Combination of breast imaging parameters obtained from 18F-FDG PET and CT scan can improve the prediction of breast-conserving surgery after neoadjuvant chemotherapy in luminal/HER2-negative breast cancer

Development and clinical evaluation of [68Ga]Ga-NODAGA-ADAPT6 as a novel HER2-targeted PET radiotracer for breast cancer imaging and treatment monitoring

PURPOSE

Accurate assessment of human epidermal growth factor receptor type 2 (HER2) expression is crucial for diagnosis, treatment planning, and monitoring of breast cancer patients. A 68Ga-labeled tracer based on the albumin-binding domain-derived affinity protein 6 (ADAPT6) was developed to evaluate HER2 expression in breast cancer.

METHODS

The gene encoding ADAPT6 was modified with N-terminal (GHEHEHEDANS) and C-terminal (GSSC) extensions to enhance its functionality. The precursor was synthesized, purified, and characterized, followed by radiolabeling with 68Ga to produce [68Ga]Ga-NODAGA-ADAPT6. In vivo metabolism and biodistribution studies were performed in HCC1954 (HER2-positive) and MDA-MB-468 (HER2-negative) tumor-bearing mice. Additionally, with ethical approval and informed consent, 22 breast cancer patients underwent [68Ga]Ga-NODAGA-ADAPT6 PET imaging to assess HER2 expression in primary and metastatic lesions.

RESULTS

The tracer was prepared with a radiochemical purity exceeding 99% and demonstrated high stability in vivo. Micro-PET/CT imaging revealed significant accumulation of the radiotracer in HCC1954 tumors, which was markedly reduced after HER2 blockade with trastuzumab. In contrast, MDA-MB-468 tumors showed minimal uptake. In the clinical study, [68Ga]Ga-NODAGA-ADAPT6 PET images displayed varying levels of radiotracer uptake in primary and metastatic lesions, which correlated well with the HER2 expression status determined by pathological analysis.

CONCLUSION

[68Ga]Ga-NODAGA-ADAPT6 exhibited excellent pharmacokinetic properties and high specificity for HER2-expressing lesions in PET imaging. These findings highlight its potential as a promising tool for distinguishing different levels of HER2 expression in breast cancer, aiding in personalized treatment strategies.

Innovations in Positron Emission Tomography and State of the Art in the Evaluation of Breast Cancer Treatment Response

The advent of hybrid Positron Emission Tomography/Computed Tomography (PET/CT) and PET/Magnetic Resonance Imaging (MRI) scanners resulted in an increased clinical relevance of nuclear medicine in oncology. The use of [18F]-Fluorodeoxyglucose ([18F]FDG) has also made it possible to study tumors (including breast cancer) from not only a dimensional perspective but also from a metabolic point of view. In particular, the use of [18F]FDG PET allowed early confirmation of the efficacy or failure of therapy. The purpose of this review was to assess the literature concerning the response to various therapies for different subtypes of breast cancer through PET. We start by summarizing studies that investigate the validation of PET/CT for the assessment of the response to therapy in breast cancer; then, we present studies that compare PET imaging (including PET devices dedicated to the breast) with CT and MRI, focusing on the identification of the most useful parameters obtainable from PET/CT. We also focus on novel non-FDG radiotracers, as they allow for the acquisition of information on specific aspects of the new therapies.

Near-Infrared Spectral Tomography for Predicting Residual Cancer Burden during Early-Stage Neoadjuvant Chemotherapy for Breast Cancer

PURPOSE

The aim of this study is to investigate whether near-infrared spectral tomography (NIRST) might serve as a reliable prognostic tool to predict residual cancer burden (RCB) in patients with breast cancer undergoing neoadjuvant chemotherapy (NAC) based upon early treatment response measurements.

