Both intensity- (IM) and frequency-modulation (FM) behavior of a directly modulated quantum cascade laser (QCL) are measured from 300 Hz to 1.7 GHz. Quantitative measurements of tuning coefficients has been performed and the transition from thermal- to electronic-tuning is clearly observed. A very specific FM behavior of QCLs has been identified which allows for optical quasi single sideband (SSB) modulation through current injection and has not been observed in directly modulated semiconductor lasers before. This predestines QCLs in applications where SSB is required, such as telecommunication or high speed spectroscopy. The experimental procedure and theoretical modeling for data extraction is discussed.

Chirped laser dispersion spectroscopy (CLaDS) utilizing direct modulation of a quantum cascade laser (QCL) is presented. By controlling the laser bias nearly single- and dual-sideband CLaDS operation can be realized in an extremely simplified optical setup with no external optical modulators. Capability of direct single-sideband modulation is a unique feature of QCLs that exhibit a low linewidth enhancement factor. The developed analytical model shows excellent agreement with the experimental, directly modulated CLaDS spectra. This method overcomes major technical limitations of mid-infrared CLaDS systems by allowing significantly higher modulation frequencies and eliminating optical fringes introduced by external modulators.

Intravoxel incoherent motion (IVIM) imaging of diffusion and perfusion in the heart suffers from high parameter estimation error. The purpose of this work is to improve cardiac IVIM parameter mapping using Bayesian inference. A second-order motion-compensated diffusion weighted spin-echo sequence with navigator-based slice tracking was implemented to collect cardiac IVIM data in early systole in eight healthy subjects on a clinical 1.5 T CMR system. IVIM data were encoded along six gradient optimized directions with b-values of 0–300 s/mm2. Subjects were scanned twice in two scan sessions one week apart to assess intra-subject reproducibility. Bayesian shrinkage prior (BSP) inference was implemented to determine IVIM parameters (diffusion D, perfusion fraction F and pseudo-diffusion D*). Results were compared to least-squares (LSQ) parameter estimation. Signal-to-noise ratio (SNR) requirements for a given fitting error were assessed for the two methods using simulated data. Reproducibility analysis of parameter estimation in-vivo using BSP and LSQ was performed. BSP resulted in reduced SNR requirements when compared to LSQ in simulations. In-vivo, BSP analysis yielded IVIM parameter maps with smaller intra-myocardial variability and higher estimation certainty relative to LSQ. Mean IVIM parameter estimates in eight healthy subjects were (LSQ/BSP): 1.63 ± 0.28/1.51 ± 0.14·10−3 mm2/s for D, 13.13 ± 19.81/13.11 ± 5.95% for F and 201.45 ± 313.23/13.11 ± 14.53·10−3 mm2/s for D ∗. Parameter variation across all volunteers and measurements was lower with BSP compared to LSQ (coefficient of variation BSP vs. LSQ: 9% vs. 17% for D, 45% vs. 151% for F and 111% vs. 155% for D ∗). In addition, reproducibility of the IVIM parameter estimates was higher with BSP compared to LSQ (Bland-Altman coefficients of repeatability BSP vs. LSQ: 0.21 vs. 0.26·10−3 mm2/s for D, 5.55 vs. 6.91% for F and 15.06 vs. 422.80·10−3 mm2/s for D*). Robust free-breathing cardiac IVIM data acquisition in early systole is possible with the proposed method. BSP analysis yields improved IVIM parameter maps relative to conventional LSQ fitting with fewer outliers, improved estimation certainty and higher reproducibility. IVIM parameter mapping holds promise for myocardial perfusion measurements without the need for contrast agents.

Clinical decision making regarding the treatment of unruptured intracranial aneurysms (IA) benefits from a better understanding of the interplay of IA rupture risk factors. Probabilistic graphical models can capture and graphically display potentially causal relationships in a mechanistic model. In this study, Bayesian networks (BN) were used to estimate IA rupture risk factors influences. From 1248 IA patient records, a retrospective, single-cohort, patient-level data set with 9 phenotypic rupture risk factors (n=790 complete entries) was extracted. Prior knowledge together with score-based structure learning algorithms estimated rupture risk factor interactions. Two approaches, discrete and mixed-data additive BN, were implemented and compared. The corresponding graphs were learned using non-parametric bootstrapping and Markov chain Monte Carlo, respectively. The BN models were compared to standard descriptive and regression analysis methods. Correlation and regression analyses showed significant associations between IA rupture status and patient's sex, familial history of IA, age at IA diagnosis, IA location, IA size and IA multiplicity. BN models confirmed the findings from standard analysis methods. More precisely, they directly associated IA rupture with familial history of IA, IA size and IA location in a discrete framework. Additive model formulation, enabling mixed-data, found that IA rupture was directly influenced by patient age at diagnosis besides additional mutual influences of the risk factors. This study establishes a data-driven methodology for mechanistic disease modelling of IA rupture and shows the potential to direct clinical decision-making in IA treatment, allowing personalised prediction.

Objectives:To quantitatively and qualitatively compare MRI of the temporomandibular joint (TMJ) using an optimized high-resolution protocol at 3.0 T and a clinical standard protocol at 1.5 T.Methods:A phantom and 12 asymptomatic volunteers were MR imaged using a 2-channel surface coil (standard TMJ coil) at 1.5 and 3.0 T (Philips Achieva and Philips Ingenia, respectively; Philips Healthcare, Best, Netherlands). Imaging protocol consisted of coronal and oblique sagittal proton density-weighted turbo spin echo sequences. For quantitative evaluation, a spherical phantom was imaged. Signal-to-noise ratio (SNR) maps were calculated on a voxelwise basis. For qualitative evaluation, all volunteers underwent MRI of the TMJ with the jaw in closed position. Two readers independently assessed visibility and delineation of anatomical structures of the TMJ and overall image quality on a 5-point Likert scale. Quantitative and qualitative measurements were compared between field strengths.Results:The quantitative analys...