|Year : 2022 | Volume
| Issue : 3 | Page : 345-353
Accuracy of digital mammography, ultrasound and MRI in predicting the pathological complete response and residual tumor size of breast cancer after completion of neoadjuvant chemotherapy
Rashmi Sudhir1, Veeraiah Chaudhary Koppula1, T Subramanyeshwar Rao2, Kamala Sannapareddy1, Senthil J Rajappa3, Sudha S Murthy4
1 Department of Radiodiagnosis, Basavatarakam Indo-American Cancer Hospital and Research Centre, Hyderabad, Telangana, India
2 Department of Surgical Oncology, Basavatarakam Indo-American Cancer Hospital and Research Centre, Hyderabad, Telangana, India
3 Department of Medical Oncology, Basavatarakam Indo-American Cancer Hospital and Research Centre, Hyderabad, Telangana, India
4 Department of Pathology and Lab Medicine, Basavatarakam Indo-American Cancer Hospital and Research Centre, Hyderabad, Telangana, India
|Date of Submission||08-Sep-2019|
|Date of Decision||26-Oct-2019|
|Date of Acceptance||27-Mar-2020|
|Date of Web Publication||27-Jan-2021|
Department of Radiodiagnosis, Basavatarakam Indo-American Cancer Hospital and Research Centre, Hyderabad, Telangana
Source of Support: None, Conflict of Interest: None
Background: Neoadjuvant chemotherapy (NACT) is the standard of care for the treatment of locally advanced or non-metastatic breast cancer, which may increase the chances of breast conservative surgery (BCS) in place of radical mastectomy without compromising on the overall survival. The aim of this study was to evaluate the accuracy of mammography (MG), ultrasound (US), and magnetic resonance imaging (MRI) in predicting the complete response and to assess the extent of residual breast cancer in women treated with NACT.
Materials and Methods: Fifty-six consecutive patients with stage II or III breast cancer, who underwent imaging evaluation of breast with digital mammogram, US, and MRI after NACT and before the breast surgery, were included in the study. For each patient, pathologic complete response (pCR) or residual tumor (non-pCR) was predicted and the maximum extent of the residual tumor was measured on each imaging modality. These measurements were subsequently compared with the final histopathology results.
Results: Of 56 patients, 22 showed pCR with MRI having better accuracy for predicting complete response than the MG and US (area under the receiver operating characteristic curve: 0.86, 0.68, and 0.65, respectively; p = 0.0001 for MRI; p = 0.06 for MG, and p = 0.02 for US). The sensitivity of MRI for detecting pCR was 72.7%; specificity and positive predictive value were 100%. For pathological residual tumor, the size measured on MRI showed significantly higher correlation with the pathologic size (correlation coefficient, r = 0.786), than the MG (r = 0.293) and US (r = 0.508) with P < 0.05.
Conclusions: Accuracy of MRI for predicting pathological complete response was significantly higher than the MG and US. Pathologic residual tumor size was also more precisely reflected by the longest tumor dimension on MRI with the strong positive correlation coefficient.
Keywords: Breast cancer imaging, magnetic resonance imaging, neoadjuvant chemotherapy, pathological complete response, residual tumour
Key Message Compared to digital mammography and ultrasound of breast, contrast-enhanced magnetic resonance imaging has the highest accuracy for predicting the post-neoadjuvant chemotherapy pathological complete response and residual tumor size among Indian women.
