Compressed sensing of human breast optical coherence 3-D image volume data using predictive coding

There are clinical needs for optical coherence tomography (OCT) of large areas within a short period of time, such as imaging resected breast tissue for the evaluation of cancer. We report on the use of denoising predictive coding (DN-PC), a novel compressed sensing (CS) algorithm for reconstruction of OCT volumes of human normal breast and breast cancer tissue. The DN-PC algorithm has been rewritten to allow for computational parallelization and efficient memory transfer, resulting in a net reduction of computation time by a factor of 20. We compress image volumes at decreasing A-line sampling rates to evaluate a relation between reconstruction behavior and image features of breast tissue.

In vivo characterisation of field pea stem wall thickness using optical coherence tomography

BACKGROUND

Modern field pea breeding faces a significant challenge in selecting lines with strong stems that resist lodging. Traditional methods of assessing stem strength involve destructive mechanical tests on mature stems after natural senescence, such as measuring stem flexion, stem buckling or the thickness of dry stems when compressed, but these measurements may not correspond to the strength of stems in the living plant. Optical coherence tomography (OCT) can be used as a noncontact and nondestructive method to measure stem wall thickness in living plants by acquiring two- or three-dimensional images of living plant tissue.

RESULTS

In this proof-of-principle study, we demonstrated in vivo characterisation of stem wall thickness using OCT, with the measurement corrected for the refractive index of the stem tissue. This in vivo characterisation was achieved through real-time imaging of stems, with an acquisition rate of 13 milliseconds per two-dimensional, cross-sectional OCT image. We also acquired OCT images of excised stems and compared the accuracy of in vivo OCT measurements of stem wall thickness with ex vivo results for 10 plants each of two field pea cultivars, Dunwa and Kaspa. In vivo OCT measurements of stem wall thickness have an average percent error of - 3.1% when compared with ex vivo measurements. Additionally, we performed in vivo measurements of both stem wall thickness and stem width at various internode positions on the two cultivars. The results revealed that Dunwa had a uniform stem wall thickness across different internode positions, while Kaspa had a significantly negative slope of [Formula: see text]0.0198 mm/node. Both cultivars exhibited an increase in stem width along the internode positions; however, Dunwa had a rate of increase of 0.1844 mm/node, which is three times higher than that of Kaspa.

CONCLUSIONS

Our study has demonstrated the efficacy of OCT for accurate measurement of the stem wall thickness of live field pea. Moreover, OCT shows that the trends of stem wall thickness and stem width along the internode positions are different for the two cultivars, Dunwa and Kaspa, potentially hinting at differences in their stem strength. This rapid, in vivo imaging method provides a useful tool for characterising physical traits critical in breeding cultivars that are resistant to lodging.

Multiscale Label-Free Imaging of Fibrillar Collagen in the Tumor Microenvironment

With recent advances in cancer therapeutics, there is a great need for improved imaging methods for characterizing cancer onset and progression in a quantitative and actionable way. Collagen, the most abundant extracellular matrix protein in the tumor microenvironment (and the body in general), plays a multifaceted role, both hindering and promoting cancer invasion and progression. Collagen deposition can defend the tumor with immunosuppressive effects, while aligned collagen fiber structures can enable tumor cell migration, aiding invasion and metastasis. Given the complex role of collagen fiber organization and topology, imaging has been a tool of choice to characterize these changes on multiple spatial scales, from the organ and tumor scale to cellular and subcellular level. Macroscale density already aids in the detection and diagnosis of solid cancers, but progress is being made to integrate finer microscale features into the process. Here we review imaging modalities ranging from optical methods of second harmonic generation (SHG), polarized light microscopy (PLM), and optical coherence tomography (OCT) to the medical imaging approaches of ultrasound and magnetic resonance imaging (MRI). These methods have enabled scientists and clinicians to better understand the impact collagen structure has on the tumor environment, at both the bulk scale (density) and microscale (fibrillar structure) levels. We focus on imaging methods with the potential to both examine the collagen structure in as natural a state as possible and still be clinically amenable, with an emphasis on label-free strategies, exploiting intrinsic optical properties of collagen fibers.

Classifying breast cancer in ultrahigh-resolution optical coherence tomography images using convolutional neural networks

Optical coherence tomography (OCT) is being investigated in breast cancer diagnostics as a real-time histology evaluation tool. We present a customized deep convolutional neural network (CNN) for classification of breast tissues in OCT B-scans. Images of human breast samples from mastectomies and breast reductions were acquired using a custom ultrahigh-resolution OCT system with 2.72 µm axial resolution and 5.52 µm lateral resolution. The network achieved 96.7% accuracy, 92% sensitivity, and 99.7% specificity on a dataset of 23 patients. The usage of deep learning will be important for the practical integration of OCT into clinical practice.

