Ultrahigh-resolution optical coherence microscopy accurately classifies precancerous and cancerous human cervix free of labeling

Characteristics and utility of high-resolution optical coherence microscopy images of endocervical canal lesions

OBJECTIVES

To investigate optical coherence microscopy (OCM) imaging features and the application value of these high-resolution images for identifying endocervical canal lesions (ECLs), which is a clinical dilemma in cervical cancer screening programs.

METHODS

In total, 520 OCM images were obtained by scanning the cervical canal lesions with an ultra-high-resolution OCM system (204 specimens from 73 patients). The OCM morphologic characteristics of ECLs were observed and summarized, and then 3 researchers performed a diagnostic test of OCM images of cervical canal lesions. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, 95% confidence interval of each parameter, and interinvestigator agreement (κ) were calculated.

RESULTS

Normal endocervix, cysts, squamous metaplasia, high-grade squamous intraepithelial lesions involving glands, and invasive carcinoma had distinct OCM characteristics, which correlated well with corresponding H&E histologic sections. The accuracy, sensitivity, and specificity of the 3 researchers were 90.6%, 89.3% (95% CI, 86.5%-91.7%) and 91.6% (95% CI, 89.2%-93.5%), respectively. The positive predictive value was 90.1% (95% CI, 87.3%-92.4%), and the negative predictive value was 90.9% (95% CI, 88.5%-92.9%), with almost perfect agreement (κ = 0.874).

CONCLUSIONS

The application of the OCM system in cervical canal lesions is feasible and could help improve detection of occult ECLs in cervical cancer screening programs. This study lays the foundation for further research on OCM in cervical canal lesions in vivo, which also has a potential impact on projecting pathologic evaluation beyond what is currently possible, perhaps globally.

A Deep Learning Model for Cervical Optical Coherence Tomography Image Classification

Objectives: Optical coherence tomography (OCT) has recently been used in gynecology to detect cervical lesions in vivo and proven more effective than colposcopy in clinical trials. However, most gynecologists are unfamiliar with this new imaging technique, requiring intelligent computer-aided diagnosis approaches to help them interpret cervical OCT images efficiently. This study aims to (1) develop a clinically-usable deep learning (DL)-based classification model of 3D OCT volumes from cervical tissue and (2) validate the DL model's effectiveness in detecting high-risk cervical lesions, including high-grade squamous intraepithelial lesions and cervical cancer. Method: The proposed DL model, designed based on the convolutional neural network architecture, combines a feature pyramid network (FPN) with texture encoding and deep supervision. We extracted, represent, and fused four-scale texture features to improve classification performance on high-risk local lesions. We also designed an auxiliary classification mechanism based on deep supervision to adjust the weight of each scale in FPN adaptively, enabling low-cost training of the whole model. Results: In the binary classification task detecting positive subjects with high-risk cervical lesions, our DL model achieved an 81.55% (95% CI, 72.70-88.51%) F1-score with 82.35% (95% CI, 69.13-91.60%) sensitivity and 81.48% (95% CI, 68.57-90.75%) specificity on the Renmin dataset, outperforming five experienced medical experts. It also achieved an 84.34% (95% CI, 74.71-91.39%) F1-score with 87.50% (95% CI, 73.20-95.81%) sensitivity and 90.59% (95% CI, 82.29-95.85%) specificity on the Huaxi dataset, comparable to the overall level of the best investigator. Moreover, our DL model provides visual diagnostic evidence of histomorphological and texture features learned in OCT images to assist gynecologists in making clinical decisions quickly. Conclusions: Our DL model holds great promise to be used in cervical lesion screening with OCT efficiently and effectively.

Usability of a smartphone-compatible, confocal micro-endoscope for cervical cancer screening in resource-limited settings

BACKGROUND

More efficient methods to detect and treat precancerous lesions of the cervix at a single visit, such as low-cost confocal microscopy, could improve early diagnosis and hence outcomes. We piloted a prototype smartphone-compatible confocal micro-endoscope (SCME) among women presenting to a public cervical cancer screening clinic in Kampala, Uganda. We describe the piloting of the SCME device at an urban clinic used by lower cadre staff.

METHODS

We screened women aged 18 and 60 years, who presented for cervical cancer screening at the Kawempe National Referral Hospital Kampala, and evaluated the experience of their providers (nurses). Nurses received a 2-day training by the study doctors on how to use the SCME, which was added to the standard Visual Inspection with Acetic acid (VIA)-based cervical cancer screening. The SCME was used to take colposcopy images before and after VIA at positions 12 and 6 O'clock if VIA negative, and on precancer-suspicious lesions if VIA positive. We used questionnaires to assess the women's experiences after screening, and the experience of the nurses who operated the SCME.