|How to cite this article:|
Sudhir R, Koppula VC, Rao T S, Sannapareddy K, Rajappa SJ, Murthy SS. Accuracy of digital mammography, ultrasound and MRI in predicting the pathological complete response and residual tumor size of breast cancer after completion of neoadjuvant chemotherapy. Indian J Cancer 2022;59:345-53
|How to cite this URL:|
Sudhir R, Koppula VC, Rao T S, Sannapareddy K, Rajappa SJ, Murthy SS. Accuracy of digital mammography, ultrasound and MRI in predicting the pathological complete response and residual tumor size of breast cancer after completion of neoadjuvant chemotherapy. Indian J Cancer [serial online] 2022 [cited 2022 Dec 7];59:345-53. Available from: https://www.indianjcancer.com/text.asp?2022/59/3/345/308054
| » Introduction|| |
Neoadjuvant chemotherapy (NACT) is a systemic therapy administered to the patient preoperatively to downstage the primary tumor. NACT is the standard of care for the treatment of locally advanced or nonmetastatic breast cancer, which may increase the chances of breast conservative surgery (BCS) in place of radical mastectomy without compromising the overall survival., Multiple randomized controlled trials have shown that patients who experienced pathological complete response after NACT had a significantly higher overall disease-free survival rate than the patients with residual tumors.,, Surgical excision of a residual primary tumor visible on preoperative imaging is considered the standard of care after NACT as the accuracy of clinical examination for response assessment is very low. Hence, preoperative imaging evaluation of breast after NACT is extremely important to detect residual cancer with high precision and to ensure that the patient undergoes appropriate type of surgery. Several clinical trials and meta-analyses have investigated the diagnostic efficacy of various imaging modalities (mammography (MG), ultrasound (US), and magnetic resonance imaging (MRI) after NACT and compared the accuracy of preoperative measurements with the final pathologic size of the tumor, however, there is no conclusion yet regarding the most reliable and accurate modality.,, Many of them have shown MRI to be highly sensitive but rather low specificity for identifying pathological complete response (pCR = ypT0N0). Breast parenchyma of Asian women is relatively denser than the Western population., To the best of our knowledge, there is no published literature from the Indian subcontinent to assess the accuracy of various imaging modalities in the evaluation of post-NACT breast cancer.
In this single-center prospective study, we calculated and compared the accuracy of digital MG, US, and contrast-enhanced MRI (CE-MRI) to predict the pCR and assess the residual tumor (non-pCR) extent of breast cancer after completion of NACT.
| » Materials and Methods|| |
This prospective study was conducted at a tertiary care cancer institute after approval obtained from the institutional ethics committee board. The study consisted of 56 consecutive women with stages II or III breast cancer who underwent image-guided diagnostic core biopsy, post biopsy clip placement within the mass, NACT, BCS or mastectomy after NACT, preoperative imaging (MG, US, and MRI of the breast) and final histopathology done at our center between March 2018 and June 2019. Patients who did not take adequate NACT (at least 4 cycles) and those who did not undergo surgery after the NACT at our center were excluded. NACT was administered according to the international guidelines. Informed consent was obtained from all participants.
Three experienced breast radiologists were involved in image interpretation of MG, US, and breast MRI. All readers independently interpreted the images and in case of doubt, a joint consensus was reached after second observation. Radiologists were blinded to the final histopathology report of the specimen.
Bilateral two views (CC and MLO) standard mammogram (MG) were obtained using the Senographe Digital Mammography scanner (GE Medical Systems, Milwaukee, WI, USA). The presence of any suspicious abnormality at or close to the clip, e.g., isodense or hyperdense mass with spiculated/irregular margins, architectural distortion, focal asymmetric density, microcalcification, or combination of these were considered to be a residual tumor on MG.
US of both the breasts was performed by one of the three radiologists on ACUSON s2000 Siemens Ultrasound System using high-frequency linear probe (18 MHz). The depth, frequency, and gain were optimized prior to the scanning. Any suspicious abnormality on the US at the site of prior tumor, e.g., hypoechogenicity with or without posterior shadowing or enhancement, architectural distortion and/or echogenic calcific foci were considered as the residual tumor. The longest diameter of the hypoechoic part was taken as the residual tumor size on ultrasound.