EXPERIMENTAL DESIGN

A total of thirty-five patients with breast cancer receiving NAC were included in this study. NIRST imaging was performed at multiple time points, including: before treatment, at end of the first cycle, at the mid-point, and post-NAC treatments. From reconstructed NIRST images, average values of total hemoglobin (HbT) were obtained for both the tumor region and contralateral breast at each time point. RCB scores/classes were assessed by a pathologist using histologic slides of the surgical specimen obtained after completing NAC. Logistic regression of the normalized early percentage change of HbT in the tumor region (ΔHbT%) was used to predict RCB and determine its significance as an indicator for differentiating cases within each RCB class.

RESULTS

The ΔHbT% at the end of the first cycle, as compared with pretreatment levels, showed excellent prognostic capability in differentiating RCB-0 from RCB-I/II/III or RCB-II from RCB-0/I/III (P < 0.001). Corresponding area under the curve (AUC) values for these comparisons were 0.97 and 0.94, and accuracy values were 0.90 and 0.83, respectively.

CONCLUSIONS

NIRST holds promise as a potential clinical tool that can be seamlessly integrated into existing clinical workflow within the infusion suite. By providing early assessment of RCB, NIRST has potential to improve breast cancer patient management strategies.

Molecular imaging as biomarker for treatment response and outcome in breast cancer

Molecular imaging, such as positron emission tomography (PET), is increasingly used as biomarker to predict and assess treatment response in breast cancer. The number of biomarkers is expanding with specific tracers for tumour characteristics throughout the body and this information can be used to aid the decision-making process. These measurements include metabolic activity using [18F]fluorodeoxyglucose PET ([18F]FDG-PET), oestrogen receptor (ER) expression using 16α-[18F]Fluoro-17β-oestradiol ([18F]FES)-PET and human epidermal growth factor receptor 2 (HER2) expression using PET with radiolabelled trastuzumab (HER2-PET). In early breast cancer, baseline [18F]FDG-PET is frequently used for staging, but limited subtype-specific data reduce its usefulness as biomarker for treatment response or outcome. Early metabolic change on serial [18F]FDG-PET is increasingly used in the neo-adjuvant setting as dynamic biomarker to predict pathological complete response to systemic therapy, potentially allowing de-intensification or step-up intensification of treatment. In the metastatic setting, baseline [18F]FDG-PET and [18F]FES-PET can be used as biomarker to predict treatment response, in triple-negative and ER-positive breast cancer, respectively. Metabolic progression on repeated [18F]FDG-PET appears to precede progressive disease on standard evaluation imaging; however, subtype-specific studies are limited and more prospective data are needed before implementation in clinical practice. Even though (repeated) [18F]FDG-PET, [18F]FES-PET and HER2-PEt all show promising results as biomarkers to predict therapy response and outcome, for eventual integration into clinical practice, future studies will have to clarify at what timepoint this integration has to optimally take place.

A novel method for selecting the set optimal wavelength combination in multi-spectral transmission image

In the process of detecting heterogeneity in breast tissue based on multi-spectral transmission imaging, the detection accuracy will be affected due to the high redundancy degree of information between bands. In order to select the reasonable wavelength combination, this paper uses various nonlinear transformations to convert the multi-spectral images into spectral data for the first time, so as to select the set optimal wavelength combination based on the successive projections algorithm (SPA). Firstly, we design the collection experiment of 4-wavelength multi-spectral image. And then, K-SVD dictionary learning method, texture extraction method and gray correlation analysis method are used to obtain the feature spectral information. Finally, the set optimal wavelength combination is selected based on SPA. The experimental results show that random forest (RF) classification model and Faster-RCNN recognition models effectively verify that the combination of wavelengths 1,2,4 selected has the highest accuracy in the heterogeneous detection. In conclusion, this paper uses modulation-frame accumulation technique to improve the quality of multi-spectral transmission images. And based on the RF and Faster-RCNN models, the effectiveness of SPA-based optimal wavelength combination method proposed is verified, which will provide a new idea of feature wavelength selection for screening early breast masses through multi-spectral transmission imaging.