Review of quantitative multiscale imaging of breast cancer

Breast percent density changes in digital mammography pre- and post-radiotherapy

INTRODUCTION

Breast cancer (BC), the most frequently diagnosed malignancy among women worldwide, presents a public health challenge and affects mortality rates. Breast-conserving therapy (BCT) is a common treatment, but the risk from residual disease necessitates radiotherapy. Digital mammography monitors treatment response by identifying post-operative and radiotherapy tissue alterations, but accurate assessment of mammographic density remains a challenge. This study used OpenBreast to measure percent density (PD), offering insights into changes in mammographic density before and after BCT with radiation therapy.

METHODS

This retrospective analysis included 92 female patients with BC who underwent BCT, chemotherapy, and radiotherapy, excluding those who received hormonal therapy or bilateral BCT. Percent/percentage density measurements were extracted using OpenBreast, an automated software that applies computational techniques to density analyses. Data were analysed at baseline, 3 months, and 15 months post-treatment using standardised mean difference (SMD) with Cohen's d, chi-square, and paired sample t-tests. The predictive power of PD changes for BC was measured based on the receiver operating characteristic (ROC) curve analysis.

RESULTS

The mean age was 53.2 years. There were no significant differences in PD between the periods. Standardised mean difference analysis revealed no significant changes in the SMD for PD before treatment compared with 3- and 15-months post-treatment. Although PD increased numerically after radiotherapy, ROC analysis revealed optimal sensitivity at 15 months post-treatment for detecting changes in breast density.

CONCLUSIONS

This study utilised an automated breast density segmentation tool to assess the changes in mammographic density before and after BC treatment. No significant differences in the density were observed during the short-term follow-up period. However, the results suggest that quantitative density assessment could be valuable for long-term monitoring of treatment effects. The study underscores the necessity for larger and longitudinal studies to accurately measure and validate the effectiveness of quantitative methods in clinical BC management.

Optimizing diffuse optical imaging for breast tissues with a dual-encoder neural network to preserve small structural information and fine features

Purpose

Various laboratory sources have recently achieved progress in implementing deep learning models on biomedical optical imaging of soft biological tissues. The highly scattered nature of tissues at specific optical wavelengths results in poor spatial resolution. This opens up opportunities for diffuse optical imaging to improve the spatial resolution of obtained optical properties suffering from artifacts. This study aims to investigate a dual-encoder deep learning model for successfully detecting tumors in different phantoms w.r.t tumor size on diffuse optical imaging.

Approach

Our proposed dual-encoder network extends U-net by adding a parallel branch of signal data to get information directly from the base source. This allows the trained network to localize the inclusions without degrading or merging with the background. The signals from the forward model and the images from the inverse problem are combined in a single decoder, filling the gap between existing direct processing and post-processing.

Results

Absorption and reduced scattering coefficients are well reconstructed in both simulation and phantom test datasets. The proposed and implemented dual-encoder networks characterize better optical-property images than the signal-encoder and image-encoder networks, and the contrast-and-size detail resolution of the dual-encoder networks outperforms the other two approaches. From the measures of performance evaluation, the structural similarity and peak signal-to-noise ratio of the reconstructed images obtained by the dual-encoder networks remain the highest values.

Conclusions

In this study, we synthesized the advantages of boundary data direct reconstruction, namely the extracted signals and iterative methods, from the obtained images into a unified network architecture.

Emerging principles of cancer biophysics

Cancer is a multi-step process where normal cells become transformed, grow, and may disseminate to establish new lesions within the body. In recent years, the physical properties of individual cells and the tissue microenvironment have been shown to be potent determinants of cancer progression. Biophysical tools have long been used to examine cell and tissue mechanics, morphology, and migration. However, exciting developments have linked these physical traits to gene expression changes that drive metastatic seeding, organ selectivity, and tumor growth. Here, we present some vignettes to address recent studies to show progress in harnessing biophysical tools and concepts to gain insights into metastasis.

Feasibility of dual-contrast fluorescence imaging of pathological breast tissues

The combination of intravital dye, methylene blue (MB), with molecular cancer marker, pH low insertion peptide (pHLIP) conjugated with fluorescent Alexa532 (Alexa532-pHLIP), was evaluated for enhancing contrast of pathological breast tissue ex vivo. Fresh, thick breast specimens were stained sequentially with Alexa532-pHLIP and aqueous MB and imaged using dual-channel fluorescence microscopy. MB and Alexa532-pHLIP accumulated in the nuclei and cytoplasm of cancer cells, respectively. MB also stained nuclei of normal cells. Some Alexa532-pHLIP fluorescence emission was detected from connective tissue and benign cell membranes. Overall, Alexa532-pHLIP showed high affinity to cancer, while MB highlighted tissue morphology. The results indicate that MB and Alexa532-pHLIP provide complementary information and show promise for the detection of breast cancer.

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

Challenges of conducting quantitative ultrasound with a multimodal optical imaging system

High-frequency quantitative ultrasound is a potential non-invasive source of imaging cell-tissue scale biomarkers for major diseases such as heart disease, cancer, and preterm birth. However, one of the barriers to developing such biomarkers is that it is labor-intensive to compare quantitative ultrasound images to optical images of the tissue structure. We have previously developed a multiscale imaging system that can obtain registered qualitative ultrasound and optical images, but there are further technical challenges to obtaining quantitative data: System-specific details of obtaining and processing data with Verasonics high-frequency transducers; the need for high-frequency reference phantoms; and off-axis clutter from imaging above a glass coverslip. This paper provides a characterization of the Verasonics ultrasound system with the 18.5 MHz L22-14v and 28.5 MHz L38-22v transducers, describes the construction of high-frequency reference phantoms, and details methods for reducing off-axis clutter. The paper features a demonstration multiscale image of a wild type mouse mammary gland that incorporates quantitative ultrasound with both transducers and second harmonic generation microscopy. These advances demonstrate a way to obtain, on a single system with a cohesive and integrated pipeline, quantitative ultrasound data that is correlated with optical imaging without the need for extensive sample preparation.