MRI scans were performed on 1.5T (Signa HDx, General Electric Medical System, Milwaukee, WI) with dedicated breast array coils with the patient in a prone position. All the scans were done 1-2 weeks after the completion of NACT and 2-4 weeks prior to the definitive surgery. MRI sequences for all patients were similar, which included T1W, T2W, and STIR in the axial plane, T2W, and STIR in coronal and sagittal planes, diffusion-weighted imaging (DWI) at b-value of 0 and 800 s/mm2. Precontrast T1W fat-saturated gradient-echo images were acquired followed by dynamic post-contrast T1W fat-saturated gradient-echo images in five phases over 6 minutes. Gadodiamide (Omniscan, 0.1 mmol per kilogram of body weight) was administered intravenously at the rate of 2 mL/sec, followed by 20 ml of saline flush. post-contrast images were initiated to be acquired after completion of the contrast injection. Post processing dynamic subtraction images were obtained by digital subtraction of precontrast T1W fat-saturated gradient-echo images from the post-contrast dynamic images. A maximum intensity projection (MIP) was obtained in all planes. The kinetic curve of the enhancing lesion was drawn and analyzed using the mean curve technique. Type I curve (progressive enhancement pattern), demonstrates persistent increase in signal intensity after contrast injection on each successive contrast-enhanced image, usually indicative of benign etiology. Type II curve (a plateau pattern), shows slow or rapid increase signal intensity in the initial phase followed by persistent same signal intensity in the delayed phase, suggestive of indeterminate or malignant lesion. Type III curve (a wash-out pattern), shows rapid increase signal intensity in the initial phase followed by signal drop-off in delayed phase, indicative of malignancy.
Interpretation of MRI was done by analyzing pre-contrast images, dynamic post-contrast images, kinetic curves, post-processed subtraction, and MIP images. On visual inspection, the presence of any amount of enhancing lesion noted around the clip in the subtraction images was considered as residual mass, and the longest diameter of the largest residual mass was used for comparison with the pathological size of the residual mass. The absence of contrast enhancement around the clip or no new enhancing lesion in the breast was defined as a complete response on MRI. The enhancing residual mass visible on the dynamic post-contrast images were further analyzed for the type of kinetic curve (I, II or III).
Data collection and statistical analysis
Data for every patient, clinical information (age, presence or absence of palpable lump or other symptoms) from the clinical case sheet, tumor size measurement on pre-NACT diagnostic MG and US using electronic calipers by the performing breast radiologists, the histopathological diagnosis of the tumor on core biopsy sample reported by breast pathologists, pre-NACT clinical-stage, the number of chemotherapy cycles administered to the patient prior to the definitive surgery, maximum tumor dimensions of the corresponding visualized malignancy on post-NACT and pre-operative MG, US, and breast-MRI measured separately on each modality, type of definitive surgery (breast conservative or mastectomy) done, time interval between the pre-operative imaging and definitive surgery, final histopathological diagnosis and receptor status (Estrogen Receptor (ER)/Progesterone Receptor (PR)//HER-2neu) on immunohistochemistry examination, pCR or non-pCR status, size of the pathologic residual tumor on final histopathology were collected from the digitally stored hospital information system.
Final histological tumor size was used as the gold standard for comparing the tumor measurements [mean ± standard deviation (SD)] on preoperative MG, US and MRI. Spearman's correlation coefficient (rho) was calculated to assess the strength of association between imaging tumor size and pathologic size and interclass correlation coefficient (ICC) graphs were plotted. Correlation coefficient value of more than 0.75 was considered a strong positive good association, between 0.5 to 0.75 moderate positive associations and less than 0.5 as a weak positive correlation. The receiver operating characteristic (ROC) curve was performed to assess the diagnostic performance of preoperative MG, US, and MRI on the entire study cohort for predicting pCR. For the ROC curve analysis, no residual tumor on imaging was taken positive variable and the presence of a residual tumor on imaging was taken as a negative variable with a pathological complete response as the reference standard. All the statistical analyses were performed using IBM SPSS version 20. A P value <0.05 was considered statistically significant.
