Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography.

PURPOSE: The purpose of the study was to assess the utility of tumor biomarkers, ultrasound (US) and US-guided diffuse optical tomography (DOT) in early prediction of breast cancer response to neoadjuvant therapy (NAT). METHODS: This prospective HIPAA compliant study was approved by the institutional review board. Forty one patients were imaged with US and US-guided DOT prior to NAT, at completion of the first three treatment cycles, and prior to definitive surgery from February 2017 to January 2020. Miller-Payne grading was used to assess pathologic response. Receiver operating characteristic curves (ROCs) were derived from logistic regression using independent variables, including: tumor biomarkers, US maximum diameter, percentage reduction of the diameter (%US), pretreatment maximum total hemoglobin concentration (HbT) and percentage reduction in HbT (%HbT) at different treatment time points. Resulting ROCs were compared using area under the curve (AUC). Statistical significance was tested using two-sided two-sample student t-test with P < 0.05 considered statistically significant. Logistic regression was used for ROC analysis. RESULTS: Thirty-eight patients (mean age = 47, range 24-71 years) successfully completed the study, including 15 HER2 + of which 11 were ER + ; 12 ER + or PR + /HER2-, and 11 triple negative. The combination of HER2 and ER biomarkers, %HbT at the end of cycle 1 (EOC1) and %US (EOC1) provided the best early prediction, AUC = 0.941 (95% CI 0.869-1.0). Similarly an AUC of 0.910 (95% CI 0.810-1.0) with %US (EOC1) and %HbT (EOC1) can be achieved independent of HER2 and ER status. The most accurate prediction, AUC = 0.974 (95% CI 0.933-1.0), was achieved with %US at EOC1 and %HbT (EOC3) independent of biomarker status. CONCLUSION: The combined use of tumor HER2 and ER status, US, and US-guided DOT may provide accurate prediction of NAT response as early as the completion of the first treatment cycle. CLINICAL TRIAL REGISTRATION NUMBER: NCT02891681. https://clinicaltrials.gov/ct2/show/NCT02891681 , Registration time: September 7, 2016.

Evaluation of Ovarian Cancer: Initial Application of Coregistered Photoacoustic Tomography and US.

Purpose To assess transvaginal coregistered photoacoustic tomography (PAT) and pulse-echo US for diagnosis of ovarian cancer based on functional parameters provided by PAT. Materials and Methods Between February 2017 and December 2017, 26 ovarian masses from 16 participants were successfully imaged in vivo by multispectral photoacoustic imaging, including nine invasive epithelial ovarian cancers (six serous carcinomas and three endometroid adenocarcinomas), three other tumors (two borderline serous tumors and one sex cord-stromal tumor), and 14 benign and normal (hereafter referred to as benign/normal) ovaries. The relative total hemoglobin concentration (rHbT) and mean oxygen saturation (sO2) shown at PAT were used to characterize the ovaries identified at US. Results The average rHbT was 1.9 times higher for invasive epithelial cancers than for the benign/normal ovaries (P = .01). Additionally, the rHbT distribution was extensive in invasive epithelial cancers, but was scattered in benign/normal ovaries. However, the rHbT of two borderline serous tumors and one stromal tumor was in the same range as that of benign/normal ovaries. The mean sO2 of invasive epithelial cancers, and of the borderline and stromal tumors, was 8.2% lower than that of benign/normal ovaries (P = .003). Discussion Invasive epithelial ovarian cancers showed higher and extensive tumor vascularity and lower oxygen saturation than benign and normal ovaries. Two borderline noninvasive serous and one stromal tumor showed low oxygen saturation compared with benign and normal ovaries. ©RSNA, 2018 Online supplemental material is available for this article.

Ultrasound-Guided Diffuse Optical Tomography for Predicting and Monitoring Neoadjuvant Chemotherapy of Breast Cancers: Recent Progress.

In this manuscript, we review the current progress of utilizing ultrasound-guided diffuse optical tomography (US-guided DOT) for predicting and monitoring neoadjuvant chemotherapy (NAC) outcomes of breast cancer patients. We also report the recent advance on optical tomography systems toward portable and robust clinical use at multiple clinical sites. The first patient who has been closely monitored before NAC, at day 2, day 8, end of first three cycles of NAC, and before surgery is given as an example to demonstrate the potential of US-guided DOT technique.

Optimized light delivery probe using ball lenses for co-registered photoacoustic and ultrasound endo-cavity subsurface imaging.

An optimized hand-held photoacoustic and ultrasound probe suitable for endo-cavity tumor subsurface imaging was designed and evaluated. Compared to previous designs, the prototype probe, consisting of four 1 mm multi-mode optical fibers attached with 1.5 mm diameter ball-shaped fiber tips sandwiched between a transvaginal ultrasound transducer and a custom-made sheath, demonstrated a higher light output and better beam homogeneity on tissue subsurface. The output power and fluence profile were simulated for different design parameters. A camera recorded fluence profiles through calibrated intralipid solution at various imaging depths. The light delivery efficiency was experimentally compared with and without the ball lenses, based on ex-vivo imaging of human colorectal cancer and in-vivo imaging of a palmar vein proximal to the human wrist. The simulations and experiments demonstrated that ball-shaped fiber tip design can achieve homogeneous fluence distribution on tissue subsurface with acceptable light output efficiency, suggesting its clinical potential for in-vivo endo-cavity imaging.

