ABSTRACT
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.
ABSTRACT
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response.
ABSTRACT
Vaginal tearing at childbirth is extremely common yet understudied despite the long-term serious consequences on women's health. The mechanisms of vaginal tearing remain unknown, and their knowledge could lead to the development of transformative prevention and treatment techniques for maternal injury. In this study, whole rat vaginas with pre-imposed elliptical tears oriented along the axial direction of the organs were pressurized using a custom-built inflation setup, producing large tear propagation. Large deformations of tears through propagation were analyzed, and nonlinear strains around tears were calculated using the digital image correlation technique. Second harmonic generation microscopy was used to examine collagen fiber organization in mechanically untested and tested vaginal specimens. Tears became increasingly circular under pressure, propagating slowly up to the maximum pressure and then more rapidly. Hoop strains were significantly larger than axial strains and displayed a region- and orientation-dependent response with tear propagation. Imaging revealed initially disorganized collagen fibers that aligned along the axial direction with increasing pressure. Fibers in the near-regions of tear tips aligned toward the hoop direction, hampering tear propagation. Changes in tear geometry, regional strains, and fiber orientation revealed the inherent toughening mechanisms of the vaginal tissue. STATEMENT OF SIGNIFICANCE: Women's reproductive health has historically been understudied despite alarming maternal injury and mortality rates in the world. Maternal injury and disability can be reduced by advancing our limited understanding of the large deformations experienced by women's reproductive organs. This manuscript presents, for the first time, the mechanics of tear propagation in vaginal tissue and changes to the underlying collagen microstructure near to and far from the tear. A novel inflation setup capable of maintaining the in vivo tubular geometry of the vagina while propagating a pre-imposed tear was developed. Toughening mechanisms of the vagina to propagation were examined through measurements of tear geometry, strain distributions, and reorientation of collagen fibers. This research draws from current advances in the engineering science and mechanics fields with the goal of improving maternal health care.
Subject(s)
Lacerations , Animals , Female , Rats , Rupture , Stress, Mechanical , VaginaABSTRACT
Convection-enhanced delivery (CED) is a method used to increase transport of therapeutics in and around brain tumors. CED works through locally applying a pressure differential to drive fluid flow throughout the tumor, such that convective forces dominate over diffusive transport. This allows therapies to bypass the blood brain barrier that would otherwise be too large or solely rely on passive diffusion. However, this also drives fluid flow out through the tumor bulk into surrounding brain parenchyma, which results in increased interstitial fluid (IF) flow, or fluid flow within extracellular spaces in the tissue. IF flow has been associated with altered transport of molecules, extracellular matrix rearrangement, and triggering of cellular motility through a number of mechanisms. Thus, the results of a simple method to increase drug delivery may have unintended consequences on tissue morphology. Clinically, prediction of dispersal of agents via CED is important to catheter design, placement, and implementation to optimize contact of tumor cells with therapeutic agent. Prediction software can aid in this problem, yet we wonder if there is a better way to predict therapeutic distribution based simply on IF flow pathways as determined from pre-intervention imaging. Overall, CED based therapy has seen limited success and we posit that integration and appreciation of altered IF flow may enhance outcomes. Thus, in this manuscript we both review the current state of the art in CED and IF flow mechanistic understanding and relate these two elements to each other in a clinical context.