Diagnostic Accuracy of Quantitative Micro-Elastography for Margin Assessment in Breast-Conserving Surgery

Inadequate margins in breast-conserving surgery (BCS) are associated with an increased likelihood of local recurrence of breast cancer. Currently, approximately 20% of BCS patients require repeat surgery due to inadequate margins at the initial operation. Implementation of an accurate, intraoperative margin assessment tool may reduce this re-excision rate. This study determined, for the first time, the diagnostic accuracy of quantitative micro-elastography (QME), an optical coherence tomography (OCT)-based elastography technique that produces images of tissue microscale elasticity, for detecting tumor within 1 mm of the margins of BCS specimens. Simultaneous OCT and QME were performed on the margins of intact, freshly excised specimens from 83 patients undergoing BCS and on dissected specimens from 7 patients undergoing mastectomy. The resulting three-dimensional images (45 × 45 × 1 mm) were coregistered with postoperative histology to determine tissue types present in each scan. Data from 12 BCS patients and the 7 mastectomy patients served to build a set of images for reader training. One hundred and fifty-four subimages (10 × 10 × 1 mm) from the remaining 71 BCS patients were included in a blinded reader study, which resulted in 69.0% sensitivity and 79.0% specificity using OCT images, versus 92.9% sensitivity and 96.4% specificity using elasticity images. The quantitative nature of QME also facilitated development of an automated reader, which resulted in 100.0% sensitivity and 97.7% specificity. These results demonstrate high accuracy of QME for detecting tumor within 1 mm of the margin and the potential for this technique to improve outcomes in BCS. SIGNIFICANCE: An optical imaging technology probes breast tissue elasticity to provide accurate assessment of tumor margin involvement in breast-conserving surgery.

Fully Automated Postlumpectomy Breast Margin Assessment Utilizing Convolutional Neural Network Based Optical Coherence Tomography Image Classification Method

BACKGROUND

The purpose of this study was to develop a deep learning classification approach to distinguish cancerous from noncancerous regions within optical coherence tomography (OCT) images of breast tissue for potential use in an intraoperative setting for margin assessment.

METHODS

A custom ultrahigh-resolution OCT (UHR-OCT) system with an axial resolution of 2.7 μm and a lateral resolution of 5.5 μm was used in this study. The algorithm used an A-scan-based classification scheme and the convolutional neural network (CNN) was implemented using an 11-layer architecture consisting of serial 3 × 3 convolution kernels. Four tissue types were classified, including adipose, stroma, ductal carcinoma in situ, and invasive ductal carcinoma.

RESULTS

The binary classification of cancer versus noncancer with the proposed CNN achieved 94% accuracy, 96% sensitivity, and 92% specificity. The mean five-fold validation F1 score was highest for invasive ductal carcinoma (mean standard deviation, 0.89 ± 0.09) and adipose (0.79 ± 0.17), followed by stroma (0.74 ± 0.18), and ductal carcinoma in situ (0.65 ± 0.15).

CONCLUSION

It is feasible to use CNN based algorithm to accurately distinguish cancerous regions in OCT images. This fully automated method can overcome limitations of manual interpretation including interobserver variability and speed of interpretation and may enable real-time intraoperative margin assessment.

Optical palpation for the visualization of tumor in human breast tissue

Accurate and effective removal of tumor in one operation is an important goal of breast-conserving surgery. However, it is not always achieved. Surgeons often utilize manual palpation to assess the surgical margin and/or the breast cavity. Manual palpation, however, is subjective and has relatively low resolution. Here, we investigate a tactile imaging technique, optical palpation, for the visualization of tumor. Optical palpation generates maps of the stress at the surface of tissue under static preload compression. Stress is evaluated by measuring the deformation of a contacting thin compliant layer with known mechanical properties using optical coherence tomography. In this study, optical palpation is performed on 34 freshly excised human breast specimens. Wide field-of-view (up to ~46 × 46 mm) stress images, optical palpograms, are presented from four representative specimens, demonstrating the capability of optical palpation to visualize tumor. Median stress reported for adipose tissue, 4 kPa, and benign dense tissue, 8 kPa, is significantly lower than for invasive tumor, 60 kPa. In addition, we demonstrate that optical palpation provides contrast consistent with a related optical technique, quantitative micro-elastography. This study demonstrates that optical palpation holds promise for visualization of tumor in breast-conserving surgery.