Classification of human ovarian cancer using functional, spectral, and imaging features obtained from in vivo photoacoustic imaging.

We report in this pilot study the diagnostic results of in vivo imaging of patients with ovarian lesions, using a co-registered photoacoustic and ultrasound (PAT/US) system. A total of 39 ovaries from 24 patients were imaged in vivo. PAT functional features, i.e., blood oxygen saturation (sO2) and relative total hemoglobin (rHbT), PAT image features, and PAT spectral features within a region of interest (ROI) in each ovarian tissue were extracted. To select the significant features, a t-test on each feature was performed, and the independent predictors were determined by evaluating correlation between each pair of predictors. To classify the ovarian lesions, we employed a generalized linear model (GLM) and a support vector machine (SVM). We used these classifiers first to distinguish benign/normal lesions from ovaries with invasive epithelial tumors and then to separate normal/benign lesions from all types of ovarian tumors. We developed classifiers once by inclusion of PAT functional features to assess the best diagnostic performance of the classifiers when multiple wavelengths data are available. Second time, we excluded the PAT functional features from the features set to evaluate the best diagnostic performance if only a single wavelength is available. Our results show that using functional features improves the classification performance, especially for distinguishing normal/benign ovarian lesions from all types of tumors. In this case, an area under ROC curve (AUC) of 0.92, 0.93 of testing data was achieved using a GLM and SVM classifier when functional features were included in the feature set while excluding these features resulted in an AUC of 0.89, 0.92, respectively.

Co-registered photoacoustic and ultrasound imaging of human colorectal cancer.

Colorectal cancer is the second most common malignancy diagnosed globally. Critical gaps exist in diagnostic and surveillance imaging modalities for colorectal neoplasia. Although prior studies have demonstrated the capability of photoacoustic imaging techniques to differentiate normal from neoplastic tissue in the gastrointestinal tract, evaluation of deep tissue with a fast speed and a large field of view remains limited. To investigate the ability of photoacoustic technology to image deeper tissue, we conducted a pilot study using a real-time co-registered photoacoustic tomography (PAT) and ultrasound (US) system. A total of 23 ex vivo human colorectal tissue samples were imaged immediately after surgical resection. Co-registered photoacoustic images of malignancies showed significantly increased PAT signal compared to normal regions of the same sample. The quantitative relative total hemoglobin (rHbT) concentration computed from four optical wavelengths, the spectral features, such as the mean spectral slope, and 0.5-MHz intercept extracted from PAT and US spectral data, and image features, such as the first- and second-order statistics along with the standard deviation of the mean radon transform of PAT images, have shown statistical significance between untreated colorectal tumors and the normal tissue. Using either a logistic regression model or a support vector machine, the best set of parameters of rHbT and PAT intercept has achieved area-under-the-curve (AUC) values of 0.97 and 0.95 for both training and testing data sets, respectively, for prediction of histologically confirmed invasive carcinoma.

Compact ultrasound-guided diffuse optical tomography system for breast cancer imaging.

Near-infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response in patients with locally advanced breast cancers. The path toward commercialization of DOT techniques depends upon the improvement of robustness and user-friendliness of this technique in hardware and software. In this study, we introduce our recently developed ultrasound-guided DOT system, which has been improved in system compactness, robustness, and user-friendliness by custom-designed electronics, automated data preprocessing, and implementation of a new two-step reconstruction algorithm. The system performance has been tested with several sets of solid and blood phantoms and the results show accuracy in reconstructed absorption coefficients as well as blood oxygen saturation. A clinical example of a breast cancer patient, who was undergoing neoadjuvant chemotherapy, is given to demonstrate the system performance.

Improving breast cancer diagnosis by reducing chest wall effect in diffuse optical tomography.

We have developed the ultrasound (US)-guided diffuse optical tomography technique to assist US diagnosis of breast cancer and to predict neoadjuvant chemotherapy response of patients with breast cancer. The technique was implemented using a hand-held hybrid probe consisting of a coregistered US transducer and optical source and detector fibers which couple the light illumination from laser diodes and photon detection to the photomultiplier tube detectors. With the US guidance, diffused light measurements were made at the breast lesion site and the normal contralateral reference site which was used to estimate the background tissue optical properties for imaging reconstruction. However, background optical properties were affected by the chest wall underneath the breast tissue. We have analyzed data from 297 female patients, and results have shown statistically significant correlation between the fitted optical properties ( ? a and ? s ? ) and the chest wall depth. After subtracting the background ? a at each wavelength, the difference of computed total hemoglobin (tHb) between malignant and benign lesion groups has improved. For early stage malignant lesions, the area-under-the-receiver operator characteristic curve (AUC) has improved from 88.5% to 91.5%. For all malignant lesions, the AUC has improved from 85.3% to 88.1%. Statistical test has revealed the significant difference of the AUC improvements after subtracting background tHb values.

