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1.
Biomed Opt Express ; 11(4): 2052-2072, 2020 Apr 01.
Article in English | MEDLINE | ID: mdl-32341866

ABSTRACT

The development of a multimodal optical imaging system is presented that integrates endogenous fluorescence and diffuse reflectance spectroscopy with single-wavelength spatial frequency domain imaging (SFDI) and surface profilometry. The system images specimens at visible wavelengths with a spatial resolution of 70 µm, a field of view of 25 cm2 and a depth of field of ∼1.5 cm. The results of phantom experiments are presented demonstrating the system retrieves absorption and reduced scattering coefficient maps using SFDI with <6% reconstruction errors. A phase-shifting profilometry technique is implemented and the resulting 3-D surface used to compute a geometric correction ensuring optical properties reconstruction errors are maintained to <6% in curved media with height variations <20 mm. Combining SFDI-computed optical properties with data from diffuse reflectance spectra is shown to correct fluorescence using a model based on light transport in tissue theory. The system is used to image a human prostate, demonstrating its ability to distinguish prostatic tissue (anterior stroma, hyperplasia, peripheral zone) from extra-prostatic tissue (urethra, ejaculatory ducts, peri-prostatic tissue). These techniques could be integrated in robotic-assisted surgical systems to enhance information provided to surgeons and improve procedural accuracy by minimizing the risk of damage to extra-prostatic tissue during radical prostatectomy procedures and eventually detect residual cancer.

2.
J Biomed Opt ; 20(3): 036014, 2015 03.
Article in English | MEDLINE | ID: mdl-25793562

ABSTRACT

Obtaining accurate quantitative information on the concentration and distribution of fluorescent markers lying at a depth below the surface of optically turbid media, such as tissue, is a significant challenge. Here, we introduce a fluorescence reconstruction technique based on a diffusion light transport model that can be used during surgery, including guiding resection of brain tumors, for depth-resolved quantitative imaging of near-infrared fluorescent markers. Hyperspectral fluorescence images are used to compute a topographic map of the fluorophore distribution, which yields structural and optical constraints for a three-dimensional subsequent hyperspectral diffuse fluorescence reconstruction algorithm. Using the model fluorophore Alexa Fluor 647 and brain-like tissue phantoms, the technique yielded estimates of fluorophore concentration within ±25% of the true value to depths of 5 to 9 mm, depending on the concentration. The approach is practical for integration into a neurosurgical fluorescence microscope and has potential to further extend fluorescence-guided resection using objective and quantified metrics of the presence of residual tumor tissue.


Subject(s)
Algorithms , Brain Neoplasms/diagnostic imaging , Optical Imaging/methods , Brain Neoplasms/chemistry , Brain Neoplasms/surgery , Fluorescent Dyes/analysis , Humans , Image Processing, Computer-Assisted , Neoplasm, Residual , Phantoms, Imaging , Sensitivity and Specificity , Spectrometry, Fluorescence , Spectroscopy, Near-Infrared
3.
World J Gastroenterol ; 18(32): 4270-7, 2012 Aug 28.
Article in English | MEDLINE | ID: mdl-22969189

ABSTRACT

AIM: To investigate the performance of a new software-based colonoscopy quality assessment system. METHODS: The software-based system employs a novel image processing algorithm which detects the levels of image clarity, withdrawal velocity, and level of the bowel preparation in a real-time fashion from live video signal. Threshold levels of image blurriness and the withdrawal velocity below which the visualization could be considered adequate have initially been determined arbitrarily by review of sample colonoscopy videos by two experienced endoscopists. Subsequently, an overall colonoscopy quality rating was computed based on the percentage of the withdrawal time with adequate visualization (scored 1-5; 1, when the percentage was 1%-20%; 2, when the percentage was 21%-40%, etc.). In order to test the proposed velocity and blurriness thresholds, screening colonoscopy withdrawal videos from a specialized ambulatory colon cancer screening center were collected, automatically processed and rated. Quality ratings on the withdrawal were compared to the insertion in the same patients. Then, 3 experienced endoscopists reviewed the collected videos in a blinded fashion and rated the overall quality of each withdrawal (scored 1-5; 1, poor; 3, average; 5, excellent) based on 3 major aspects: image quality, colon preparation, and withdrawal velocity. The automated quality ratings were compared to the averaged endoscopist quality ratings using Spearman correlation coefficient. RESULTS: Fourteen screening colonoscopies were assessed. Adenomatous polyps were detected in 4/14 (29%) of the collected colonoscopy video samples. As a proof of concept, the Colometer software rated colonoscope withdrawal as having better visualization than the insertion in the 10 videos which did not have any polyps (average percent time with adequate visualization: 79% ± 5% for withdrawal and 50% ± 14% for insertion, P < 0.01). Withdrawal times during which no polyps were removed ranged from 4-12 min. The median quality rating from the automated system and the reviewers was 3.45 [interquartile range (IQR), 3.1-3.68] and 3.00 (IQR, 2.33-3.67) respectively for all colonoscopy video samples. The automated rating revealed a strong correlation with the reviewer's rating (ρ coefficient= 0.65, P = 0.01). There was good correlation of the automated overall quality rating and the mean endoscopist withdrawal speed rating (Spearman r coefficient= 0.59, P = 0.03). There was no correlation of automated overall quality rating with mean endoscopists image quality rating (Spearman r coefficient= 0.41, P = 0.15). CONCLUSION: The results from a novel automated real-time colonoscopy quality feedback system strongly agreed with the endoscopists' quality assessments. Further study is required to validate this approach.


Subject(s)
Colonoscopy/methods , Computer Systems/standards , Diagnosis, Computer-Assisted/methods , Early Detection of Cancer/methods , Software/standards , Adenomatous Polyps/diagnosis , Algorithms , Colonic Neoplasms/diagnosis , Humans , Pilot Projects , Quality Assurance, Health Care , Reproducibility of Results
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