RESULTS

Between November 2021 and July 2022, we screened 291 women with a median age of 36 years and 65.7% were HIV positive. Of the women screened, 146 were eligible for VIA, 123 were screened with the SCME, and we obtained confocal images from 103 women. Of those screened with the SCME, 60% found it comfortable and 81% were willing to screen again with it. Confocal images from 79% of the women showed distinguishable cellular features, while images from the remaining 21% were challenging to analyze. Nurses reported a mean score of 85% regarding the SCME's usefulness to their work, 71% regarding their satisfaction and willingness to use it again, 63% in terms of ease of use, and 57% concerning the ease of learning how to operate the SCME.

CONCLUSION

Our findings demonstrate the feasibility of using the SCME by lower cadre staff in low-resource settings to aid diagnosis of precancerous lesions. However, more work is needed to make it easier for providers to learn how to operate the SCME and capture high-quality confocal images.

Clinical value of optical coherence tomography in the early diagnosis of cervical cancer and precancerous lesions: a cross-sectional study

Background

This study aimed to measure the accuracy of optical coherence tomography (OCT) in the early diagnosis of high-grade cervical lesions and assess its diagnostic value in the triage of high-risk HPV infection.

Method

From Jan 2019 to Jan 2021, women who visited the gynecology clinics of 2 hospitals for colposcopy were invited to participate in this study. Women aged 35 to 64 years old who were sexually active and had an intact cervix with a diameter of more than or equal to 2 cm were included in this study. Additionally, individuals with abnormal cytology, positive HPV test results, or other clinically suspicious symptoms or signs were referred. All participants were examined before colposcopy using OCT. Biopsy and/or ECC were conducted under colposcopy. We used the results of histopathology as the gold standard and assessed the accuracy of OCT.

Results

Overall, 883 women were included in the analysis. Approximately 13.25% of women were ASCUS+ in cytological assessments, and 22.31% were positive for high-risk HPV. Nearly 15.18% of women were positive in OCT. Of them, 27 women were diagnosed with CIN2, and 33 were diagnosed with CIN3+ lesions. Among HPV-positive women, the detection rates for CIN2+ and CIN3+ were much lower for those who were negative in OCT, compared with NILM cytology (CIN2+: 20.0% vs. 30.0%, P=0.002, and CIN3+: 18.2% vs. 27.3%, P=0.013). Among women who were positive for HPV16/18, the detection rate for CIN2+ was much lower for negative OCT, compared with NILM cytology (8.3% vs.15.0%, P=0.005). Compared to HPV and cytological tests, HPV combined with OCT had higher specificity for detecting CIN2+ and CIN3+ (96.1% vs. 93.2%, P=0.002; 93.8% vs. 91.3%, P=0.013). OCT triage after HPV genotyping had the highest AUC for detecting CIN2+ and CIN3+ cases among patients with high-risk HPV infection (0.921, 0.920).

Conclusion

OCT is an accurate test for the early diagnosis of high-grade cervical lesions and has great diagnostic value in the triage of patients with high-risk HPV infection.

Optical imaging for screening and early cancer diagnosis in low-resource settings

Low-cost optical imaging technologies have the potential to reduce inequalities in healthcare by improving the detection of pre-cancer or early cancer and enabling more effective and less invasive treatment. In this Review, we summarise technologies for in vivo widefield, multi-spectral, endoscopic, and high-resolution optical imaging that could offer affordable approaches to improve cancer screening and early detection at the point-of-care. Additionally, we discuss approaches to slide-free microscopy, including confocal imaging, lightsheet microscopy, and phase modulation techniques that can reduce the infrastructure and expertise needed for definitive cancer diagnosis. We also evaluate how machine learning-based algorithms can improve the accuracy and accessibility of optical imaging systems and provide real-time image analysis. To achieve the potential of optical technologies, developers must ensure that devices are easy to use; the optical technologies must be evaluated in multi-institutional, prospective clinical tests in the intended setting; and the barriers to commercial scale-up in under-resourced markets must be overcome. Therefore, test developers should view the production of simple and effective diagnostic tools that are accessible and affordable for all countries and settings as a central goal of their profession.

