Optical tomography method that accounts for tilted chest wall in breast imaging

Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall

SIGNIFICANCE

In general, image reconstruction methods used in diffuse optical tomography (DOT) are based on diffusion approximation, and they consider the breast tissue as a homogenous, semi-infinite medium. However, the semi-infinite medium assumption used in DOT reconstruction is not valid when the chest wall is underneath the breast tissue.

AIM

We aim to reduce the chest wall's effect on the estimated average optical properties of breast tissue and obtain accurate forward model for DOT reconstruction.

APPROACH

We propose a deep learning-based neural network approach where a convolution neural network (CNN) is trained to simultaneously obtain accurate optical property values for both the breast tissue and the chest wall.

RESULTS

The CNN model shows great promise in reducing errors in estimating the optical properties of the breast tissue in the presence of a shallow chest wall. For patient data, the CNN model predicted the breast tissue optical absorption coefficient, which was independent of chest wall depth.

CONCLUSIONS

Our proposed method can be readily used in DOT and diffuse spectroscopy measurements to improve the accuracy of estimated tissue optical properties.

Effect and correction of optode coupling errors in breast imaging using diffuse optical tomography

In diffuse optical tomography (DOT) and spectroscopy (DOS) using handheld probes, tissue curvature can cause bad fiber-to-tissue contact. Understanding and minimizing image artifacts caused by these coupling errors would significantly improve DOT and DOS image quality. In this work, we utilized Monte Carlo simulations and experiments with gelatin-Intralipid phantoms to systematically study the influence of source or detector (optode) coupling errors. Optode coupling errors can increase the amplitude and decrease the phase of the measured diffuse reflectance, creating artifacts in the reconstructed absorption maps, such as hot spots on the edges. We propose an outlier removal algorithm that can correct these image artifacts, and we demonstrate its performance using simulations, phantom experiments, and breast patient data acquired with bad probe contact due to a dense or small breast. Further, we designed and implemented a new resistance-type thin-film force sensor array that provides real-time optode coupling feedback and guides the outlier removal to minimize optode coupling errors. Our approaches and study results have significant implications for reducing image artifacts arising from handheld probes, which are commonly used with mobile and wearable DOT and DOS devices.

A Brief Review on Breast Carcinoma and Deliberation on Current Non Invasive Imaging Techniques for Detection

BACKGROUND

Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival.

DISCUSSION

This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.

CONCLUSION

This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.

Near-Infrared Diffuse Optical Imaging for Early Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy: A Comparative Study Using 18F-FDG PET/CT

Diffuse optical spectroscopic imaging (DOSI) is used as an indicator of tumor blood volume quantified by tissue hemoglobin concentrations. We aimed to determine whether early changes in tumor total hemoglobin (tHb) concentration can predict a pathologic complete response (pCR) to neoadjuvant chemotherapy in patients with operable breast cancer, and we compared the predictive value of pCR between DOSI and (18)F-FDG PET combined with CT.

METHODS

Of the 100 patients enrolled, 84 patients were prospectively evaluated for primary objective analysis. Sixty-four of the patients underwent both sequential DOSI scans at baseline after their first and second chemotherapy courses and (18)F-FDG PET/CT at baseline and after their second chemotherapy course. The mean tHb (tHbmean) concentration and SUVmax of the lesion were measured using DOSI and (18)F-FDG PET/CT, respectively, and the percentage change in tHbmean (∆tHbmean) and change in SUVmax (∆SUVmax) were calculated. We compared the diagnostic performances of DOSI and (18)F-FDG PET/CT for predicting pCR via the analysis of the receiver-operating-characteristic curves.

RESULTS

pCR was achieved in 16 patients, and neoadjuvant chemotherapy caused a significant reduction of ∆tHbmean in pCR compared with non-pCR after the 2 chemotherapy courses. When the tentative ∆tHbmean cutoff values after the first and second courses were used, the ability to predict pCR was as follows: 81.2% sensitivity/47.0% specificity and 93.7% sensitivity/47.7% specificity, respectively. Comparison of the diagnostic performances of DOSI and (18)F-FDG PET/CT revealed areas under the curve of 0.69 and 0.75 of ∆tHbmean after the first and second courses, respectively, which were lower than those of ∆SUVmax (0.90).

CONCLUSION

DOSI predicted pCR in patients with breast cancer with moderate accuracy. The diagnostic performance of DOSI was inferior to that of the early metabolic response as monitored by (18)F-FDG PET/CT.

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography

A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach.

Diffuse optical tomography in the presence of a chest wall

Diffuse optical tomography (DOT) has been employed to derive spatial maps of physiologically important chromophores in the human breast, but the fidelity of these images is often compromised by boundary effects such as those due to the chest wall. We explore the image quality in fast, data-intensive analytic and algebraic linear DOT reconstructions of phantoms with subcentimeter target features and large absorptive regions mimicking the chest wall. Experiments demonstrate that the chest wall phantom can introduce severe image artifacts. We then show how these artifacts can be mitigated by exclusion of data affected by the chest wall. We also introduce and demonstrate a linear algebraic reconstruction method well suited for very large data sets in the presence of a chest wall.

Artifact reduction method in ultrasound-guided diffuse optical tomography using exogenous contrast agents

In diffuse optical tomography (DOT), a typical perturbation approach requires two sets of measurements obtained at the lesion breast (lesion or target site) and a contra-lateral location of the normal breast (reference site) for image reconstruction. For patients who have a small amount of breast tissue, the chest-wall underneath the breast tissue at both sites affects the imaging results. In this group of patients, the perturbation, which is the difference between measurements obtained at the lesion and reference sites, may include the information of background mismatch which can generate artifacts or affect the reconstructed quantitative absorption coefficient of the lesion. Also, for patients who have a single breast due to prior surgery, the contra-lateral reference is not available. To improve the DOT performance or overcome its limitation, we introduced a new method based on an exogenous contrast agent and demonstrate its performance using animal models. Co-registered ultrasound was used to guide the lesion localization. The results have shown that artifacts caused by background mismatch can be reduced significantly by using this new method.