Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning

Evaluation of a novel forward-looking optical coherence tomography probe for endoscopic applications: an ex vivo feasibility study

BACKGROUND

As a result of recent advances in the development of small microelectromechanical system mirrors, a novel forward-looking optical coherence tomography (OCT) probe with a uniquely large field of view is being commercially developed. The aim of this study is to prospectively assess the feasibility of this advanced OCT probe in interpreting ex vivo images of colorectal polyp tissue and to identify necessary steps for further development.

METHODS

A total of 13 colorectal lesions from 9 patients, removed during endoscopic resection, were imaged ex vivo with the OCT device and compared with histopathological images that served as the gold standard for diagnostics. Normal tissue from one patient, removed during the endoscopic procedure, was imaged as a negative control. We assessed the presence of features indicative for polyp type and degree of dysplasia, by comparing OCT images to histopathological images and by evaluating the presence of OCT-specific features identified by previous studies, such as effacement (loss of layered tissue structure), a hyperreflective epithelial layer, and irregularity of the surface.

RESULTS

As verified by corresponding histological images, tissue structures such as blood vessels and tissue layers could be distinguished in OCT images of the normal tissue sample. Detailed structures on histological images such as crypts and cell nuclei could not be identified in the OCT images. However, we did identify OCT features specific for colorectal lesions, such as effacement and a hyperreflective epithelial layer. In general, the imaging depth was about 1 mm.

CONCLUSION

Some relevant tissue structures could be observed in OCT images of the novel device. However, some adaptations, such as increasing imaging depth using a laser with a longer central wavelength, are required to improve its clinical value for the imaging of colorectal lesions.

Advances in endoscopic diagnosis and management of colorectal cancer

Colorectal cancer (CRC) is a leading global health concern, and early identification and precise prognosis play a vital role in enhancing patient results. Endoscopy is a minimally invasive imaging technique that is crucial for the screening, diagnosis, and treatment of CRC. This editorial discusses the importance of advances in endoscopic techniques, the integration of artificial intelligence, and the potential of novel technologies in enhancing the diagnosis and management of CRC.

Tissue characterization using axicon probe-assisted common-path optical coherence tomography

In this work, a common-path optical coherence tomography (OCT) system is demonstrated for characterizing the tissue in terms of some optical properties. A negative axicon structure chemically etched inside the fiber tip is employed as optical probe in the OCT. This probe generates a quality Bessel beam owning a large depth-of-field, ∼700 µm and small central spot size, ∼3 µm. The OCT system is probing the sample without using any microscopic lens. For experimental validation, the OCT imaging of chicken tissue has been obtained along with estimation of its refractive index and optical attenuation coefficient. Afterwards, the cancerous tissue is differentiated from the normal tissue based on the OCT imaging, refractive index, and optical attenuation coefficient. The respective tissue samples are collected from the human liver and pancreas. This probe could be a useful tool for endoscopic or minimal-invasive inspection of malignancy inside the tissue either at early-stage or during surgery.

High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy

Colonoscopy and endoscopic ultrasound play pivotal roles in the assessment of rectal diseases, especially rectal cancer and inflammatory bowel diseases. Optical coherence tomography (OCT) offers a superior depth resolution, which is a critical factor for individualizing the therapeutic concept and evaluating the therapy response. We developed two distinct rectoscope prototypes, which were integrated into a 1300 nm MHz-OCT system constructed at our facility. The rapid rotation of the distal scanning probe at 40,000 revolutions per minute facilitates a 667 Hz OCT frame rate, enabling real-time endoscopic imaging of large areas. The performance of these OCT-rectoscopes was assessed in an ex vivo porcine colon and a post mortem human in-situ colon. The OCT-rectoscope consistently distinguished various layers of the intestinal wall, identified gut-associated lymphatic tissue, and visualized a rectal polyp during the imaging procedure with 3D-reconstruction in real time. Subsequent histological examination confirmed these findings. The body donor was preserved using an ethanol-glycerol-lysoformin-based technique for true-to-life tissue consistency. We could demonstrate that the novel MHZ-OCT-rectoscope effectively discriminates rectal wall layers and crucial tissue characteristics in a post mortem human colon in-situ. This real-time-3D-OCT holds promise as a valuable future diagnostic tool for assessing disease state and therapy response on-site in rectal diseases.

