned over the part of the image showing the stiffest tissue. Four elastography images—in each of two orthogonal planes—were taken of each lesion. The transducer was held still over the lesion for about 10 s to allow the shear wave image to build up. If the patient was breathing heavily, she was asked to hold her breath during acquisition. Mean ROI stiffness values (kPa) from the four images were used for analysis. Analysis was based on histological data points from pathological examination of the resected specimen: histological grade, tumour type, invasive size, vascular invasion, ER, HER-2 status and lymph node stage. These were assessed according to UK national guidelines [15, 16]. Macro-metastases were counted as node positive while micro-metastases and isolated tumour cells were counted as node negative. Univariate and multivariate logistic regression were used to establish the significance of associations of histological and shear wave findings with lymph node status.

Results

The sample comprised 396 patients; 217 presented with symptoms, whereas 179 had cancers detected by mammographic screening. The patients’ ages ranged from 31 to 92 years with a median of 62 years. The histological characteristics of the study group are shown in Table 1. The median invasive tumour size was 19 mm, 28 % of patients had lymph node metastases and 27 % had vascular invasion. The tumour stiffness values according to nodal status are shown in Table 2. Nodal status according to range of mean stiffness values is shown in Table 3. Nodal metastasis rates ranged from 7 % for tumours with mean stiffness <50 kPa to 41 % for tumours with a mean stiffness of >150 kPa.
Table 1

Histological features of the 396 invasive cancers in the study group

Histological featureNumber (%)
Grade 155 (14)
Grade 2167 (42)
Grade 3174 (44)
Node positive112 (28)
Vascular invasion105 (27)
HER 2 positivea 36 (9)
ER positive330 (83)
PR positive271 (68)
Invasive size <15 mm131 (33)

a6 patients had unknown HER 2 status

Table 2

Mean stiffness (kPa) values of 396 breast cancers by nodal status

Range of mean stiffness values (kPa)Mean of mean stiffness values (kPa)Median of mean stiffness values (kPa)
Node negative (n = 284)14–281114105
1–3 nodes positive (n = 78)31–281141130
4 or more nodes positive (n = 34)77–265156149
Table 3

Nodal status according to mean stiffness value (range)

Mean stiffness range (kPa)Node negative n (%)Node positive n (%)
<5027 (93)2 (7)
50–99101 (78)28 (22)
100–14983 (72)32 (28)
>15073 (59)50 (41)
Histological features of the 396 invasive cancers in the study group a6 patients had unknown HER 2 status Mean stiffness (kPa) values of 396 breast cancers by nodal status Nodal status according to mean stiffness value (range) At univariate analysis, invasive size, histological grade, HER-2 status, vascular invasion, tumour type and mean stiffness were significantly associated with nodal involvement while ER, PR and age were not (Table 4). At multivariate analysis, invasive size, tumour type, vascular invasion and mean stiffness maintained independent significance in predicting nodal involvement while ER, PR, HER-2, age and histological grade did not (Table 5).
Table 4

Univariate logistic regression

Dependent parameterIndependent parameter p value
Nodal Involvement (yes/no)Age (years)0.6083
ER (binary)0.1739
HER2 status0.0408
Invasive size (mm)<0.0001
PR (binary)0.0930
Stiffness reading<0.0001
Tumour grade<0.0001
Tumour type (classified)0.0020
Vascular invasion<0.0001
Table 5

Multivariate logistic regression

Dependent parameterIndependent parameter p value
Nodal involvement (yes/no)Age (years)0.7655
ER (binary)0.4626
HER2 status0.4570
Invasive size (mm)<0.0001
PR (binary)0.3698
Stiffness reading0.0350
Tumour grade0.6300
Tumour type (classified)0.0104
Vascular invasion0.0027
Univariate logistic regression Multivariate logistic regression

