A mobile-phone based high-resolution microendoscope to image cervical precancer

Ultracompact fluorescence smartphone attachment using built-in optics for protoporphyrin-IX quantification in skin

Smartphone-based fluorescence imaging systems have the potential to provide convenient quantitative image guidance at the point of care. However, common approaches have required the addition of complex optical attachments, which reduce translation potential. In this study, a simple clip-on attachment appropriate for fluorescence imaging of protoporphyrin-IX (PpIX) in skin was designed using the built-in light source and ultrawide camera sensor of a smartphone. Software control for image acquisition and quantitative analysis was developed using the 10-bit video capability of the phone. Optical performance was characterized using PpIX in liquid tissue phantoms and endogenously produced PpIX in mice and human skin. The proposed system achieves a very compact form factor (<30 cm3) and can be readily fabricated using widely available low-cost materials. The limit of detection of PpIX in optical phantoms was <10 nM, with good signal linearity from 10 to 1000 nM (R2 >0.99). Both murine and human skin imaging verified that in vivo PpIX fluorescence was detected within 1 hour of applying aminolevulinic acid (ALA) gel. This ultracompact handheld system for quantification of PpIX in skin is well-suited for dermatology clinical workflows. Due to its simplicity and form factor, the proposed system can be readily adapted for use with other smartphone devices and fluorescence imaging applications. Hardware design and software for the system is made freely available on GitHub (https://github.com/optmed/CompactFluorescenceCam).

Smartphone-based imaging systems for medical applications: a critical review

SIGNIFICANCE

Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed.

AIM

Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances.

APPROACH

First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed.

RESULTS

The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo, multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications.

CONCLUSIONS

A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forward.

Survival outcomes of neoadjuvant chemotherapy-related strategies compared with concurrent chemoradiotherapy for locally advanced cervical cancer: a meta-analysis of randomized controlled trials

PURPOSE

The survival benefits of neoadjuvant chemotherapy (NAC) compared with those of concurrent chemoradiotherapy (CRT) for locally advanced cervical cancer (LACC) patients remain uncertain. Meta-analysis was used to compare NAC and CRT.

METHODS

A systematic search was performed up to 9 September 2020. Survival outcomes were analyzed based on event frequency or hazard ratios (HRs). Multilevel mixed-effects logistic regression was applied to analyze the effect of regimen variables on survival outcomes.

RESULTS

Analysis based on Cox regression showed that CRT was better than NAC + radical hysterectomy (RT) (HR 1.25; 95% confidence interval (CI)) 1.02-1.54; p = 0.034) in terms of overall survival (OS). According to multilevel mixed-effects model analysis comparing NAC + RT and CRT, LACC patients who used cisplatin instead of carboplatin had a better Progression-free survival (PFS) (odds ratio (OR) 1.54; 95% CI 1.08-2.20; p = 0.016). When NAC + CRT and CRT were compared, gemcitabine administration was associated with a decrease in PFS (OR 0.47; 95% CI 0.22-0.99; p = 0.047). Increased doses of cisplatin and paclitaxel were associated with survival improvement.

CONCLUSION

Based on traditional meta-analysis, CRT was better than NAC + RT in terms of OS. Carboplatin instead of cisplatin as part of the NAC + RT strategy or gemcitabine use in NAC + CRT may not be a good choice. An increased total dosage of paclitaxel and/or cisplatin as part of NAC + CRT and CRT strategies may improve the survival outcome of LACC patients.

Screening test accuracy of portable devices that can be used to perform colposcopy for detecting CIN2+ in low- and middle-income countries: a systematic review and meta-analysis

BACKGROUND

Portable devices that can be used to perform colposcopy may improve cervical cancer screening in low- and middle-income countries (LMIC) where access to colposcopy is limited. The objective of this study was to systematically review the diagnostic test accuracy (DTA) of these devices for the detection of cervical intraepithelial neoplasia grade 2 or higher (CIN2+).

METHODS

In accordance with our protocol (Prospero CRD42018104286), we searched Embase, Medline and the Cochrane Controlled Register of Trials up to 9/2019. We included DTA studies, which investigated portable devices with moderate-to-high optical magnification (≥ 6×) for colposcopy, as described in the manual for Colposcopy and Treatment by the International Agency for Research on Cancer, with a histopathological reference standard. We used the QUADAS-2 tool to assess study quality. We examined results for sensitivity and specificity in paired forest plots, stratified by stages in the clinical pathway. We pooled estimates of test accuracy for the index test, used as an add-on to other tests, using a bivariate random-effect model.

RESULTS

We screened 1737 references and assessed 239 full-text articles for eligibility. Five single-gate DTA studies, including 2693 women, met the inclusion criteria. Studies evaluated two devices (Gynocular™ and Pocket) at different stages of the screening pathway. In three studies, which used the index test in an add-on capacity in 1273 women, we found a pooled sensitivity of 0.79 (95% CI 0.55-0.92) and specificity of 0.83 (95% CI 0.59-0.94). The main sources of bias were partial verification, incorporation and classification bias.