Diffuse optical tomography using semiautomated coregistered ultrasound measurements.

Diffuse optical tomography (DOT) has demonstrated huge potential in breast cancer diagnosis and treatment monitoring. DOT image reconstruction guided by ultrasound (US) improves the diffused light localization and lesion reconstruction accuracy. However, DOT reconstruction depends on tumor geometry provided by coregistered US. Experienced operators can manually measure these lesion parameters; however, training and measurement time are needed. The wide clinical use of this technique depends on its robustness and faster imaging reconstruction capability. This article introduces a semiautomated procedure that automatically extracts lesion information from US images and incorporates it into the optical reconstruction. An adaptive threshold-based image segmentation is used to obtain tumor boundaries. For some US images, posterior shadow can extend to the chest wall and make the detection of deeper lesion boundary difficult. This problem can be solved using a Hough transform. The proposed procedure was validated from data of 20 patients. Optical reconstruction results using the proposed procedure were compared with those reconstructed using extracted tumor information from an experienced user. Mean optical absorption obtained from manual measurement was 0.21±0.06 cm-1 for malignant and 0.12±0.06 cm-1 for benign cases, whereas for the proposed method it was 0.24±0.08 cm-1 and 0.12±0.05 cm-1, respectively.

Two step imaging reconstruction using truncated pseudoinverse as a preliminary estimate in ultrasound guided diffuse optical tomography.

Due to the correlated nature of diffused light, the problem of reconstructing optical properties using diffuse optical tomography (DOT) is ill-posed. US-, MRI- or x-ray-guided DOT approaches can reduce the total number of parameters to be estimated and improve optical reconstruction accuracy. However, when the target volume is large, the number of parameters to estimate can exceed the number of measurements, resulting in an underdetermined imaging model. In such cases, accurate image reconstruction is difficult and regularization methods should be employed to obtain a useful solution. In this manuscript, a simple two-step reconstruction method that can produce useful image estimates in DOT is proposed and investigated. In the first step, a truncated Moore-Penrose Pseudoinverse solution is computed to obtain a preliminary estimate of the image that can be reliably determined from the measured data; subsequently, this preliminary estimate is incorporated into the design of a penalized least squares estimator that is employed to compute the final image estimate. By use of phantom data, the proposed method was demonstrated to yield more accurate images than those produced by conventional reconstruction methods. The method was also evaluated with clinical data that included 10 benign and 10 malignant cases. The capability of reconstructing high contrast malignant lesions was demonstrated to be improved by use of the proposed method.

Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging.

A spatial frequency domain imaging (SFDI) system was developed for characterizing ex vivo human ovarian tissue using wide-field absorption and scattering properties and their spatial heterogeneities. Based on the observed differences between absorption and scattering images of different ovarian tissue groups, six parameters were quantitatively extracted. These are the mean absorption and scattering, spatial heterogeneities of both absorption and scattering maps measured by a standard deviation, and a fitting error of a Gaussian model fitted to normalized mean Radon transform of the absorption and scattering maps. A logistic regression model was used for classification of malignant and normal ovarian tissues. A sensitivity of 95%, specificity of 100%, and area under the curve of 0.98 were obtained using six parameters extracted from the SFDI images. The preliminary results demonstrate the diagnostic potential of the SFDI method for quantitative characterization of wide-field optical properties and the spatial distribution heterogeneity of human ovarian tissue. SFDI could be an extremely robust and valuable tool for evaluation of the ovary and detection of neoplastic changes of ovarian cancer.

An improved YEF-DCT based compression algorithm for video capsule endoscopy.

Video capsule endoscopy is a non-invasive technique to receive images of intestine for medical diagnostics. The main design challenges of endoscopy capsule are accruing and transmitting acceptable quality images by utilizing as less hardware and battery power as possible. In order to save wireless transmission power and bandwidth, an efficient image compression algorithm needs to be implemented inside the endoscopy electronic capsule. In this paper, an integer discrete-cosine-transform (DCT) based algorithm is presented that works on a low-complexity color-space specially designed for wireless capsule endoscopy application. First of all, thousands of human endoscopic images and video frames have been analyzed to identify special intestinal features present in those frames. Then a color space, referred as YEF, is used. The YEF converter is lossless and takes only a few adders and shift operation to implement. A low-cost quantization scheme with variable chroma sub-sampling options is also implemented to achieve higher compression. Comparing with the existing works, the proposed transform coding based compressor performs strongly with an average compression ratio of 85% and a high image quality index, peak-signal-to-noise ratio (PSNR) of 52 dB.