The LMIT: Light-mediated minimally-invasive theranostics in oncology

Minimally-invasive diagnosis and therapy have gradually become the trend and research hotspot of current medical applications. The integration of intraoperative diagnosis and treatment is a development important direction for real-time detection, minimally-invasive diagnosis and therapy to reduce mortality and improve the quality of life of patients, so called minimally-invasive theranostics (MIT). Light is an important theranostic tool for the treatment of cancerous tissues. Light-mediated minimally-invasive theranostics (LMIT) is a novel evolutionary technology that integrates diagnosis and therapeutics for the less invasive treatment of diseased tissues. Intelligent theranostics would promote precision surgery based on the optical characterization of cancerous tissues. Furthermore, MIT also requires the assistance of smart medical devices or robots. And, optical multimodality lay a solid foundation for intelligent MIT. In this review, we summarize the important state-of-the-arts of optical MIT or LMIT in oncology. Multimodal optical image-guided intelligent treatment is another focus. Intraoperative imaging and real-time analysis-guided optical treatment are also systemically discussed. Finally, the potential challenges and future perspectives of intelligent optical MIT are discussed.

Size and depth of residual tumor after neoadjuvant chemoradiotherapy in rectal cancer - implications for the development of new imaging modalities for response assessment

With the shift towards organ preserving treatment strategies in rectal cancer it has become increasingly important to accurately discriminate between a complete and good clinical response after neoadjuvant chemoradiotherapy (CRT). Standard of care imaging techniques such as CT and MRI are well equipped for initial staging of rectal tumors, but discrimination between a good clinical and complete response remains difficult due to their limited ability to detect small residual vital tumor fragments. To identify new promising imaging techniques that could fill this gap, it is crucial to know the size and invasion depth of residual vital tumor tissue since this determines the requirements with regard to the resolution and imaging depth of potential new optical imaging techniques. We analyzed 198 pathology slides from 30 rectal cancer patients with a Mandard tumor regression grade 2 or 3 after CRT that underwent surgery. For each patient we determined response pattern, size of the largest vital tumor fragment or bulk and the shortest distance from the vital tumor to the luminal surface. The response pattern was shrinkage in 14 patients and fragmentation in 16 patients. For both groups combined, the largest vital tumor fragment per patient was smaller than 1mm for 38% of patients, below 0.2mm for 12% of patients and for one patient as small as 0.06mm. For 29% of patients the vital tumor remnant was present within the first 0.01mm from the luminal surface and for 87% within 0.5mm. Our results explain why it is difficult to differentiate between a good clinical and complete response in rectal cancer patients using endoscopy and MRI, since in many patients submillimeter tumor fragments remain below the luminal surface. To detect residual vital tumor tissue in all patients included in this study a technique with a spatial resolution of 0.06mm and an imaging depth of 8.9mm would have been required. Optical imaging techniques offer the possibility of detecting majority of these cases due to the potential of both high-resolution imaging and enhanced contrast between tissue types. These techniques could thus serve as a complimentary tool to conventional methods for rectal cancer response assessment.

Enhanced 3D visualization of human fallopian tube morphology using a miniature optical coherence tomography catheter

We demonstrate the use of our miniature optical coherence tomography catheter to acquire three-dimensional human fallopian tube images. Images of the fallopian tube's tissue morphology, vasculature, and tissue heterogeneity distribution are enhanced by adaptive thresholding, masking, and intensity inverting, making it easier to differentiate malignant tissue from normal tissue. The results show that normal fallopian tubes tend to have rich vasculature accompanied by a patterned tissue scattering background, features that do not appear in malignant cases. This finding suggests that miniature OCT catheters may have great potential for fast optical biopsy of the fallopian tube.

Depth-resolved attenuation mapping of the human ovary and fallopian tube using optical coherence tomography

Due to the lack of reliable early-diagnostic tools, most ovarian cancers are diagnosed at late stages. Although optical coherence tomography (OCT) has shown promise for identifying diseased ovaries and fallopian tubes at an earlier stage, previous studies either did not provide quantitative scattering mapping or simply used Beer's law to fit the scattering coefficients of each A-line. In this paper, we calculated the pixel-wise attenuation coefficients of ovaries and fallopian tubes in OCT images. Data from 73 freshly excised human ovaries and fallopian tubes from 36 patients have shown that statistical features are statistically different between cancerous ovaries, infundibula, and fimbriae and normal ones.

