Interferometric differentiation between resonant Coherent Anti-Stokes Raman Scattering and nonresonant four-wave-mixing processes

A major impediment of using Coherent Anti-Stokes Raman Scattering to identify biological molecules is that the illumination levels required to produce a measurable signal often also produce significant nonresonant background from the medium, especially from water, that is not specific to the resonance being investigated. We present a method of using nonlinear interferometry to measure the temporal shape of the anti-Stokes signal to differentiate which components are resonant and nonresonant. This method is easily adaptable to most existing pulsed CARS illumination methods and should allow for distinguishing resonant CARS when using higher energy pulses. By examining the differences between signals produced by acetone and water, we show that the resonant and nonresonant signals can be clearly differentiated.Comment: 8 pages, 4 figure

The impact of a high‐definition multileaf collimator for spine SBRT

PurposeAdvanced radiotherapy delivery systems designed for high‐dose, high‐precision treatments often come equipped with high‐definition multi‐leaf collimators (HD‐MLC) aimed at more finely shaping radiation dose to the target. In this work, we study the effect of a high definition MLC on spine stereotactic body radiation therapy (SBRT) treatment plan quality and plan deliverability.Methods and MaterialsSeventeen spine SBRT cases were planned with VMAT using a standard definition MLC (M120), HD‐MLC, and HD‐MLC with an added objective to reduce monitor units (MU). M120 plans were converted into plans deliverable on an HD‐MLC using in‐house software. Plan quality and plan deliverability as measured by portal dosimetry were compared among the three types of plans.ResultsOnly minor differences were noted in plan quality between the M120 and HD‐MLC plans. Plans generated with the HD‐MLC tended to have better spinal cord sparing (3% reduction in maximum cord dose). HD‐MLC plans on average had 12% more MU and 55% greater modulation complexity as defined by an in‐house metric. HD‐MLC plans also had significantly degraded deliverability. Of the VMAT arcs measured, 94% had lower gamma passing metrics when using the HD‐MLC.ConclusionModest improvements in plan quality were noted when switching from M120 to HD‐MLC at the expense of significantly less accurate deliverability in some cases.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139989/1/acm212197.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139989/2/acm212197_am.pd

Automated quantification of aligned collagen for human breast carcinoma prognosis

Background: Mortality in cancer patients is directly attributable to the ability of cancer cells to metastasize to distant sites from the primary tumor. This migration of tumor cells begins with a remodeling of the local tumor microenvironment, including changes to the extracellular matrix and the recruitment of stromal cells, both of which facilitate invasion of tumor cells into the bloodstream. In breast cancer, it has been proposed that the alignment of collagen fibers surrounding tumor epithelial cells can serve as a quantitative image-based biomarker for survival of invasive ductal carcinoma patients. Specific types of collagen alignment have been identified for their prognostic value and now these tumor associated collagen signatures (TACS) are central to several clinical specimen imaging trials. Here, we implement the semi-automated acquisition and analysis of this TACS candidate biomarker and demonstrate a protocol that will allow consistent scoring to be performed throughout large patient cohorts. Methods: Using large field of view high resolution microscopy techniques, image processing and supervised learning methods, we are able to quantify and score features of collagen fiber alignment with respect to adjacent tumor-stromal boundaries. Results: Our semi-automated technique produced scores that have statistically significant correlation with scores generated by a panel of three human observers. In addition, our system generated classification scores that accurately predicted survival in a cohort of 196 breast cancer patients. Feature rank analysis reveals that TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction. Conclusion: These results demonstrate the utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries

Data for submission "Collagen organization of renal cell carcinoma differs between low and high grade tumors"

Sample: A human RCC tissue microarray (TMA) block was constructed by the Translational Research Initiatives in Pathology (TRIP) lab at the University of Wisconsin-Madison (UW-Madison). A section of 5um thickness was cut from the TMA block containing ~600um diameter tissue TMA cores. The section was then placed on a glass slide, stained with standard hematoxylin and eosin (H&E), and mounted under a #1.5 glass coverslip. Different tissue cores were from different patients. HE imaging: A bright field image of the entire H&E slide was collected with an Aperio CS2 Digital Pathology Scanner (Leica Biosystems) at 20x magnification. Each core of grade 1 and grade 4 was cropped to the size of 1520 pixels by 1520 pixels using Aperio ImageScope viewing software (Leica Biosystems). In total, 75 TMA cores were verified and annotated as grade 1 and 55 TMA cores as grade 4. Each core represents an individual patient. SHG imaging: All cores in this study were imaged with a custom built forward detection SHG microscope (Bredfeldt et al., 2014a). A MIRA 900 Ti: Sapphire laser (Coherent, Santa Clara, CA) was used to deliver 780 nm light to the sample using a 40x/1.25NA water immersion objective (Nikon, Melville, NY). No SHG signal was observed for five grade 1 cores and four grade 4 cores after navigating the system to at least 3 different fields of view on each core. Hence, in total, 70 TMA cores have SHG singal and annotated as grade1, 51 TMA cores as grade 4. To be noted, HE image and SHG image provided here are all original images and not co-registered.This repository contains datasets generated and/or analysed in the RCC project.This study was supported by the UW Department of Urology with additional funding from the UW Laboratory for Optical and Computational Instrumentation. We acknowledge funding support from the UW Institute for Clinical and Translational Research (ICTR) under award #UL1TR000427. We also acknowledge funding from NIH under grants R01 CA179556 (KWE) and U54DK104310 (KWE). The authors thank the UW Translational Research Initiatives in Pathology Laboratory, in part supported by the UW Department of Pathology and Laboratory Medicine and UWCCC grant P30 CA014520, for use of its facilities and services

Feasibility of the Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) System for Anesthesia Avoidance in Pediatric Patients: A Multicenter Trial.

PurposeThe Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) system was the first published radiation therapy (RT)-compatible system to reduce the need for pediatric anesthesia through video-based distraction. We evaluated the feasibility of AVATAR implementation and effects on anesthesia use, quality of life, and anxiety in a multicenter pediatric trial.Methods and materialsPediatric patients 3 to 10 years of age preparing to undergo RT at 10 institutions were prospectively enrolled. Children able to undergo at least 1 fraction of RT using AVATAR without anesthesia were considered successful (S). Patients requiring anesthesia for their entire treatment course were nonsuccessful (NS). The PedsQL3.0 Cancer Module (PedsQL) survey assessed quality of life and was administered to the patient and guardian at RT simulation, midway through RT, and at final treatment. The modified Yale Preoperative Anxiety Scale (mYPAS) assessed anxiety and was performed at the same 3 time points. Success was evaluated using the χ2 test. PedsQL and mYPAS scores were assessed using mixed effects models with time points evaluated as fixed effects and a random intercept on the subject.ResultsEighty-one children were included; median age was 7 years. AVATAR was successful at all 10 institutions and with photon and proton RT. There were 63 (78%) S patients; anesthesia was avoided for a median of 20 fractions per patient. Success differed by age (P = .04) and private versus public insurance (P < .001). Both patient (P = .008) and parent (P = .006) PedsQL scores significantly improved over the course of RT for patients aged 5 to 7. Anxiety in the treatment room decreased for both S and NS patients over RT course (P < .001), by age (P < .001), and by S versus NS patients (P < .001).ConclusionsIn this 10-center prospective trial, anesthesia avoidance with AVATAR was 78% in children aged 3 to 10 years, higher than among age-matched historical controls (49%; P < .001). AVATAR implementation is feasible across multiple institutions and should be further studied and made available to patients who may benefit from video-based distraction