Optical Coherence Tomography Can Reduce Colposcopic Referral Rates in Patients With High-Risk Human Papillomavirus

OBJECTIVE

This study aimed to evaluate the feasibility of combined human papillomavirus (HPV) and optical coherence tomography (OCT) cervical cancer screening strategies.

MATERIALS AND METHODS

The OCT and cytology results were compared with the pathological results to calculate the sensitivity, specificity, positive predictive value, negative predictive value, and immediate cervical intraepithelial neoplasia grade 3 or worse (CIN3+) risk. The authors compared the efficiency of colposcopy by using different triage strategies. They discussed differentiation in OCT screening in different age groups.

RESULTS

Eight hundred thirteen participants with high-risk HPV-positive and cervical cytology results underwent OCT before colposcopy between March 1 and October 1, 2021. The HPV16/18 genotyping with OCT triage has a specificity of CIN3+ lesions (61.1%; 95% CI = 57.6%-64.6%), intraepithelial neoplasia grade 2 or worse (CIN2+) (66.0%; 95% CI = 62.4%-69.6%). The HPV16/18 genotyping with cytology triage has a specificity of CIN3+ (44.0%; 95% CI = 40.4%-47.6%), CIN2+ (47.0%; 95% CI = 43.2%-50.8%). The OCT triage has a higher positive predictive value compared with the cytology, with a significant difference in CIN2+ lesions (45.0%; 95% CI = 38.8%-51.3% vs 29.2%; 95% CI = 24.7%-33.7%).

CONCLUSIONS

The combination of OCT and high-risk HPV triage (both genotyping and nongenotyping) had a similar immediate CIN3+ risk stratification and reduced the number of colposcopies compared with the cytological triage strategy.

Cross-Attention Based Multi-Resolution Feature Fusion Model for Self-Supervised Cervical OCT Image Classification

Cervical cancer seriously endangers the health of the female reproductive system and even risks women's life in severe cases. Optical coherence tomography (OCT) is a non-invasive, real-time, high-resolution imaging technology for cervical tissues. However, since the interpretation of cervical OCT images is a knowledge-intensive, time-consuming task, it is tough to acquire a large number of high-quality labeled images quickly, which is a big challenge for supervised learning. In this study, we introduce the vision Transformer (ViT) architecture, which has recently achieved impressive results in natural image analysis, into the classification task of cervical OCT images. Our work aims to develop a computer-aided diagnosis (CADx) approach based on a self-supervised ViT-based model to classify cervical OCT images effectively. We leverage masked autoencoders (MAE) to perform self-supervised pre-training on cervical OCT images, so the proposed classification model has a better transfer learning ability. In the fine-tuning process, the ViT-based classification model extracts multi-scale features from OCT images of different resolutions and fuses them with the cross-attention module. The ten-fold cross-validation results on an OCT image dataset from a multi-center clinical study of 733 patients in China indicate that our model achieved an AUC value of 0.9963 ± 0.0069 with a 95.89 ± 3.30% sensitivity and 98.23 ± 1.36 % specificity, outperforming some state-of-the-art classification models based on Transformers and convolutional neural networks (CNNs) in the binary classification task of detecting high-risk cervical diseases, including high-grade squamous intraepithelial lesion (HSIL) and cervical cancer. Furthermore, our model with the cross-shaped voting strategy achieved a sensitivity of 92.06% and specificity of 95.56% on an external validation dataset containing 288 three-dimensional (3D) OCT volumes from 118 Chinese patients in a different new hospital. This result met or exceeded the average of four medical experts who have used OCT for over one year. In addition to promising classification performance, our model has a remarkable ability to detect and visualize local lesions using the attention map of the standard ViT model, providing good interpretability for gynecologists to locate and diagnose possible cervical diseases.

Microendoscopy in vivo for the pathological diagnosis of cervical precancerous lesions and early cervical cancer

BACKGROUND

Cervical cancer is an important public health problem. Conventional colposcopy is inefficient in the diagnosis of cervical lesions and massive biopsies result in trauma. There is an urgent need for a new clinical strategy to triage women with abnormal cervical screening results immediately and effectively. In this study, the high-resolution microendoscopy combined with methylene blue cell staining technology was used to perform real-time in vivo imaging of the cervix for the first time.

METHODS

A total of 41 patients were enrolled in the study. All patients underwent routine colposcopy and cervical biopsy, and high-resolution images of methylene blue-stained cervical lesions were obtained in vivo using microendoscopy. The cell morphological features of benign and neoplastic cervical lesions stained with methylene blue under microendoscopy were analyzed and summarized. The microendoscopy and histopathology findings of the high-grade squamous intraepithelial lesion (HSIL) and more severe lesions were compared.