| » Results|| |
Patient demographics, clinical, imaging, and pathologic summary of the breast cancer are summarized in [Table 1]. Fifty-six women between 26 and 67 years of age, with a median age of 44.5 years and interquartile range (IQR) 36-59 years were included. Twenty-six (46.4%) patients had BCS and 30 (53.6%) patients underwent mastectomy. The most common histological subtype was invasive ductal carcinoma (IDC) in 52 (94.6%) patients, with DCIS also noted in 12 (21.4%) patients. The time between imaging and surgery ranged from 15 to 28 days. Thirty-nine (69.4%) patients received 8 cycles of neoadjuvant chemotherapy (4 cycles of anthracycline-based followed by 4 cycles of docetaxel-based regimes) and 17 (30.6%) received only 4 cycles of anthracycline-based regime. On immunohistochemistry examination (IHC) for molecular subtyping, 13 (23.2%) were luminal A (LA) with hormone receptor (HR) positive and HER2- negative; 4 (7.1%) were luminal B (LB) with HR-positive and HER2-positive; 7 (12.5%) were HER2-enriched with HR-negative and HER2-positive and 32 (57.1%) were triple-negative with HR-negative and HER2-negative. The mean pathological residual tumor size was 8.2 ± 8.1 mm. The pathological complete response was identified in 22 out of 56 (39.3%) patients and residual disease in 34 (60.7%).
|Table 1: Patient demographics, clinical, imaging, and pathologic summary|
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Correlation between preoperative tumor size on imaging and pCR
Of the 22 patients with pCR, no residual disease was detected on preoperative MG in 15 (68.2%), on ultrasound in 8 (36.4%) and on CE-MRI in 16 (72.8%) patients. pCR was identified in 15 of 32 (46.9%) triple-negative breast cancers, 5 of 17 (29.4%) luminal A and luminal B cancers and 2 of 7 (28.6%) HER2-enriched cancers. In patients with pCR, a preoperative MG showed a residual lesion in 7 (31.8%) with mean longest diameter 17 mm (range 4-33 mm), the US in 14 (63.6%) with mean longest diameter 14 mm (range 7-23 mm), MRI in 6 (27.3%) patients with mean longest diameter 11.5 mm (range 3-30 mm) and all 6 patients on dynamic post-contrast MRI imaging demonstrated type 1 kinetic curve.
Area under the ROC curve (AUC) for MRI, US, and MG was 0.86, 0.68, and 0.65, respectively with P < 0.0001 for MRI, P = 0.02 for US and P = 0.06 for MG [Figure 1]. MRI showed the highest accuracy with a very good diagnostic performance for detecting pCR. The sensitivity of MRI for detecting pCR was 72.7%; specificity and positive predictive value were 100%.
|Figure 1: ROC curves to show the accuracy (AUC) of mammogram, ultrasound, and MRI for predicting pCR|
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Correlation between post-NACTresidual tumor size on imaging and final pathological size
The correlation between the post-NACT residual tumor size on imaging and final pathological size is summarized in [Table 2]. In this study, 34 patients showed residual disease (invasive carcinoma and/or ductal carcinoma in situ) on final histopathology (non pCR) with mean tumor size 8.19 ± 8.23 mm (range 3-25 mm). The mean longest diameter measured on preoperative MG, US and MRI were 11.21 ± 20.14 mm (range 0-132 mm); 12.60 ± 7.50 mm (range 0-33 mm) and 9.28 ± 8.83 mm (range 0-30 mm) respectively. Spearman's correlation coefficient between the predicted tumor size on preoperative imaging and postoperative final pathologic size was 0.786 for MRI, 0.508 for US, and 0.293 for MG [Figure 2]. MRI showed a strong positive correlation with the final pathologic size of all lesions (P < 0.05). Preoperative measurements on MG and US did not show a significant correlation with the final pathologic size.
