Imaging performance in guiding response to neoadjuvant therapy according to breast cancer subtypes: A systematic literature review
Introduction
In 2012, 1.7 million new cases of breast cancer were diagnosed worldwide. Despite research and improvements in breast cancer treatment, breast cancer is still: one of the most prevalent cancers overall, the most prevalent cancer among women, and one of the main causes of death (WHO, 2012). Research on new treatment approaches is thus of evident interest.
Neoadjuvant chemotherapy(NAC) showed to be at least equally effective as adjuvant chemotherapy (Mauri et al., 2005) while having additional advantages (Fisher et al., 1997, van der Hage et al., 2001), such as the ability to monitor therapeutic response during treatment (Gralow et al., 2008). Early therapeutic response assessed by imaging seems to be a predictor of pathologic complete response(pCR) (Marinovich et al., 2012), usually defined as absence of any residual invasive tumour cells in the original tumour bed and axilla (Kaufmann et al., 2006). PCR itself predicts long-term survival, especially in HER2-positive and triple negative(TN) tumours (Chollet et al., 2002, Von Minckwitz et al., 2012), monitoring early therapeutic response may be used to guide systemic treatment, which is called a response-guided NAC approach (von Minckwitz et al., 2013). Under this scenario, patients could be monitored after a specific number of NAC cycles, and according to their response at imaging, their further systematic treatment could be tailored, i.e. responders continue with the same initial treatment, and non-responders can be switched to a presumably non-cross-resistant regimen(Fig. 1) (von Minckwitz et al., 2013).
Currently, there is no definite guideline to assess response to NAC during treatment. Previous authors proposed physical examination plus mammography and ultrasound, but their performance seems to be limited (Yeh et al., 2005, Hamisa et al., 2015, Londero et al., 2004). Therefore, performance examination of more advanced techniques, i.e. magnetic resonance imaging(MRI) and PET—Computed Tomography(PET/CT) is of interest. So far, meta-analyses have shown sensitivities and specificities of 68% and 91% for dynamic contrast-enhanced(DCE)-MRI (Wu et al., 2012), 93% and 82% for diffusion-weighted(DW)-MRI (Wu et al., 2012) and 84% and 71% for 18F FDG-PET/CT (Cheng et al., 2012) respectively. On the basis of these findings, MRI is currently the technique mainly used in clinical practice. While these techniques seem to already have better performance, recent studies have shown that breast cancer subtype affects imaging performance (Loo et al., 2011, Hayashi et al., 2013, Ko et al., 2013). Hence, personalizing the use of imaging techniques based on subtypes may further improve their performance in evaluating therapeutic response (Loo et al., 2011, Humbert et al., 2012).
As there is no subtype-specific guidance on imaging techniques to monitor therapeutic response during NAC to guide in further treatment regimen, this paper aims to create an overview of current knowledge on the performance of imaging techniques in breast cancer subtypes based on expression of ER and HER2.
Section snippets
Methods
We performed a systematic literature search to find studies reporting on the performance of imaging in assessing pCR during NAC for breast cancer subtypes.
Results
Of the initially 229 identified articles, 30 were selected for full reading after removing duplicates. Sixteen articles were further excluded because: 1)response monitoring was performed before or after NAC, 2)did not report performance data or did not specify their results to subtypes and 3)FDG-PET was used without CT. After snowballing one extra article was included, which made a total of 15 articles(Fig. 2).
Discussion
In view of the potential of response-guided NAC to improve breast cancer survival, we aimed to create an overview of current knowledge on imaging performance to monitor NAC according to breast cancer subtype.
Our results suggest that due to the differences in imaging performance across subtypes, personalizing the monitoring step of response-guided NAC based on these is of relevance. However after reviewing the 15 included articles, we revealed that there is a lack of evidence with enough
Competing interests
The authors declare that they have no conflict of interest.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author’s contributions
AMC, VR, WvH and ML designed and conceptualized the study together, AMC, VR and ML gathered, selected and interpreted the data and drafted the manuscript. WvH, GS, JW and MS helped drafting the manuscript and critically reviewed it. All authors read and approved the final manuscript.
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2021, ESMO OpenCitation Excerpt :Patients with no evidence of invasive cancer in the breast and axillary nodes [pathological complete response (pCR)] have in fact significantly improved disease-free and overall survival. While there is a clear correlation between pCR and prognosis, only poor diagnostic accuracy can be reached when predicting a pCR before surgery by a combination of multiple aspects such as tumor biology, the applied NAC regimen, and breast imaging results.4-6 Thus, a valuable predictive biomarker of NAC response is of paramount importance to assist the clinical decision to continue, change, or stop NAC, and to finally increase the likelihood of achieving pCR.
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2018, The Lancet OncologyCitation Excerpt :Further high-quality prospective evidence is needed to understand the usefulness of such biomarkers. Response can be assessed either clinically or radiologically and improved techniques for the detection of an early response might permit treatment strategies to be adjusted in non-responders (eg, a change of neoadjuvant regimen or proceeding to surgery).36 Accurate prediction of response might increase the reliability of surgical decision making when assessing potential downstaging for breast conservation.
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2018, Magnetic Resonance Imaging Clinics of North AmericaCitation Excerpt :In a study of 250 patients, MR imaging size correlation was significantly better with estrogen receptor (ER)-negative tumors (r = 0.76) than ER-positive tumors (r = 0.40).34 MR imaging was observed to be of limited benefit in predicting pCR in ER-positive tumors.14 FDG-PET/CT performed better than MR imaging for hormone receptor–positive/HER2-negative breast cancer.14
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2020, Nuclear Medicine and BiologyCitation Excerpt :Pathologic response was assessed according to Sinn et al. Since the definition of pathologic response differs in most studies, a comparison of imaging-based prediction of pCR is difficult [42]. In our study cohort, all tumors responded partially and none achieved pCR which is known to be rare for hormone receptor-positive tumors (<20%) [43].