Clinical feasibility of optical coherence micro-elastography for imaging tumor margins in breast-conserving surgery

It has been demonstrated that optical coherence micro-elastography (OCME) provides additional contrast of tumor compared to optical coherence tomography (OCT) alone. Previous studies, however, have predominantly been performed on mastectomy specimens. Such specimens typically differ substantially in composition and geometry from the more clinically relevant wide-local excision (WLE) specimens excised during breast-conserving surgery. As a result, it remains unclear if the mechanical contrast observed is maintained in WLE specimens. In this manuscript, we begin to address this issue by performing a feasibility study of OCME on 17 freshly excised, intact WLE specimens. In addition, we present two developments required to sustain the progression of OCME towards intraoperative deployment. First, to enable the rapid visualization of en face images required for intraoperative assessment, we describe an automated segmentation algorithm to fuse en face micro-elastograms with OCT images to provide dual contrast images. Secondly, to validate contrast in micro-elastograms, we present a method that enables co-registration of en face images with histology of WLE specimens, sectioned in the orthogonal plane, without any modification to the standard clinical workflow. We present a summary of the observations across the 17 specimens imaged in addition to representative micro-elastograms and OCT images demonstrating contrast in a number of tumor margins, including those involved by invasive ductal carcinoma, mucinous carcinoma, and solid-papillary carcinoma. The results presented here demonstrate the potential of OCME for imaging tumor margins.

Quantitative evaluation of redox ratio and collagen characteristics during breast cancer chemotherapy using two-photon intrinsic imaging

Preoperative neoadjuvant treatment in locally advanced breast cancer is recognized as an effective adjuvant therapy, as it improves treatment outcomes. However, the potential complications remain a threat, so there is an urgent clinical need to assess both the tumor response and changes in its microenvironment using non-invasive and precise identification techniques. Here, two-photon microscopy was employed to detect morphological alterations in breast cancer progression and recession throughout chemotherapy. The changes in structure were analyzed based on the autofluorescence and collagen of differing statuses. Parameters, including optical redox ratio, the ratio of second harmonic generation and auto-fluorescence signal, collagen density, and collagen shape orientation, were studied. Results indicate that these parameters are potential indicators for evaluating breast tumors and their microenvironment changes during progression and chemotherapy. Combined analyses of these parameters could provide a quantitative, novel method for monitoring tumor therapy.

Wide-field quantitative micro-elastography of human breast tissue

Currently, 20-30% of patients undergoing breast-conserving surgery require a second surgery due to insufficient surgical margins in the initial procedure. We have developed a wide-field quantitative micro-elastography system for the assessment of tumor margins. In this technique, we map tissue elasticity over a field-of-view of ~46 × 46 mm. We performed wide-field quantitative micro-elastography on thirteen specimens of freshly excised tissue acquired from patients undergoing a mastectomy. We present wide-field optical coherence tomography (OCT) images, qualitative (strain) micro-elastograms and quantitative (elasticity) micro-elastograms, acquired in 10 minutes. We demonstrate that wide-field quantitative micro-elastography can extend the range of tumors visible using OCT-based elastography by providing contrast not present in either OCT or qualitative micro-elastography and, in addition, can reduce imaging artifacts caused by a lack of contact between tissue and the imaging window. Also, we describe how the combined evaluation of OCT, qualitative micro-elastograms and quantitative micro-elastograms can improve the visualization of tumor.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.

Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT

BACKGROUND AND OBJECTIVE

Breast cancer is one of the most common cancers, and recognized as the third leading cause of mortality in women. Optical coherence tomography (OCT) enables three dimensional visualization of biological tissue with micrometer level resolution at high speed, and can play an important role in early diagnosis and treatment guidance of breast cancer. In particular, ultra-high resolution (UHR) OCT provides images with better histological correlation. This paper compared UHR OCT performance with standard OCT in breast cancer imaging qualitatively and quantitatively. Automatic tissue classification algorithms were used to automatically detect invasive ductal carcinoma in ex vivo human breast tissue.

