While pulmonary arterial hypertension (PAH) leads to right ventricle (RV) hypertrophy and structural remodeling, the relative contributions of changes in myocardial geometric and mechanical properties to systolic and diastolic chamber dysfunction and their time courses remain unknown. Using measurements of RV hemodynamic and morphological changes over 10 weeks in a male rat model of PAH and a mathematical model of RV mechanics, we discriminated the contributions of RV geometric remodeling and alterations of myocardial material properties to changes in systolic and diastolic chamber function. Significant and rapid RV hypertrophic wall thickening was sufficient to stabilize ejection fraction in response to increased pulmonary arterial pressure by week 4 without significant changes in systolic myofilament activation. After week 4, RV end-diastolic pressure increased significantly with no corresponding changes in end-diastolic volume. Significant RV diastolic chamber stiffening by week 5 was not explained by RV hypertrophy. Instead, model analysis showed that the increases in RV end-diastolic chamber stiffness were entirely attributable to increased resting myocardial material stiffness that was not associated with significant myocardial fibrosis or changes in myocardial collagen content or type. These findings suggest that whereas systolic volume in this model of RV pressure overload is stabilized by early RV hypertrophy, diastolic dilation is prevented by subsequent resting myocardial stiffening.

Purpose: Papilledema and peripapillary deformation of Bruch's membrane (BM) are associated with elevated intracranial pressure (ICP). We have developed a novel methodology to measure these parameters using a radial optical coherence tomography (OCT) scan pattern and apply this to test the hypothesis that ICP is associated with volumetric features of ophthalmic structures. Methods: 6-radial OCT B-scans centered over the optic nerve head were acquired in 17 subjects (30 eyes) before lumbar puncture with measurement of ICP (range: 10–55 cm H 2 O). Internal limiting membrane (ILM) and BM were segmented. Three definitions of BM were studied to account for imaging artifact affecting peripapillary BM: connecting rater-identified BM margins(traditional), connecting rater-identified BM 1.6 mm on either side of the ONH(estimated), and excluding BM in the central 3.2 mm of the images(excluded). Optic nerve head volume (ONHV), BM displacement volume (BMDV) and cup volume (CV) were calculated by interpolating between B-scans. Ganglion cell complex volume (GCCV) was measured in the macula. Linear generalized estimating equations (GEE) modeled ONVH, BMDV, and CV as a function of ICP and GCCV. Results: Increased ONHV was associated with elevated ICP for traditional ( p = 0.006), estimated ( p = 0.003) and excluded ( p = 0.05) BM definitions. Decreased BMDV was associated with elevated ICP for traditional ( p < 0.0005), estimated ( p < 0.0005) and excluded ( p = 0.001) definitions. Decreased ONHV was independently associated with decreased GCCV ( p = 0.001) and decreased ICP ( p = 0.031) in multivariable models. CV was neither associated with ICP nor GCCV in univariate or multivariable models. Conclusions: Elevated ICP is associated with ONHV increase and BMDV decrease, calculated from OCT images accounting for image artifact. Ganglion cell atrophy affects the relationship between ICP and ONHV. OCT derived volumetric measures of the posterior eye may have application as biomarkers for elevated ICP.

BackgroundOptic nerve head measurements extracted from optical coherence tomography (OCT) show promise for monitoring clinical conditions with elevated optic nerve heads. The aim of this study is to compare reliability within and between raters and between image acquisition devices of optic nerve measurements derived from OCT scans in eyes with varying degrees of optic nerve elevation.MethodsWide angle line scans and narrow angle radial scans through optic nerve heads were obtained using three spectral domain(SD) OCT devices on 5 subjects (6 swollen optic nerves, 4 normal optic nerves). Three raters independently semi-manually segmented the internal limiting membrane(ILM) and Bruch’s membrane(BM) on each scan using customized software. One rater segmented each scan twice. Segmentations were qualitatively and quantitatively compared. Inter-rater, intra-rater and inter-device reliability was assessed for the optic nerve cross sectional area calculated from the ILM and BM segmentations using intraclass correlation coefficients and graphical comparison.ResultsLine scans from all devices were qualitatively similar. Radial scans for which frame rate could not be adjusted were of lower quality. Intra-rater reliability for segmentation and optic nerve cross sectional area was better than inter-rater reliability, which was better than inter-device reliability, though all ICC exceeded 0.95. Reliability was not impacted by the degree of optic nerve elevation.ConclusionsSD-OCT devices acquired similar quality scans of the optic nerve head, with choice of scan protocol affecting the quality. For image derived markers, variability between devices was greater than that attributable to inter and intra-rater differences.

The photopic negative response of the full-field electroretinogram (ERG) is reduced in optic neuropathies. However, technical requirements for measurement and poor classification performance have limited widespread clinical application. Recent advances in hardware facilitate efficient clinic-based recording of the full-field ERG. Time series classification, a machine learning approach, may improve classification by using the entire ERG waveform as the input. In this study, full-field ERGs were recorded in 217 eyes (109 optic neuropathy and 108 controls) of 155 subjects. User-defined ERG features including photopic negative response were reduced in optic neuropathy eyes (p &lt; 0.0005, generalized estimating equation models accounting for age). However, classification of optic neuropathy based on user-defined features was only fair with receiver operating characteristic area under the curve ranging between 0.62 and 0.68 and F1 score at the optimal cutoff ranging between 0.30 and 0.33. In comparison, machine learning classifiers using a variety of time series analysis approaches had F1 scores of 0.58–0.76 on a test data set. Time series classifications are promising for improving optic neuropathy diagnosis using ERG waveforms. Larger sample sizes will be important to refine the models.

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