Quantifying the drug response of patient-derived organoid clusters by aggregated morphological indicators with multi-parameters based on optical coherence tomography

Patient-derived organoids (PDOs) serve as excellent tools for personalized drug screening to predict clinical outcomes of cancer treatment. However, current methods for efficient quantification of drug response are limited. Herein, we develop a method for label-free, continuous tracking imaging and quantitative analysis of drug efficacy using PDOs. A self-developed optical coherence tomography (OCT) system was used to monitor the morphological changes of PDOs within 6 days of drug administration. OCT image acquisition was performed every 24 h. An analytical method for organoid segmentation and morphological quantification was developed based on a deep learning network (EGO-Net) to simultaneously analyze multiple morphological organoid parameters under the drug's effect. Adenosine triphosphate (ATP) testing was conducted on the last day of drug treatment. Finally, a corresponding aggregated morphological indicator (AMI) was established using principal component analysis (PCA) based on the correlation analysis between OCT morphological quantification and ATP testing. Determining the AMI of organoids allowed quantitative evaluation of the PDOs responses to gradient concentrations and combinations of drugs. Results showed that there was a strong correlation (correlation coefficient >90%) between the results using the AMI of organoids and those from ATP testing, which is the standard test used for bioactivity measurement. Compared with single-time-point morphological parameters, the introduction of time-dependent morphological parameters can reflect drug efficacy with improved accuracy. Additionally, the AMI of organoids was found to improve the efficiency of 5-fluorouracil(5FU) against tumor cells by allowing the determination of the optimum concentration, and the discrepancies in response among different PDOs using the same drug combinations could also be measured. Collectively, the AMI established by OCT system combined with PCA could quantify the multidimensional morphological changes of organoids under the drug's effect, providing a simple and efficient tool for drug screening in PDOs.

Towards targeted colorectal cancer biopsy based on tissue morphology assessment by compression optical coherence elastography

Identifying the precise topography of cancer for targeted biopsy in colonoscopic examination is a challenge in current diagnostic practice. For the first time we demonstrate the use of compression optical coherence elastography (C-OCE) technology as a new functional OCT modality for differentiating between cancerous and non-cancerous tissues in colon and detecting their morphological features on the basis of measurement of tissue elastic properties. The method uses pre-determined stiffness values (Young’s modulus) to distinguish between different morphological structures of normal (mucosa and submucosa), benign tumor (adenoma) and malignant tumor tissue (including cancer cells, gland-like structures, cribriform gland-like structures, stromal fibers, extracellular mucin). After analyzing in excess of fifty tissue samples, a threshold stiffness value of 520 kPa was suggested above which areas of colorectal cancer were detected invariably. A high Pearson correlation (r =0.98; p <0.05), and a negligible bias (0.22) by good agreement of the segmentation results of C-OCE and histological (reference standard) images was demonstrated, indicating the efficiency of C-OCE to identify the precise localization of colorectal cancer and the possibility to perform targeted biopsy. Furthermore, we demonstrated the ability of C-OCE to differentiate morphological subtypes of colorectal cancer – low-grade and high-grade colorectal adenocarcinomas, mucinous adenocarcinoma, and cribriform patterns. The obtained ex vivo results highlight prospects of C-OCE for high-level colon malignancy detection. The future endoscopic use of C-OCE will allow targeted biopsy sampling and simultaneous rapid analysis of the heterogeneous morphology of colon tumors.

Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect

In the past few decades, according to the rapid development of information technology, artificial intelligence (AI) has also made significant progress in the medical field. Colorectal cancer (CRC) is the third most diagnosed cancer worldwide, and its incidence and mortality rates are increasing yearly, especially in developing countries. This article reviews the latest progress in AI in diagnosing and treating CRC based on a systematic collection of previous literature. Most CRCs transform from polyp mutations. The computer-aided detection systems can significantly improve the polyp and adenoma detection rate by early colonoscopy screening, thereby lowering the possibility of mutating into CRC. Machine learning and bioinformatics analysis can help screen and identify more CRC biomarkers to provide the basis for non-invasive screening. The Convolutional neural networks can assist in reading histopathologic tissue images, reducing the experience difference among doctors. Various studies have shown that AI-based high-level auxiliary diagnostic systems can significantly improve the readability of medical images and help clinicians make more accurate diagnostic and therapeutic decisions. Moreover, Robotic surgery systems such as da Vinci have been more and more commonly used to treat CRC patients, according to their precise operating performance. The application of AI in neoadjuvant chemoradiotherapy has further improved the treatment and efficacy evaluation of CRC. In addition, AI represented by deep learning in gene sequencing research offers a new treatment option. All of these things have seen that AI has a promising prospect in the era of precision medicine.