STUDY DESIGN/MATERIALS AND METHODS

Human breast tissues, including non-neoplastic/normal tissues from breast reduction and tumor samples from mastectomy specimens, were excised from patients at Columbia University Medical Center. The tissue specimens were imaged by two spectral domain OCT systems at different wavelengths: a home-built ultra-high resolution (UHR) OCT system at 800 nm (measured as 2.72 μm axial and 5.52 μm lateral) and a commercial OCT system at 1,300 nm with standard resolution (measured as 6.5 μm axial and 15 μm lateral), and their imaging performances were analyzed qualitatively. Using regional features derived from OCT images produced by the two systems, we developed an automated classification algorithm based on relevance vector machine (RVM) to differentiate hollow-structured adipose tissue against solid tissue. We further developed B-scan based features for RVM to classify invasive ductal carcinoma (IDC) against normal fibrous stroma tissue among OCT datasets produced by the two systems. For adipose classification, 32 UHR OCT B-scans from 9 normal specimens, and 28 standard OCT B-scans from 6 normal and 4 IDC specimens were employed. For IDC classification, 152 UHR OCT B-scans from 6 normal and 13 IDC specimens, and 104 standard OCT B-scans from 5 normal and 8 IDC specimens were employed.

RESULTS

We have demonstrated that UHR OCT images can produce images with better feature delineation compared with images produced by 1,300 nm OCT system. UHR OCT images of a variety of tissue types found in human breast tissue were presented. With a limited number of datasets, we showed that both OCT systems can achieve a good accuracy in identifying adipose tissue. Classification in UHR OCT images achieved higher sensitivity (94%) and specificity (93%) of adipose tissue than the sensitivity (91%) and specificity (76%) in 1,300 nm OCT images. In IDC classification, similarly, we achieved better results with UHR OCT images, featured an overall accuracy of 84%, sensitivity of 89% and specificity of 71% in this preliminary study.

CONCLUSION

In this study, we provided UHR OCT images of different normal and malignant breast tissue types, and qualitatively and quantitatively studied the texture and optical features from OCT images of human breast tissue at different resolutions. We developed an automated approach to differentiate adipose tissue, fibrous stroma, and IDC within human breast tissues. Our work may open the door toward automatic intraoperative OCT evaluation of early-stage breast cancer. Lasers Surg. Med. 49:258-269, 2017. © 2017 Wiley Periodicals, Inc.

Optical coherence elastography - OCT at work in tissue biomechanics [Invited]

Optical coherence elastography (OCE), as the use of OCT to perform elastography has come to be known, began in 1998, around ten years after the rest of the field of elastography - the use of imaging to deduce mechanical properties of tissues. After a slow start, the maturation of OCT technology in the early to mid 2000s has underpinned a recent acceleration in the field. With more than 20 papers published in 2015, and more than 25 in 2016, OCE is growing fast, but still small compared to the companion fields of cell mechanics research methods, and medical elastography. In this review, we describe the early developments in OCE, and the factors that led to the current acceleration. Much of our attention is on the key recent advances, with a strong emphasis on future prospects, which are exceptionally bright.

Investigation of optical coherence micro-elastography as a method to visualize micro-architecture in human axillary lymph nodes

Background

Evaluation of lymph node involvement is an important factor in detecting metastasis and deciding whether to perform axillary lymph node dissection (ALND) in breast cancer surgery. As ALND is associated with potentially severe long term morbidity, the accuracy of lymph node assessment is imperative in avoiding unnecessary ALND. The mechanical properties of malignant lymph nodes are often distinct from those of normal nodes. A method to image the micro-scale mechanical properties of lymph nodes could, thus, provide diagnostic information to aid in the assessment of lymph node involvement in metastatic cancer. In this study, we scan axillary lymph nodes, freshly excised from breast cancer patients, with optical coherence micro-elastography (OCME), a method of imaging micro-scale mechanical strain, to assess its potential for the intraoperative assessment of lymph node involvement.

Methods

Twenty-six fresh, unstained lymph nodes were imaged from 15 patients undergoing mastectomy or breast-conserving surgery with axillary clearance. Lymph node specimens were bisected to allow imaging of the internal face of each node. Co-located OCME and optical coherence tomography (OCT) scans were taken of each sample, and the results compared to standard post-operative hematoxylin-and-eosin-stained histology.

Results

The optical backscattering signal provided by OCT alone may not provide reliable differentiation by inspection between benign and malignant lymphoid tissue. Alternatively, OCME highlights local changes in tissue strain that correspond to malignancy and are distinct from strain patterns in benign lymphoid tissue. The mechanical contrast provided by OCME complements the optical contrast provided by OCT and aids in the differentiation of malignant tumor from uninvolved lymphoid tissue.

Conclusion

The combination of OCME and OCT images represents a promising method for the identification of malignant lymphoid tissue. This method shows potential to provide intraoperative assessment of lymph node involvement, thus, preventing unnecessary removal of uninvolved tissues and improving patient outcomes.