CONCLUSION

Few studies have evaluated portable devices able to perform colposcopy, so their accuracy for the detection of CIN2+ remains uncertain. Future studies should include patient-relevant and long-term outcomes, including missed cases, overtreatment, residual and recurrent disease. To meet the challenge of eliminating cervical cancer in LMIC, methods for visual assessment of the cervix need urgent redress.

Expert consensus from the Italian Society for Colposcopy and Cervico-Vaginal Pathology (SICPCV) for colposcopy and outpatient surgery of the lower genital tract during the COVID-19 pandemic

In the context of the COVID-19 pandemic, patients need to be evaluated within 2-4 weeks in the following cases: cytology result of "squamous cell carcinoma," "atypical glandular cells, favor neoplastic," "endocervical adenocarcinoma in situ," or "adenocarcinoma"; histopathological diagnosis of suspected invasion from cervical/vaginal biopsy, or invasive disease after a cervical excision procedure, vaginal excision, or vulvar biopsy/excision; sudden onset of strongly suggestive symptoms for malignancy. Digital imaging technologies represent an important opportunity during the COVID-19 pandemic to share colposcopic images with reference centers, with the aim of avoiding any concentration of patients. All patients must undergo screening for COVID-19 exposure and should wear a surgical mask. A high-efficiency filter smoke evacuation system is mandatory to remove surgical smoke. Electrosurgical instruments should be set at the lowest possible power and not be used for long continuous periods to reduce the amount of surgical smoke. The following personal protective equipment should be used: sterile fluid-repellant surgical gloves, an underlying pair of gloves, eye protection, FFP3 mask, surgical cap, and gown. The colposcope should be protected by a disposable transparent cover. A protective lens that must be disinfected after each use should be applied. The use of a video colposcope should be preferred.

Quantitative Screening of Cervical Cancers for Low-Resource Settings: Pilot Study of Smartphone-Based Endoscopic Visual Inspection After Acetic Acid Using Machine Learning Techniques

BACKGROUND

Approximately 90% of global cervical cancer (CC) is mostly found in low- and middle-income countries. In most cases, CC can be detected early through routine screening programs, including a cytology-based test. However, it is logistically difficult to offer this program in low-resource settings due to limited resources and infrastructure, and few trained experts. A visual inspection following the application of acetic acid (VIA) has been widely promoted and is routinely recommended as a viable form of CC screening in resource-constrained countries. Digital images of the cervix have been acquired during VIA procedure with better quality assurance and visualization, leading to higher diagnostic accuracy and reduction of the variability of detection rate. However, a colposcope is bulky, expensive, electricity-dependent, and needs routine maintenance, and to confirm the grade of abnormality through its images, a specialist must be present. Recently, smartphone-based imaging systems have made a significant impact on the practice of medicine by offering a cost-effective, rapid, and noninvasive method of evaluation. Furthermore, computer-aided analyses, including image processing-based methods and machine learning techniques, have also shown great potential for a high impact on medicinal evaluations.

OBJECTIVE

In this study, we demonstrate a new quantitative CC screening technique and implement a machine learning algorithm for smartphone-based endoscopic VIA. We also evaluated the diagnostic performance and practicability of the approach based on the results compared to the gold standard and from physicians' interpretation.

METHODS

A smartphone-based endoscope system was developed and applied to the VIA screening. A total of 20 patients were recruited for this study to evaluate the system. Overall, five were healthy, and 15 were patients who had shown a low to high grade of cervical intraepithelial neoplasia (CIN) from both colposcopy and cytology tests. Endoscopic VIA images were obtained before a loop electrosurgical excision procedure for patients with abnormal tissues, and their histology tissues were collected. Endoscopic VIA images were assessed by four expert physicians relative to the gold standard of histopathology. Also, VIA features were extracted from multiple steps of image processing techniques to find the differences between abnormal (CIN2+) and normal (≤CIN1). By using the extracted features, the performance of different machine learning classifiers, such as k-nearest neighbors (KNN), support vector machine, and decision tree (DT), were compared to find the best algorithm for VIA. After determining the best performing classifying model, it was used to evaluate the screening performance of VIA.

RESULTS

An average accuracy of 78%, with a Cohen kappa of 0.571, was observed for the evaluation of the system by four physicians. Through image processing, 240 sliced images were obtained from the cervicogram at each clock position, and five features of VIA were extracted. Among the three models, KNN showed the best performance for finding VIA within holdout 10-fold cross-validation, with an accuracy of 78.3%, area under the curve of 0.807, a specificity of 80.3%, and a sensitivity of 75.0%, respectively. The trained model performed using an unprovided data set resulted in an accuracy of 80.8%, specificity of 84.1%, and sensitivity of 71.9%. Predictions were visualized with intuitive color labels, indicating the normal/abnormal tissue using a circular clock-type segmentation. Calculating the overlapped abnormal tissues between the gold standard and predicted value, the KNN model overperformed the average assessments of physicians for finding VIA.

CONCLUSIONS

We explored the potential of the smartphone-based endoscopic VIA as an evaluation technique and used the cervicogram to evaluate normal/abnormal tissue using machine learning techniques. The results of this study demonstrate its potential as a screening tool in low-resource settings.

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.