RESULTS

The overall consistency of microendoscopy diagnosis with pathological diagnosis was 95.12% (39/41). Diagnostic cell morphological features of cervicitis, low-grade squamous intraepithelial lesion (LSIL), HSIL, adenocarcinoma in situ, and invasive cancer were clearly demonstrated in methylene blue stained microendoscopic images. In HSIL and more severe lesions, microendoscopic methylene blue cell staining technology can show the microscopic diagnostic features consistent with histopathology.

CONCLUSIONS

This study was an initial exercise in the application of the microendoscopy imaging system combined with methylene blue cell staining technology to cervical precancerous lesions and cervical cancer screening. The results provided the basis for a novel clinical strategy for triage of women with abnormal cervical screening results using in vivo non-invasive optical diagnosis technology.

Efficacy of optical coherence tomography in the triage of women with minor abnormal cervical cytology before colposcopy

OBJECTIVES

To evaluate the efficacy of Optical Coherence Tomography (OCT) for detecting cervical lesions in women with minor abnormal cytology results (atypical squamous cells of undetermined significance (ASC-US) and low-grade squamous intraepithelial lesion (LSIL)).

METHODS

A prospective study was conducted at gynecologic clinic from Mar 2021 to Sep 2021. The recruited women with cervical cytological findings of ASC-US or LSIL were inspected with OCT before colposcopy-directed cervical biopsy. The diagnostic performance of OCT, alone and in combination with high-risk human papillomavirus (hrHPV) testing were evaluated to detect cervical intraepithelial neoplasia of grade 2 or worse (CIN2+)/CIN3 or worse (CIN3+). The rate of colposcopy referral and the immediate risk of CIN3+ of OCT were calculated.

RESULTS

A total of 349 women with minor abnormal cervical cytology results were enrolled. For detection of CIN2+/CIN3+, the sensitivity and NPV of OCT were lower than those of hrHPV testing (CIN2+: 71.3% vs. 95.4%, 89.0% vs. 91.1%, P < 0.001; CIN3+: 75% vs. 93.8%, 96.5% vs. 95.6%, P < 0.001), but the specificity, accuracy and PPV were higher than those of hrHPV testing (CIN2+: 77.5% vs. 15.6%, 75.9% vs. 35.5%, 51.2% vs. 27.3%, P < 0.001; CIN3+: 69.4% vs. 13.6%, 69.9% vs. 20.9%, 19.8% vs. 9.9%, P < 0.001). OCT combined with hrHPV testing (CIN2+: 80.9%; CIN3+: 72.6%) showed higher specificity than that of OCT alone (P < 0.001). The colposcopy referral rate base on OCT classification was lower than that based on hrHPV testing (34.7% vs. 87.1%, P < 0.001). Patients with hrHPV-positive ASC-US and hrHPV-negative LSIL cytology, the immediate CIN3+ risk in OCT negative cases was less than 4%.

CONCLUSIONS

OCT alone or combination with hrHPV testing shows good performance for detecting CIN2+/CIN3+ in patients with ASC-US/LSIL cytology. OCT is an effective method for colposcopy triage in women with hrHPV-positive ASC-US and hrHPV-negative LSIL cytology.

Digital aberration correction enhances field of view in visible-light optical coherence microscopy

In optical coherence microscopy, optical aberrations commonly result in astigmatism-dominated wavefront errors in the peripheral regions of the optical objective, primarily elongating the microscope's point-spread function along the radial direction in the vicinity of the focal plane. We report on enhanced-field-of-view optical coherence microscopy through computational aberration correction in the visible-light range. An isotropic spatial resolution of 2.5 µm was achieved over an enhanced lateral field of view spanning 1.3 mm × 1.6 mm, as experimentally verified in a micro-bead phantom and further demonstrated in ex vivo tissue samples. The extended field of view achieved by the digital aberration correction facilitates the use of low-cost systems by averting the need for high-quality objectives.