Discussion

We have found that mean stiffness as measured by SWE is an independent predictor for nodal involvement in breast cancer in addition to well-established predictors such as invasive size and vascular invasion status. In contrast to previous studies, [11, 12] histological grade was not an independent predictor of nodal involvement on multivariate analysis. This may be because stiffness on SWE is associated with histological grade [7, 8]. The stiff tissue associated with invasive breast cancer is usually seen at the periphery of the tumour, extending into the peri-tumoural stroma. Often, the tumour itself is less stiff than the surrounding stroma. Although not proven, it is likely that the stiffness represents abnormal tumour-associated collagen, which has been shown to exhibit increased collagen crosslinking and abnormal alignment. These collagen abnormalities have recently been shown to have independent prognostic significance [17, 18]. In recent years, stromal gene signatures, and components such as Caveolin 1 and LOX 2, have been shown to be important prognostic and predictive indicators in breast cancer [19-22]. It is possible that the peri-tumoural stromal stiffness represents an imaging surrogate for some of these stromal processes. As these stromal prognostic indicators are not measured by the conventional predictors of nodal involvement, such as invasive size and histological grade, it is not surprising that stromal stiffness has independent predictive significance. Vascular invasion, another well-established predictive factor for axillary lymph node metastasis in breast cancer, has been shown to have a strong relationship with stromal stiffness on SWE [7, 8]. Like SWE stiffness, vascular invasion is also most commonly seen at the tumour–stromal interface [23]. The independence of vascular invasion and stromal stiffness as predictors of nodal metastasis suggests that the predictive power of stromal stiffness is mediated by other factors in addition to vascular invasion. Previous SWE studies have found that increased stiffness is associated with nodal metastases on univariate analysis [7, 8]. However, these studies did not show SWE stiffness to be an independent predictor of lymph node metastasis on multivariate analysis. This difference in findings compared to the current study may reflect insufficient statistical power resulting from the lower participant numbers (166 and 100, compared to 396 in this study). The larger of the previous studies took only one shear wave measurement from each tumour while the current study took four, further increasing the statistical power of our study. The main weakness of the current study is that it is from a single centre with a special interest in SWE. We do not know whether such results are reproducible in other clinical centres. Although the analysis was retrospective, the SWE data were acquired prospectively as part of our routine clinical practise, and recorded before core biopsy results or surgical pathology were known. In current practise, ultrasound guided needle biopsy of axillary lymph nodes with abnormal cortical morphology allows pre-operative diagnosis of axillary metastases in only around 50 % of women [13]. Preoperative diagnosis of nodal metastases is valuable as, when added to tumour size estimation on imaging and histological grading on core biopsy, it refines preoperative prognostication [24, 25]. This can facilitate the use of NACT to down-stage tumours prior to surgery, or to identify more accurately at diagnosis the most appropriate axillary surgery for patients following NACT. There remains some debate regarding the optimal timing of sentinel lymph node biopsy (SLNB) in patients receiving NACT [26], and the false negative rate of SLNB after neoadjuvant chemotherapy may be higher than would be deemed acceptable [27]; consequently, any tool to help facilitate more accurate staging of the axilla at diagnosis would be valuable. Our findings suggest that SWE has the potential to refine preoperative prognostication, and thus help improve decision making with regard to neo-adjuvant chemotherapy and management of the axilla. In conclusion, mean stiffness at SWE is an independent predictor of lymph node metastasis in women with invasive breast cancer and thus can contribute additional, non-invasive prognostic information compared to conventional preoperative tumour assessment and staging.
  23 in total

1.  Differentiating benign from malignant solid breast masses with US strain imaging.

Authors:  Elizabeth S Burnside; Timothy J Hall; Amy M Sommer; Gina K Hesley; Gale A Sisney; William E Svensson; Jason P Fine; Jinfeng Jiang; Nicholas J Hangiandreou
Journal:  Radiology       Date:  2007-11       Impact factor: 11.105

2.  HER2 assessment on core biopsy specimens using monoclonal antibody CB11 accurately determines HER2 status in breast carcinoma.

Authors:  Colin A Purdie; Lee B Jordan; Jean B McCullough; Sharon L Edwards; Joan Cunningham; Miriam Walsh; Andrew Grant; Norman Pratt; Alastair M Thompson
Journal:  Histopathology       Date:  2010-05       Impact factor: 5.087

3.  Aligned collagen is a prognostic signature for survival in human breast carcinoma.

Authors:  Matthew W Conklin; Jens C Eickhoff; Kristin M Riching; Carolyn A Pehlke; Kevin W Eliceiri; Paolo P Provenzano; Andreas Friedl; Patricia J Keely
Journal:  Am J Pathol       Date:  2011-03       Impact factor: 4.307

Review 4.  Prognostic factors in breast cancer. College of American Pathologists Consensus Statement 1999.

Authors:  P L Fitzgibbons; D L Page; D Weaver; A D Thor; D C Allred; G M Clark; S G Ruby; F O'Malley; J F Simpson; J L Connolly; D F Hayes; S B Edge; A Lichter; S J Schnitt
Journal:  Arch Pathol Lab Med       Date:  2000-07       Impact factor: 5.534

5.  Shear-wave elastography of invasive breast cancer: correlation between quantitative mean elasticity value and immunohistochemical profile.

Authors:  Ji Hyun Youk; Hye Mi Gweon; Eun Ju Son; Jeong-Ah Kim; Joon Jeong
Journal:  Breast Cancer Res Treat       Date:  2013-01-17       Impact factor: 4.872

6.  Matrix crosslinking forces tumor progression by enhancing integrin signaling.

Authors:  Kandice R Levental; Hongmei Yu; Laura Kass; Johnathon N Lakins; Mikala Egeblad; Janine T Erler; Sheri F T Fong; Katalin Csiszar; Amato Giaccia; Wolfgang Weninger; Mitsuo Yamauchi; David L Gasser; Valerie M Weaver
Journal:  Cell       Date:  2009-11-25       Impact factor: 41.582

7.  Doctor, what are my chances of having a positive sentinel node? A validated nomogram for risk estimation.

Authors:  José Luiz B Bevilacqua; Michael W Kattan; Jane V Fey; Hiram S Cody; Patrick I Borgen; Kimberly J Van Zee
Journal:  J Clin Oncol       Date:  2007-07-30       Impact factor: 44.544

8.  A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer.

Authors:  Pierre Farmer; Hervé Bonnefoi; Pascale Anderle; David Cameron; Pratyaksha Wirapati; Pratyakasha Wirapati; Véronique Becette; Sylvie André; Martine Piccart; Mario Campone; Etienne Brain; Gaëtan Macgrogan; Thierry Petit; Jacek Jassem; Frédéric Bibeau; Emmanuel Blot; Jan Bogaerts; Michel Aguet; Jonas Bergh; Richard Iggo; Mauro Delorenzi
Journal:  Nat Med       Date:  2009-01-04       Impact factor: 53.440

9.  An absence of stromal caveolin-1 expression predicts early tumor recurrence and poor clinical outcome in human breast cancers.