|Table 2: Correlation between residual tumor size on imaging and final histopathologic size|
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|Figure 2: Scatter plots and Spearman's correlation coefficient (r) to show the correlation strength between the residual tumor size on imaging and pathology. (a) Correlation between the residual tumor size on mammogram and pathology with correlation coefficient (r) = 0.293. (b) Correlation between the residual tumor size on ultrasound and pathology with correlation coefficient (r) = 0.508. (c) Correlation between the residual tumor size on MRI and pathology with correlation coefficient (r) = 0.786|
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On calculating the difference between the longest diameter measured on imaging and final pathologic size of all lesions, MRI predicted the most accurate size with a mean size difference of 2.4 ± 6.95 mm, compared to MG with 3.80 ± 18.70 mm and US 5.05 ± 8.07 mm. With the threshold size difference of 5 mm between the preoperative imaging size and pathologic size, the MG was accurate in 57%, US in 50%, and MRI in 85% of residual tumor size prediction [Figure 3]. Overestimation rate was high on the US (41%) in contrast to MG (21.5%) and MRI (12.5%). Underestimation rate was high on MG (21.5%) and much lower on the US (9%) and MRI (2.5%). The correlation between different molecular subtype (Luminal A, Luminal B, HER2-enriched and triple-negative) and preoperative imaging size of tumor did not show significant difference with the P value >0.1.
|Figure 3: Sixty-one-year-old female with right breast cancer, luminal B subtype. post-NACT pathological residual tumor size 12 mm. (a) Diagnostic MG (Right CC and MLO views) prior to the NACT showed 42 mm hyperdense mass with irregular margins (thick white arrow) in the right breast. (b) post-NACT mammogram (CC and MLO views) showed a clip in situ, no residual mass (thin white arrow). (c) US after NACT showed a hypoechoic residual mass, maximum tumor dimension 15.5 mm. (d) MRI after NACT showed enhancing residual mass surrounding the clip (white hollow arrow) in the subareolar region, maximum tumor dimension 13 mm|
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Correlation between post-NACT residual axillary lymph node on imaging and pathology
Of 34 patients with residual disease on final histopathology, 14 patients (41.2%) were detected to have residual metastatic deposits in ipsilateral dissected axillary lymph nodes. Of 14 lymph node-positive patients, 10 (71.4%) were suspected on US, and 11 (78.6%) on MRI. The specificity and accuracy of predicting metastases in axillary lymph nodes were higher for MRI as compared to US (95.2% versus 67.4%, and 91% versus 68.4%, respectively).
| » Discussion|| |
As we have moved into the era of precision and personalized cancer management, NACT is increasingly being administered to the patients with non-metastatic breast cancer to downstage the disease and increase the chances of successful BCS without compromising on the outcome compared with radical mastectomy., post-NACT response evaluation and measurement of residual tumor in the breast and axillary nodes aid in deciding further treatment and in predicting the prognosis. The accuracy of clinical response assessment for determining pCR after NACT is 57 to 66%, and 60-80% of patients predicted to have pCR have a residual tumor on final pathology., Accuracy of imaging plays an important role in assessing the post neo-adjuvant therapy residual disease to select the next appropriate therapeutic option although many studies were done in the past, the positive predictive value (PPV) for predicting pCR was not sufficient to replace pathological examination.,,,,, Our results showed that MRI had the highest accuracy for detecting pathological complete response and detecting residual tumor after NACT, which was in concordance with other studies., In contrast to the study done by Gampenrieder et al. this study did not show any significant difference in the diagnostic performance of imaging in predicting the complete response of different molecular subtypes. Accuracy of the digital MG was much lower than MRI as 75% of our study patients had either heterogeneously dense or extremely dense breast American college of Radiology (ACR category C and D), which may obscure smaller isodense lesions because of superimposition of breast parenchyma. Accuracy of US was also low because of residual lesion and post-treatment changes, both appeared hypoechoic or mixed echoic. On adding the color Doppler, 22 of 34 patients (64.7%) with residual tumor demonstrated some amount of color flow in contrast to 2 out of 22 (9%) patients with post-treatment changes/fibrotic lesions.