Development of a multimodal mobile colposcope for real-time cervical cancer detection

Cervical cancer remains a leading cause of cancer death among women in low-and middle-income countries. Globally, cervical cancer prevention programs are hampered by a lack of resources, infrastructure, and personnel. We describe a multimodal mobile colposcope (MMC) designed to diagnose precancerous cervical lesions at the point-of-care without the need for biopsy. The MMC integrates two complementary imaging systems: 1) a commercially available colposcope and 2) a high speed, high-resolution, fiber-optic microendoscope (HRME). Combining these two image modalities allows, for the first time, the ability to locate suspicious cervical lesions using widefield imaging and then to obtain co-registered high-resolution images across an entire lesion. The MMC overcomes limitations of high-resolution imaging alone; widefield imaging can be used to guide the placement of the high-resolution imaging probe at clinically suspicious regions and co-registered, mosaicked high-resolution images effectively increase the field of view of high-resolution imaging. Representative data collected from patients referred for colposcopy at Barretos Cancer Hospital in Brazil, including 22,800 high resolution images and 9,900 colposcope images, illustrate the ability of the MMC to identify abnormal cervical regions, image suspicious areas with subcellular resolution, and distinguish between high-grade and low-grade dysplasia.

Research progress on the application of optical coherence tomography in the field of oncology

Optical coherence tomography (OCT) is a non-invasive imaging technique which has become the “gold standard” for diagnosis in the field of ophthalmology. However, in contrast to the eye, nontransparent tissues exhibit a high degree of optical scattering and absorption, resulting in a limited OCT imaging depth. And the progress made in the past decade in OCT technology have made it possible to image nontransparent tissues with high spatial resolution at large (up to 2mm) imaging depth. On the one hand, OCT can be used in a rapid, noninvasive way to detect diseased tissues, organs, blood vessels or glands. On the other hand, it can also identify the optical characteristics of suspicious parts in the early stage of the disease, which is of great significance for the early diagnosis of tumor diseases. Furthermore, OCT imaging has been explored for imaging tumor cells and their dynamics, and for the monitoring of tumor responses to treatments. This review summarizes the recent advances in the OCT area, which application in oncological diagnosis and treatment in different types: (1) superficial tumors:OCT could detect microscopic information on the skin’s surface at high resolution and has been demonstrated to help diagnose common skin cancers; (2) gastrointestinal tumors: OCT can be integrated into small probes and catheters to image the structure of the stomach wall, enabling the diagnosis and differentiation of gastrointestinal tumors and inflammation; (3) deep tumors: with the rapid development of OCT imaging technology, it has shown great potential in the diagnosis of deep tumors such in brain tumors, breast cancer, bladder cancer, and lung cancer.

Cervical optical coherence tomography image classification based on contrastive self-supervised texture learning

BACKGROUND

Cervical cancer seriously affects the health of the female reproductive system. Optical coherence tomography (OCT) emerged as a non-invasive, high-resolution imaging technology for cervical disease detection. However, OCT image annotation is knowledge-intensive and time-consuming, which impedes the training process of deep-learning-based classification models.

PURPOSE

This study aims to develop a computer-aided diagnosis (CADx) approach to classifying in-vivo cervical OCT images based on self-supervised learning.

METHODS

In addition to high-level semantic features extracted by a convolutional neural network (CNN), the proposed CADx approach designs a contrastive texture learning (CTL) strategy to leverage unlabeled cervical OCT images' texture features. We conducted ten-fold cross-validation on the OCT image dataset from a multi-center clinical study on 733 patients from China.

RESULTS

In a binary classification task for detecting high-risk diseases, including high-grade squamous intraepithelial lesion and cervical cancer, our method achieved an area-under-the-curve value of 0.9798 ± 0.0157 with a sensitivity of 91.17 ± 4.99% and a specificity of 93.96 ± 4.72% for OCT image patches; also, it outperformed two out of four medical experts on the test set. Furthermore, our method achieved a 91.53% sensitivity and 97.37% specificity on an external validation dataset containing 287 3D OCT volumes from 118 Chinese patients in a new hospital using a cross-shaped threshold voting strategy.

CONCLUSIONS

The proposed contrastive-learning-based CADx method outperformed the end-to-end CNN models and provided better interpretability based on texture features, which holds great potential to be used in the clinical protocol of "see-and-treat." This article is protected by copyright. All rights reserved.

