MR water quantitative priors improves the accuracy of optical breast imaging

Systematic study of the effect of ultrasound gel on the performances of time-domain diffuse optics and diffuse correlation spectroscopy

Recently, multimodal imaging has gained an increasing interest in medical applications thanks to the inherent combination of strengths of the different techniques. For example, diffuse optics is used to probe both the composition and the microstructure of highly diffusive media down to a depth of few centimeters, but its spatial resolution is intrinsically low. On the other hand, ultrasound imaging exhibits the higher spatial resolution of morphological imaging, but without providing solid constitutional information. Thus, the combination of diffuse optical imaging and ultrasound may improve the effectiveness of medical examinations, e.g. for screening or diagnosis of tumors. However, the presence of an ultrasound coupling gel between probe and tissue can impair diffuse optical measurements like diffuse optical spectroscopy and diffuse correlation spectroscopy, since it may provide a direct path for photons between source and detector. A systematic study on the effect of different ultrasound coupling fluids was performed on tissue-mimicking phantoms, confirming that a water-clear gel can produce detrimental effects on optical measurements when recovering absorption/reduced scattering coefficients from time-domain spectroscopy acquisitions as well as particle Brownian diffusion coefficient from diffuse correlation spectroscopy ones. On the other hand, we show the suitability for optical measurements of other types of diffusive fluids, also compatible with ultrasound imaging.

Collagen Complexity Spatially Defines Microregions of Total Tissue Pressure in Pancreatic Cancer

The poor efficacy of systemic cancer therapeutics in pancreatic ductal adenocarcinoma (PDAC) is partly attributed to deposition of collagen and hyaluronan, leading to interstitial hypertension collapsing blood and lymphatic vessels, limiting drug delivery. The intrinsic micro-regional interactions between hyaluronic acid (HA), collagen and the spatial origins of mechanical stresses that close off blood vessels was investigated here. Multiple localized pressure measurements were analyzed with spatially-matched histochemical images of HA, collagen and vessel perfusion. HA is known to swell, fitting a linear elastic model with total tissue pressure (TTP) increasing above interstitial fluid pressure (IFP) directly with collagen content. However, local TTP appears to originate from collagen area fraction, as well as increased its entropy and fractal dimension, and morphologically appears to be maximized when HA regions are encapsulated by collagen. TTP was inversely correlated with vascular patency and verteporfin uptake, suggesting interstitial hypertension results in vascular compression and decreased molecular delivery in PDAC. Collagenase injection led to acute decreases in total tissue pressure and increased drug perfusion. Large microscopic variations in collagen distributions within PDAC leads to microregional TPP values that vary on the hundred micron distance scale, causing micro-heterogeneous limitations in molecular perfusion, and narrows viable treatment regimes for systemically delivered therapeutics.

Sensitivity of MRI-guided near-infrared spectroscopy clinical breast exam data and its impact on diagnostic performance

In this study, data from breast MRI-guided near infrared spectroscopy (NIRS) exams delivered to 44 patients scheduled for surgical resection (ending in 16 benign and 28 malignant diagnoses) were analyzed using a spatial sensitivity metric to quantify the adequacy of the optical measurements for interrogating the tumor region of interest, as derived from the concurrent MRI scan. Along with positional sensitivity, the incorporation of spectral priors and the selection of an appropriate regularization parameter in the image reconstruction were considered, and found to influence the diagnostic accuracy of the recovered images. Once optimized, the MRI/NIRS data was able to differentiate the malignant from benign lesions through both total hemoglobin (p = 0.0037) and tissue optical index (p = 0.00019), but required the relative spatial sensitivity of the optical measurement data to each lesion to be above 1%. Spectral constraints implemented during the reconstruction were required to obtain statistically significant diagnostic information from images of H2O, lipids, and Tissue Optical Index (TOI). These results confirm the need for optical systems that have homogenous spatial coverage of the breast while still being able to accommodate the normal range of breast sizes.

Implicit and explicit prior information in near-infrared spectral imaging: accuracy, quantification and diagnostic value

Near-infrared spectroscopy (NIRS) of tissue provides quantification of absorbers, scattering and luminescent agents in bulk tissue through the use of measurement data and assumptions. Prior knowledge can be critical about things such as (i) the tissue shape and/or structure, (ii) spectral constituents, (iii) limits on parameters, (iv) demographic or biomarker data, and (v) biophysical models of the temporal signal shapes. A general framework of NIRS imaging with prior information is presented, showing that prior information datasets could be incorporated at any step in the NIRS process, with the general workflow being: (i) data acquisition, (ii) pre-processing, (iii) forward model, (iv) inversion/reconstruction, (v) post-processing, and (vi) interpretation/diagnosis. Most of the development in NIRS has used ad hoc or empirical implementations of prior information such as pre-measured absorber or fluorophore spectra, or tissue shapes as estimated by additional imaging tools. A comprehensive analysis would examine what prior information maximizes the accuracy in recovery and value for medical diagnosis, when implemented at separate stages of the NIRS sequence. Individual applications of prior information can show increases in accuracy or improved ability to estimate biochemical features of tissue, while other approaches may not. Most beneficial inclusion of prior information has been in the inversion/reconstruction process, because it solves the mathematical intractability. However, it is not clear that this is always the most beneficial stage.