Several studies have compared residual tumor size on preoperative imaging and final pathology, but results have been variable and conflicting due to heterogeneity of breast cancer.,,,,,, A few of them have compared various imaging tools (MG, US, Digital Breast Tomosynthesis and MRI) with the pathology and found MRI to be the most reliable one., In this study, the longest diameter of the residual tumor measured on MRI showed a strong positive correlation and most accurately reflected the tumor size (including invasive and non-invasive DCIS) noted on final histopathology irrespective of the molecular subtypes. Unlike MG, which tended to underestimate the size due to superimposition by breast parenchyma, MRI tended to overestimate the size except for a few cases with DCIS on final pathology, although none of the pathologic residual tumor went undetected on MRI. Many of the studies published earlier have shown a 33 to 38% rate of overestimation and a few studies have shown underestimation of tumor size on MRI.,,, Underestimated size of residual tumor on preoperative imaging may lead to positive surgical margins and thus second surgery. Hence, an accurate assessment of tumor size is important for precise breast surgery. In this study, on MRI overestimation of tumor size was more common because any enhancing residual lesion on dynamic CE-MRI was considered as residual tumor irrespective of the type of post-contrast kinetic curve. Many of the small residual tumors were diagnosed as post-treatment scar and all these scars demonstrated type I curve. Although pathologic residual tumors demonstrated dynamic type I or II or III type of curve.
MG is the most widely used imaging tool to assess post-NACT tumor response and residual tumor in the form of size and density of the mass, and microcalcification extent if present. Assessment of residual tumor on MG after NACT could be challenging because of the dense breast, spiculated margins due to post-treatment fibrosis/hyalinization and necrotic or dystrophic microcalcifications. Dense breast may obscure the isodense tumors or tumor margins, which could lead to underestimation of the residual tumor size or increase the chances of false-negative rates, both of which were observed in our study. Other studies found that microcalcification on post-NACT MG could represent either residual tumor or post-treatment necrosis., The presence of spiculated margins due to post-treatment fibrosis and microcalcification due to necrosis might lead to overestimation of tumor size and false positives on MG.
US is considered the best supplementary tool for other imaging modalities for breast cancer evaluation. However, it is less reliable for detecting microcalcification without the use of MG, thus high false-negative rates for DCIS.
For small solid and nonspecific lesions, the US is considered to have high false-positive rates that may require US-guided biopsy or close follow up to rule out a neoplasm., In concordance with the study done by Park et al. our study showed a moderate positive correlation coefficient in predicting the residual tumor with the lowest accuracy in predicting the residual tumor size. The overestimation rate of detecting residual tumor was high (41%) because of the lack of specificity of the US to differentiate hypoechoic lesion due to post-treatment fibrosis/scar and residual tumor after NACT.
There were a few limitations in this study. First, the sample size was small. Second, the evaluation of intra and inter-observer agreements was not done. Third, all patients did not receive the same number of NACT cycles. Fourth, digital breast tomosynthesis (DBT) or 3D MG was not used for evaluation, which could have shown better results than digital MG. Fifth, the clip was placed within the mass lesion after biopsy under US or mammogram guidance which might have caused some perifocal reactive changes and thus increased false-positives rates or overestimated the residual tumor size on US and MRI.
In conclusion, after NACT, imaging serves an important role in response evaluation by determining complete or partial resolution, size and extent of the residual disease and for preoperative localization of the tumor. On comparing the diagnostic performance of MG, US, and MRI for predicting pCR, we found CE-MRI to be the most reliable tool with the highest accuracy, and MG showed the lowest accuracy. Pathologic residual tumor size after NACT was also most accurately reflected by the longest tumor dimension measured on CE-MRI with the strong positive correlation coefficient, and MG was the least accurate. Hence, preoperative MRI performed after NACT is a better imaging alternative for more precise surgery of breast cancer by detecting pCR more accurately. However, larger multicenter trials are needed for validation of these observations.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2]