Study on the application and imaging characteristics of optical coherence tomography in vulva lesions

In this study, a prospective study was conducted by using optical coherence tomography (OCT) in the in vivo detection of vulvar diseases. The clinical efficacy of the OCT we investigated in the detection of vulvar diseases, and the characteristics of the OCT images were defined. Overall, this study recruited 63 patients undergoing the colposcopy for vulvar lesions in three Chinese hospitals from December 20th, 2018 and September 24th, 2019. The colposcopy and the OCT examination were performed successively, and the OCT images were compared with the relevant tissue sections to characterize different lesions. The OCT diagnoses where categorized into 7 types, including normal and inflammatory vulva, condyloma acuminata, papilloma, lichen sclerosus, atrophic sclerosing lichen, fibrous epithelial polyp as well as cysts. The structural characteristics of the vulva tissue can be clearly observed in the OCT image, which are consistent with the characteristics of the tissue section. Compared with the pathological results, the sensitivity, specificity and accuracy of the OCT examination reached 83.82% (95% confidence interval, CI 72.5%–91.3%), 57.89% (95% CI 34.0%–78.9%) and 78.16%, respectively. The OCT is found with the advantages of being noninvasive, real-time and sensitive and with high resolution. It is of high significance to screening vulva diseases, and it is expected as one of the methods to clinically diagnose vulva diseases.

Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test

PURPOSE

To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate the synergetic benefits of the colposcopy, the cytology test, and the HPV test for improving cervical screening performance.

METHODS

This study consisted of 2160 women who underwent cervical screening, there were 442 cases with the histopathological confirmed high-grade squamous intraepithelial lesion (HSIL) or cancer, and the remained 1718 women were controls. Three kinds of cervical images were acquired from colposcopy including the saline image of cervix after saline irrigation, the acetic acid image of cervix after applying acetic acid solution, and the iodine image of cervix after applying Lugol's iodine solution. Each kind of image was used to build a single-image based deep learning model by the VGG-16 convolutional neural network, respectively. A multiple-images based deep learning model was built using multivariable logistic regression (MLR) by combining the single-image based models. The performance of the visual inspection was also obtained. The results of the cytology test and HPV test were used to build a Cytology-HPV joint diagnostic model by MLR. Finally, a cross-modal integrated model was built using MLR by combining the multiple-images based deep learning model, the cytology test results, and the HPV test results. The performances of models were tested in an independent test set using the area under the receiver operating characteristic curve (AUC).

RESULTS

The saline image, acetic acid image, and iodine image based deep learning models had AUC of 0.760, 0.791, and 0.840. The multiple-images based deep learning model achieved an improved AUC of 0.845. The AUC of the visual inspection was 0.751. The Cytology-HPV joint diagnostic model had an AUC of 0.837, which was higher than the cytology test (AUC = 0.749) and the HPV test (AUC = 0.742). The cross-modal integrated model achieved the best performance with AUC of 0.921.

CONCLUSIONS

Combining all kinds of cervical images were benefit for improving the performance of the colposcopy based deep learning model, and more accurate cervical screening could be achieved by incorporating the colposcopy based deep learning model, the cytology test results, and the HPV test results.

Millimeter-scale chip-based supercontinuum generation for optical coherence tomography

Supercontinuum sources for optical coherence tomography (OCT) have raised great interest as they provide broad bandwidth to enable high resolution and high power to improve imaging sensitivity. Commercial fiber-based supercontinuum systems require high pump powers to generate broad bandwidth and customized optical filters to shape/attenuate the spectra. They also have limited sensitivity and depth performance. We introduce a supercontinuum platform based on a 1-mm² Si₃N₄ photonic chip for OCT. We directly pump and efficiently generate supercontinuum near 1300 nm without any postfiltering. With a 25-pJ pump pulse, we generate a broadband spectrum with a flat 3-dB bandwidth of 105 nm. Integrating the chip into a spectral domain OCT system, we achieve 105-dB sensitivity and 1.81-mm 6-dB sensitivity roll-off with 300-μW optical power on sample. We image breast tissue to demonstrate strong imaging performance. Our chip will pave the way toward portable OCT and incorporating integrated photonics into optical imaging technologies.

Multi-center clinical study using optical coherence tomography for evaluation of cervical lesions in-vivo

In this prospective study of an in-vivo cervical examination using optical coherence tomography (OCT), we evaluated the diagnostic value of non-invasive and real-time OCT in cervical precancerous lesions and cancer diagnosis, and determined the characteristics of OCT images. 733 patients from 5 Chinese hospitals were inspected with OCT and colposcopy-directed biopsy. The OCT images were compared with the histological sections to find out the characteristics of various categories of lesions. The OCT images were also interpreted by 3 investigators to make a 2-class classification, and the results were compared against the pathological results. Various structures of the cervical tissue were clearly observed in OCT images, which matched well with the corresponding histological sections. The OCT diagnosis results delivered a sensitivity of 87.0% (95% confidence interval, CI 82.2-90.7%), a specificity of 84.1% (95% CI 80.3-87.2%), and an overall accuracy of 85.1%. Both good consistency of OCT images and histological images and satisfactory diagnosis results were provided by OCT. Due to its features of non-invasion, real-time, and accuracy, OCT is valuable for the in-vivo evaluation of cervical lesions and has the potential to be one of the routine cervical diagnosis methods.