Novel endoscopic optical diagnostic technologies in medical trial research: recent advancements and future prospects

Novel endoscopic biophotonic diagnostic technologies have the potential to non-invasively detect the interior of a hollow organ or cavity of the human body with subcellular resolution or to obtain biochemical information about tissue in real time. With the capability to visualize or analyze the diagnostic target in vivo, these techniques gradually developed as potential candidates to challenge histopathology which remains the gold standard for diagnosis. Consequently, many innovative endoscopic diagnostic techniques have succeeded in detection, characterization, and confirmation: the three critical steps for routine endoscopic diagnosis. In this review, we mainly summarize researches on emerging endoscopic optical diagnostic techniques, with emphasis on recent advances. We also introduce the fundamental principles and the development of those techniques and compare their characteristics. Especially, we shed light on the merit of novel endoscopic imaging technologies in medical research. For example, hyperspectral imaging and Raman spectroscopy provide direct molecular information, while optical coherence tomography and multi-photo endomicroscopy offer a more extensive detection range and excellent spatial-temporal resolution. Furthermore, we summarize the unexplored application fields of these endoscopic optical techniques in major hospital departments for biomedical researchers. Finally, we provide a brief overview of the future perspectives, as well as bottlenecks of those endoscopic optical diagnostic technologies. We believe all these efforts will enrich the diagnostic toolbox for endoscopists, enhance diagnostic efficiency, and reduce the rate of missed diagnosis and misdiagnosis.

The Venom of Philippine Tarantula (Theraphosidae) Contains Peptides with Pro-Oxidative and Nitrosative-Dependent Cytotoxic Activities against Breast Cancer Cells (MCF-7) In Vitro

Background:

Breast cancer is a multifactorial disease that affects women worldwide. Its progression is likely to be executed by oxidative stress wherein elevated levels of reactive oxygen and nitrogen species drive several breast cancer pathologies. Spider venom contains various pharmacological peptides which exhibit selective activity to abnormal expression of ion channels on cancer cell surface which can confer potent anti-cancer activities against this disease.

Methods:

Venom was extracted from a Philippine tarantula by electrostimulation and fractionated by reverse phase-high performance liquid chromatography (RP-HPLC). Venom fractions were collected and used for in vitro analyses such as cellular toxicity, morphological assessment, and oxidative stress levels.

Results:

The fractionation of crude spider venom generated several peaks which were predominantly detected spectrophotometrically and colorimetrically as peptides. Treatment of MCF-7 cell line of selected spider venom peptides induced production of several endogenous radicals such as hydroxyl radicals (•OH), nitric oxide radicals (•NO), superoxide anion radicals (•O²⁻) and lipid peroxides via malondialdehyde (MDA) reaction, which is comparable with the scavenging effects afforded by 400 µg/mL vitamin E and L-cysteine (p<0.05). Concomitantly, the free radicals produced decrease the mitochondrial membrane potential and metabolic activity as detected by rhodamine 123 and tetrazolium dye respectively (p>0.05). This is manifested by cytotoxicity in MCF-7 cells as seen by increase in membrane blebbing, cellular detachment, caspase activity and nuclear fragmentation.

Conclusion:

These data suggest that the Philippine tarantula venom contains peptide constituents exhibiting pro-oxidative and nitrosative-dependent cytotoxic activities against MCF-7 cells and can indicate mechanistic insights to further explore its potential application as prooxidants in cancer therapy.

3-D-Printed Registration Phantom for Combined Ultrasound and Optical Imaging of Biological Tissues

Efforts to develop quantitative ultrasound biomarkers would benefit from comparisons between ultrasound data and higher-resolution images of the tissue microstructure, such as from optical microscopy. However, only a few studies have used these methods for multiscale imaging because it is difficult to register low-resolution (>100 μm) ultrasound images to high-resolution microscopy images. To address this need, we have designed a 3-D-printed registration phantom that is made of a hard fluorescent resin, fits into a glass-bottom dish and can be used to calculate a coordinate system transform between ultrasound and optical microscopy. We report the phantom design, a registration protocol and an example registration using 18.5-MHz ultrasound and second harmonic generation microscopy. We evaluate the registration precision, achieving standard deviations smaller than the ultrasound resolution across all axes, and illustrate on a mouse mammary gland that this method yields results superior to those of manual landmark registration.

Platform for quantitative multiscale imaging of tissue composition

Changes in the multi-level physical structure of biological features going from cellular to tissue level composition is a key factor in many major diseases. However, we are only beginning to understand the role of these structural changes because there are few dedicated multiscale imaging platforms with sensitivity at both the cellular and macrostructural spatial scale. A single platform reduces bias and complications from multiple sample preparation methods and can ease image registration. In order to address these needs, we have developed a multiscale imaging system using a range of imaging modalities sensitive to tissue composition: Ultrasound, Second Harmonic Generation Microscopy, Multiphoton Microscopy, Optical Coherence Tomography, and Enhanced Backscattering. This paper details the system design, the calibration for each modality, and a demonstration experiment imaging a rabbit eye.