Authors:  Agnieszka K Witkiewicz; Abhijit Dasgupta; Federica Sotgia; Isabelle Mercier; Richard G Pestell; Michael Sabel; Celina G Kleer; Jonathan R Brody; Michael P Lisanti
Journal:  Am J Pathol       Date:  2009-05-01       Impact factor: 4.307

10.  Histological grading of breast cancer on needle core biopsy: the role of immunohistochemical assessment of proliferation.

Authors:  T'ng Chang Kwok; Emad A Rakha; Andrew H S Lee; Matthew Grainge; Andrew R Green; Ian O Ellis; Desmond G Powe
Journal:  Histopathology       Date:  2010-08       Impact factor: 5.087

View more
  28 in total

1.  Feasibility of Shear Wave Elastography Imaging for Evaluating the Biological Behavior of Breast Cancer.

Authors:  Chaoxu Liu; Jin Zhou; Cai Chang; Wenxiang Zhi
Journal:  Front Oncol       Date:  2022-01-27       Impact factor: 6.244

2.  Effectiveness of Quantitative Shear Wave Elastography for the Prediction of Axillary Lymph Node Metastasis.

Authors:  Yingying Cheng; Guofu Li; Hui Jing; Shasha Yuan; Lei Zhang; Wen Cheng
Journal:  Evid Based Complement Alternat Med       Date:  2022-06-28       Impact factor: 2.650

3.  Tumor stiffness measured by quantitative and qualitative shear wave elastography of breast cancer.

Authors:  Eun Jee Song; Yu-Mee Sohn; Mirinae Seo
Journal:  Br J Radiol       Date:  2018-04-09       Impact factor: 3.039

4.  Comparison of strain and shear-wave ultrasounic elastography in predicting the pathological response to neoadjuvant chemotherapy in breast cancers.

Authors:  Yan Ma; Shuo Zhang; Jing Li; Jianyi Li; Ye Kang; Weidong Ren
Journal:  Eur Radiol       Date:  2016-10-17       Impact factor: 5.315

5.  Mapping Mechanical Properties of the Tumor Microenvironment by Laser Speckle Rheological Microscopy.

Authors:  Zeinab Hajjarian; Elena F Brachtel; Diane M Tshikudi; Seemantini K Nadkarni
Journal:  Cancer Res       Date:  2021-09-15       Impact factor: 12.701

6.  Prediction of Invasive Breast Cancer Using Mass Characteristic Frequency and Elasticity in Correlation with Prognostic Histologic Features and Immunohistochemical Biomarkers.

Authors:  Juanjuan Gu; Eric C Polley; Judy C Boughey; Robert T Fazzio; Mostafa Fatemi; Azra Alizad
Journal:  Ultrasound Med Biol       Date:  2021-05-14       Impact factor: 3.694

7.  Quantitative shear wave elastography in primary invasive breast cancers, based on collagen-S100A4 pathology, indicates axillary lymph node metastasis.

Authors:  Xin Wen; Xiwen Yu; Yuhang Tian; Zhao Liu; Wen Cheng; Hairu Li; Jia Kang; Tianci Wei; Shasha Yuan; Jiawei Tian
Journal:  Quant Imaging Med Surg       Date:  2020-03

8.  TGF-β1: is it related to the stiffness of breast lesions and can it predict axillary lymph node metastasis?

Authors:  Meng Ke Zhang; Qiu Jing Shang; Shi Yu Li; Bo Wang; Gang Liu; Zhi Li Wang
Journal:  Ann Transl Med       Date:  2021-05

9.  Lymphangiogenesis in Breast Cancer Correlates with Matrix Stiffness on Shear-Wave Elastography.

Authors:  Yoon Jin Cha; Ji Hyun Youk; Baek Gil Kim; Woo Hee Jung; Nam Hoon Cho
Journal:  Yonsei Med J       Date:  2016-05       Impact factor: 2.759

10.  Associations Between Elastography Findings and Clinicopathological Factors in Breast Cancer.

Authors:  Mitsuhiro Hayashi; Yutaka Yamamoto; Aiko Sueta; Mai Tomiguchi; Mutsuko Yamamoto-Ibusuki; Teru Kawasoe; Akinobu Hamada; Hirotaka Iwase
Journal:  Medicine (Baltimore)       Date:  2015-12       Impact factor: 1.817

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.