SirT3 activates AMPK-related mitochondrial biogenesis and ameliorates sepsis-induced myocardial injury

Sirtuin-3 (SirT3) and AMPK stimulate mitochondrial biogenesis, which increases mitochondrial turnover and cardiomyocyte regeneration. We studied the effects of SirT3, AMPK, and mitochondrial biogenesis on sepsis-induced myocardial injury. Our data showed that after treating cardiomyocytes with lipopolysaccharide, SirT3 and AMPK levels decreased, and this was followed by mitochondrial dysfunction and cardiomyocyte death. Overexpression of SirT3 activated the AMPK pathway and improved mitochondrial biogenesis, which is required to sustain mitochondrial redox balance, maintain mitochondrial respiration, and suppress mitochondrial apoptosis. Inhibition of mitochondrial biogenesis abolished SirT3/AMPK-induced cardioprotection by causing mitochondrial damage. These findings indicate that SirT3 reduces sepsis-induced myocardial injury by activating AMPK-related mitochondrial biogenesis.

The value of microendoscopy in the diagnosis of cervical precancerous lesions and cervical microinvasive carcinoma

PURPOSE

Cervical cancer is still one of the main causes of death in females. Conventional diagnostic tools such as colposcopy are still unsatisfactory, so accurate diagnostic tools for cervical diseases are needed. Therefore, the purpose of this study was to perform a clinical study to evaluate the value of microendoscopic imaging systems in the diagnosis of cervical precancerous lesions and cervical microinvasive carcinoma (MIC).

METHODS

Totally 106 patients ranging in age from 23 to 67 years were recruited. All patients had abnormal thin-layer cytology (TCT) results (≥ low-grade squamous intraepithelial lesions) and high-risk human papillomavirus (HPV) positivity. Each patient was first subjected to ordinary colposcopy, followed by microendoscopy and biopsy. All results of the colposcopy and microendoscopy images were compared to the histopathological diagnosis.

RESULTS

Characteristics of pathological blood vessels were easily distinguished by microendoscopy compared with ordinary colposcopy. The diagnostic agreement rate of microendoscopy with the pathological diagnosis was higher (95.3%) than that of ordinary colposcopy (37.7%) (weighted kappa = 0.863, P < .01). When diagnosing HSIL and more advanced disease, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the microendoscopic diagnosis were significantly higher than those of ordinary colposcopy (97.6 and 38.1%), (95.5 and 63.6%), (98.8 and 80.0%), (91.3 and 21.2%) and (97.7 and 43.4%), respectively.

CONCLUSION

This study shows that microendoscopy has important value in the diagnosis of cervical lesions which can provide real-time diagnosis in vivo without staining, particularly for lesions that are not sensitive to acetic acid staining.

Real-time colorectal cancer diagnosis using PR-OCT with deep learning

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternative technique to endoscopic biopsy - the current gold-standard colorectal cancer screening and surveillance modality. To help clinical translation limited by processing the large volume of generated data, we designed a deep learning-based pattern recognition (PR) OCT system that automates image processing and provides accurate diagnosis potentially in real-time. Method: OCT is an emerging imaging technique to obtain 3-dimensional (3D) "optical biopsies" of biological samples with high resolution. We designed a convolutional neural network to capture the structure patterns in human colon OCT images. The network is trained and tested using around 26,000 OCT images acquired from 20 tumor areas, 16 benign areas, and 6 other abnormal areas. Results: The trained network successfully detected patterns that identify normal and neoplastic colorectal tissue. Experimental diagnoses predicted by the PR-OCT system were compared to the known histologic findings and quantitatively evaluated. A sensitivity of 100% and specificity of 99.7% can be reached. Further, the area under the receiver operating characteristic (ROC) curves (AUC) of 0.998 is achieved. Conclusions: Our results demonstrate that PR-OCT can be used to give an accurate real-time computer-aided diagnosis of colonic neoplastic mucosa. Future development of this system as an "optical biopsy" tool to assist doctors in real-time for early mucosal neoplasms screening and treatment evaluation following initial oncologic therapy is planned.