Wide-field optical coherence micro-elastography for intraoperative assessment of human breast cancer margins

Incomplete excision of malignant tissue is a major issue in breast-conserving surgery, with typically 20 - 30% of cases requiring a second surgical procedure arising from postoperative detection of an involved margin. We report advances in the development of a new intraoperative tool, optical coherence micro-elastography, for the assessment of tumor margins on the micro-scale. We demonstrate an important step by conducting whole specimen imaging in intraoperative time frames with a wide-field scanning system acquiring mosaicked elastograms with overall dimensions of ~50 × 50 mm, large enough to image an entire face of most lumpectomy specimens. This capability is enabled by a wide-aperture annular actuator with an internal diameter of 65 mm. We demonstrate feasibility by presenting elastograms recorded from freshly excised human breast tissue, including from a mastectomy, lumpectomies and a cavity shaving.

Deep tissue volume imaging of birefringence through fibre-optic needle probes for the delineation of breast tumour

Identifying tumour margins during breast-conserving surgeries is a persistent challenge. We have previously developed miniature needle probes that could enable intraoperative volume imaging with optical coherence tomography. In many situations, however, scattering contrast alone is insufficient to clearly identify and delineate malignant regions. Additional polarization-sensitive measurements provide the means to assess birefringence, which is elevated in oriented collagen fibres and may offer an intrinsic biomarker to differentiate tumour from benign tissue. Here, we performed polarization-sensitive optical coherence tomography through miniature imaging needles and developed an algorithm to efficiently reconstruct images of the depth-resolved tissue birefringence free of artefacts. First ex vivo imaging of breast tumour samples revealed excellent contrast between lowly birefringent malignant regions, and stromal tissue, which is rich in oriented collagen and exhibits higher birefringence, as confirmed with co-located histology. The ability to clearly differentiate between tumour and uninvolved stroma based on intrinsic contrast could prove decisive for the intraoperative assessment of tumour margins.

Investigation of Optical Coherence Microelastography as a Method to Visualize Cancers in Human Breast Tissue

An accurate intraoperative identification of malignant tissue is a challenge in the surgical management of breast cancer. Imaging techniques that help address this challenge could contribute to more complete and accurate tumor excision, and thereby help reduce the current high reexcision rates without resorting to the removal of excess healthy tissue. Optical coherence microelastography (OCME) is a three-dimensional, high-resolution imaging technique that is sensitive to microscale variations of the mechanical properties of tissue. As the tumor modifies the mechanical properties of breast tissue, OCME has the potential to identify, on the microscale, involved regions of fresh, unstained tissue. OCME is based on the use of optical coherence tomography (OCT) to measure tissue deformation in response to applied mechanical compression. In this feasibility study on 58 ex vivo samples from patients undergoing mastectomy or wide local excision, we demonstrate the performance of OCME as a means to visualize tissue microarchitecture in benign and malignant human breast tissues. Through a comparison with corresponding histology and OCT images, OCME is shown to enable ready visualization of features such as ducts, lobules, microcysts, blood vessels, and arterioles and to identify invasive tumor through distinctive patterns in OCME images, often with enhanced contrast compared with OCT. These results lay the foundation for future intraoperative studies. Cancer Res; 75(16); 3236-45. ©2015 AACR.

Assessment of Sentinel Node Biopsies With Full-Field Optical Coherence Tomography

Current techniques for the intraoperative analysis of sentinel lymph nodes during breast cancer surgery present drawbacks such as time and tissue consumption. Full-field optical coherence tomography is a novel noninvasive, high-resolution, fast imaging technique. This study investigated the use of full-field optical coherence tomography as an alternative technique for the intraoperative analysis of sentinel lymph nodes. Seventy-one axillary lymph nodes from 38 patients at Tenon Hospital were imaged minutes after excision with full-field optical coherence tomography in the pathology laboratory, before being handled for histological analysis. A pathologist performed a blind diagnosis (benign/malignant), based on the full-field optical coherence tomography images alone, which resulted in a sensitivity of 92% and a specificity of 83% (n = 65 samples). Regular feedback was given during the blind diagnosis, with thorough analysis of the images, such that features of normal and suspect nodes were identified in the images and compared with histology. A nonmedically trained imaging expert also performed a blind diagnosis aided by the reading criteria defined by the pathologist, which resulted in 85% sensitivity and 90% specificity (n = 71 samples). The number of false positives of the pathologist was reduced by 3 in a second blind reading a few months later. These results indicate that following adequate training, full-field optical coherence tomography can be an effective noninvasive diagnostic tool for extemporaneous sentinel node biopsy qualification.