Metabolic Radiomics for Pretreatment 18F-FDG PET/CT to Characterize Locally Advanced Breast Cancer: Histopathologic Characteristics, Response to Neoadjuvant Chemotherapy, and Prognosis

Abstract

Radiomics has been spotlighted as imaging biomarker for estimation of intratumoral heterogeneity (ITH) which is regarded as the main reason for resistance to tumor treatment. Although a number of studies has shown clinical evidences that separate measurement of metabolic ITH by texture features (TFs) on 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) has prognostic ability in various tumors, there has been no consensus regarding the best parameter representing ITH. Besides, it is yet uncertain that TFs are useful for estimation of histopathologic markers, prediction of response to neoadjuvant chemotherapy (NAC), or prognostic ability in breast cancer. To depart from the traditional approach, we evaluated the clinical usefulness of integrated metabolic radiomics using unsupervised clustering with 109 TFs measured from pretreatment 18F-FDG PET/CT scans of 73 patients with locally advanced breast cancer (LABC) underwent NAC before surgery. Our study shows that metabolic radiomics patterns of LABC are associated with Ki67 expression, achievement of pathologic complete response after NAC, and risk of recurrence. Integrated metabolic radiomics has potential for clinically relevant pretreatment biomarker with predictive and prognostic ability for personalized management in LABC.

Pretreatment 18F-FDG Uptake Heterogeneity Predicts Treatment Outcome of First-Line Chemotherapy in Patients with Metastatic Triple-Negative Breast Cancer

“…Functional molecular imaging offers an important noninvasive approach to biologically characterize tumor heterogeneity and predict treatment outcome. Several studies have proven the predictive value of intratumor heterogeneity of baseline 18 F‐fluorodeoxyglucose ( 18 F‐FDG)‐positron emission tomography (PET) in various primary tumors, including esophageal cancer , lung cancer , cervical cancer , and early breast cancer . Common methods include textural analysis , the coefficient of variance , cumulative standard uptake value (SUV)‐volume histograms (CSH) , the area under the CSH , and fractal analysis .…”

A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET

“…Thenumberofpubl ications involving texture analysis or radiomic studies in medical imaging in general, and in PET in particular, is growing rapidly (1,2). Several authors have published promising PET results suggesting that quantification of lesion heterogeneity using radiomic features can predict patient outcome or treatment response (3)(4)(5)(6). Yet, in a recent study, Chalkidou et al (7) pointed out an inappropriate control of type I error in many radiomic studies that involved the calculation of a large number of imaging features in a small number of patients.…”

Meta-analysis of neoadjuvant therapy and its impact in facilitating breast conservation in operable breast cancer

“…In a systematic analysis 32 , the sensitivity of MRI was shown to be superior to that of other diagnostic modalities, with the exception of PET-CT. On the other hand, meta-analytical data suggested that PET-CT yields moderate accuracy in the identification of patients who will have a pCR 33 . However, recent results 34 suggested that PET-CT and integrated metabolic radiomics may have prognostic value for Ki-67 expression, response to NAT, as well as local recurrence. Vacuum-assisted biopsy after NAT has recently been reported to predict pCR, but the results are conflicting, with false-negative rates ranging from 0 to 49⋅3 per cent and negative predictive values from 71⋅3 to 100 per cent 35,36 , implying that the method has yet to be standardized and refined.…”