Mief1 augments thyroid cell dysfunction and apoptosis through inhibiting AMPK-PTEN signaling pathway

Objective: Inflammation-mediated thyroid cell dysfunction and apoptosis increases the like-hood of hypothyroidism.Aim: Our aim in the present study is to explore the role of mitochondrial elongation factor 1 (Mief1) in thyroid cell dysfunction induced by TNFα.Materials and methods: Different doses of TNFα were used to incubate with thyroid cells in vitro. The survival rate, apoptotic index and proliferation capacity of thyroid cells were measured. Cellular energy metabolism and endoplasmic reticulum function related to protein synthesis were detected.Results: In response to TNFα treatment, the levels of Mief1 were increased, coinciding with a drop in the viability of thyroid cells in vitro. Loss of Mief1 attenuates TNFα-induced cell death through reducing the ratio of cell apoptosis. Further, we found that Mief1 deletion reversed cell energy metabolism and this effect was attributable to mitochondrial protection. Mief1 knockdown sustained mitochondrial membrane potential and reduced mitochondrial ROS overproduction. In addition, Mief1 knockdown also reduced endoplasmic reticulum stress, as evidenced by decreased levels of Chop and Caspase-12. Finally, our data verified that TNFα treatment inhibited the activity of AMPK-PTEN pathway whereas Mief1 deletion reversed the activity of AMPK and thus promoted the upregulation of PTEN. However, inhibition of AMPK-PTEN pathways could abolish the beneficial effects exerted by Mief1 deletion on thyroid cells damage and dysfunction.Conclusions: Altogether, our data indicate that immune abnormality-mediated thyroid cell dysfunction and death are alleviated by Mief1 deletion possible driven through reversing the activity of AMPK-PTEN pathways.

Advances in technologies for cervical cancer detection in low-resource settings

Introduction: Cervical cancer mortality rates remain high in low- and middle-income countries (LMICs) and other medically underserved areas due to challenges with implementation and sustainability of routine screening, accurate diagnosis, and early treatment of preinvasive lesions. Areas covered: In this review, we first discuss the standard of care for cervical cancer screening and diagnosis in high- and low-resource settings, biomarkers that correlate to cervical precancer and cancer, and needs for new tests. We review technologies for screening and diagnosis with a focus on tests that are already in use in LMICs or have the potential to be adapted for use in LMICs. Finally, we provide perspectives on the next five years of technology development for improved cervical cancer screening and diagnosis in LMICs. Expert opinion: Innovation toward improved molecular and imaging tests is needed to enable effective, affordable see-and-treat approaches to detect and treat cervical precancer in a single visit. Current molecular tests remain too complex and/or costly for widespread use. Especially with imaging tests, decision support may improve performance of new technologies.

Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue

OBJECTIVE

Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge for clinical adoption, however, is the steep learning curve clinicians need to overcome to interpret OCM images. Developing an intelligent technique for computer-aided diagnosis (CADx) to accurately interpret OCM images will facilitate clinical adoption of the technology and improve patient care.

METHODS

497 high-resolution three-dimensional (3-D) OCM volumes (600 cross-sectional images each) were collected from 159 ex vivo specimens of 92 female patients. OCM image features were extracted using a convolutional neural network (CNN) model, concatenated with patient information [e.g., age and human papillomavirus (HPV) results], and classified using a support vector machine classifier. Ten-fold cross-validations were utilized to test the performance of the CADx method in a five-class classification task and a binary classification task.

RESULTS

An 88.3 ± 4.9% classification accuracy was achieved for five fine-grained classes of cervical tissue, namely normal, ectropion, low-grade and high-grade squamous intraepithelial lesions (LSIL and HSIL), and cancer. In the binary classification task [low-risk (normal, ectropion, and LSIL) versus high-risk (HSIL and cancer)], the CADx method achieved an area-under-the-curve value of 0.959 with an 86.7 ± 11.4% sensitivity and 93.5 ± 3.8% specificity.

CONCLUSION

The proposed deep-learning-based CADx method outperformed four human experts. It was also able to identify morphological characteristics in OCM images that were consistent with histopathological interpretations.

SIGNIFICANCE

Label-free OCM imaging, combined with deep-learning-based CADx methods, holds a great promise to be used in clinical settings for the effective screening and diagnosis of cervical diseases.