Quantitative lung morphology: semi-automated measurement of mean linear intercept.

BACKGROUND: Quantifying morphologic changes is critical to our understanding of the pathophysiology of the lung. Mean linear intercept (MLI) measures are important in the assessment of clinically relevant pathology, such as emphysema. However, qualitative measures are prone to error and bias, while quantitative methods such as mean linear intercept (MLI) are manually time consuming. Furthermore, a fully automated, reliable method of assessment is nontrivial and resource-intensive. METHODS: We propose a semi-automated method to quantify MLI that does not require specialized computer knowledge and uses a free, open-source image-processor (Fiji). We tested the method with a computer-generated, idealized dataset, derived an MLI usage guide, and successfully applied this method to a murine model of particulate matter (PM) exposure. Fields of randomly placed, uniform-radius circles were analyzed. Optimal numbers of chords to assess based on MLI were found via receiver-operator-characteristic (ROC)-area under the curve (AUC) analysis. Intraclass correlation coefficient (ICC) measured reliability. RESULTS: We demonstrate high accuracy (AUCROC > 0.8 for MLIactual > 63.83 pixels) and excellent reliability (ICC = 0.9998, p < 0.0001). We provide a guide to optimize the number of chords to sample based on MLI. Processing time was 0.03 s/image. We showed elevated MLI in PM-exposed mice compared to PBS-exposed controls. We have also provided the macros that were used and have made an ImageJ plugin available free for academic research use at https://med.nyu.edu/nolanlab. CONCLUSIONS: Our semi-automated method is reliable, equally fast as fully automated methods, and uses free, open-source software. Additionally, we quantified the optimal number of chords that should be measured per lung field.

Oliver McFarlane syndrome: two new cases and a review of the literature.

BACKGROUND: Oliver McFarlane syndrome is a rare syndrome. Clinical presentations include trichomegaly, chorioretinal degeneration, pituitary hormone deficits, and neurological manifestations. Genetic analysis has recently placed this syndrome within the group of PNPLA6-related disorders. Here, we describe two new individuals and review the previously published cases. MATERIALS AND METHODS: Clinical investigations were carried out in accordance with local guidelines and clinical information was retrieved from medical records. Genetic studies were carried out using next-generation sequencing based clinical exome sequencing. A PubMed literature search was performed with a review of the published clinical cases of Oliver McFarlane syndrome. RESULTS: Our first individual was a 36-year-old woman with 32 years of follow up and our second individual was a 3-year-old boy. Both individuals were born preterm and presented with prolonged neonatal respiratory distress, trichomegaly, early growth retardation, retinopathy and sparse depigmented hair. So far, none of our cases have demonstrated cognitive impairment or progressive neurological symptoms, but the child revealed persistent abnormal lung structure. Both individuals were compound heterozygous for pathogenic PNPLA6 variants, one of which was novel. We found other 31 clinically documented published cases. CONCLUSIONS: Our two new unrelated cases of Oliver McFarlane Syndrome demonstrate early ophthalmological and systemic findings of this rare syndrome and the progressive nature of the retinopathy with a long follow-up. PNPLA6-related disorders are a phenotypically highly heterogenous group where alterations in the phosphatidylcholine metabolism can lead to manifestations in different tissues with no clear genotype-phenotype correlation.