Is the whole larger than the sum of the parts? Integrated PET/MRI as a tool for response prediction

Mottaghy, Felix M.

doi:10.1007/s00259-017-3908-9

Cited by 4 publications

(2 citation statements)

References 29 publications

(33 reference statements)

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“…Mottaghy31 found a positive association between PR expression and breast density in breast biopsies from 18 patients at high risk of breast cancer but not for any other stromal markers investigated. Yang and colleagues32 in contrast found no significant association between HR status and mammographic breast density after univariate analysis of 66 patients.…”

Section: Discussionmentioning

confidence: 86%

<p>Conversion of immunohistochemical markers and breast density are associated with pathological response and prognosis in very young breast cancer patients who fail to achieve a pathological complete response after neoadjuvant chemotherapy</p>

Zhao

Wang

Huang

et al. 2019

CMAR

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Purpose Patients younger than age 35 that fail to achieve a pathologic complete response (pCR) after Neoadjuvant chemotherapy (NACT) tend to have worse long term outcomes. The purpose of our study was to assess the correlation between the conversion of immunohistochemical (IHC) markers and breast density and investigate their association with pathological response and prognosis. Methods We included 119 patients younger than age 35 who failed to achieve a pCR after NACT in this analysis. We evaluated the clinical and pathological response to NACT by the Union for International Cancer control (UICC) and the Miller-Payne grading (MPG) systems, respectively. A breast density assessment was applied via mammography examination at the time of diagnosis. MPG and breast density (BD) have been combined to define a specific classification of three risk levels to evaluate the prognosis of these patients. Results The diameter changes of the tumors and lymph nodes were negatively associated with hormone receptor conversion and positively correlated with Ki67 conversion. A significantly large size change was observed in the groups demonstrating conversion from HER-2 (+) to (−). The variation level of IHC markers was related to MPG and BD and was associated with the survival rate of the patients. Patients with a high breast density and low Miller-Payne grading after NACT had a higher risk of distant metastases or local recurrences. Conclusion ER, PR and Ki67 conversion are closely related to MPG, while PR and Ki67 conversion are closely related to BD. While ER and PR conversion are independent and significant predictors of disease free survival (DFS) and overall survival (OS), HER-2 and Ki67 conversion are only significant for DFS. This risk factor grouping provides a useful index to evaluate the risk of young women with breast cancer who fail to achieve a pCR.

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Section: Discussionmentioning

confidence: 86%

<p>Conversion of immunohistochemical markers and breast density are associated with pathological response and prognosis in very young breast cancer patients who fail to achieve a pathological complete response after neoadjuvant chemotherapy</p>

Zhao

Wang

Huang

et al. 2019

CMAR

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“…However, the predictive power of MRI parameters was seldom reported to improve the information already provided by the status of hormonal receptors (4). PET-CT has been used occasionally to monitor the response to NAC in breast cancer, sometimes in combination with MRI (5)(6)(7).…”

Section: Introductionmentioning

confidence: 99%

3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

et al. 2021

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ObjectivesTo test whether 3T MRI radiomics of breast malignant lesions improves the performance of predictive models of complete response to neoadjuvant chemotherapy when added to other clinical, histological and radiological information.MethodsWomen who consecutively had pre-neoadjuvant chemotherapy (NAC) 3T DCE-MRI between January 2016 and October 2019 were retrospectively included in the study. 18F-FDG PET-CT and histological information obtained through lesion biopsy were also available. All patients underwent surgery and specimens were analyzed. Subjects were divided between complete responders (Pinder class 1i or 1ii) and non-complete responders to NAC. Geometric, first order or textural (higher order) radiomic features were extracted from pre-NAC MRI and feature reduction was performed. Five radiomic features were added to other available information to build predictive models of complete response to NAC using three different classifiers (logistic regression, support vector machines regression and random forest) and exploring the whole set of possible feature selections.ResultsThe study population consisted of 20 complete responders and 40 non-complete responders. Models including MRI radiomic features consistently showed better performance compared to combinations of other clinical, histological and radiological information. The AUC (ROC analysis) of predictors that did not include radiomic features reached up to 0.89, while all three classifiers gave AUC higher than 0.90 with the inclusion of radiomic information (range: 0.91-0.98).ConclusionsRadiomic features extracted from 3T DCE-MRI consistently improved predictive models of complete response to neo-adjuvant chemotherapy. However, further investigation is necessary before this information can be used for clinical decision making.

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Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study

Incoronato

Grimaldi

Cavaliere

et al. 2018

Eur J Nucl Med Mol Imaging

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Is the whole larger than the sum of the parts? Integrated PET/MRI as a tool for response prediction

Cited by 4 publications

References 29 publications

<p>Conversion of immunohistochemical markers and breast density are associated with pathological response and prognosis in very young breast cancer patients who fail to achieve a pathological complete response after neoadjuvant chemotherapy</p>

<p>Conversion of immunohistochemical markers and breast density are associated with pathological response and prognosis in very young breast cancer patients who fail to achieve a pathological complete response after neoadjuvant chemotherapy</p>

3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study

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