## 1 Introduction  
Intracranial pressure (ICP) is critical in the management of several conditions, such as traumatic brain injury or intracranial hypertension. Abnormal ICP is also associated with various ocular diseases (e.g., papilledema, glaucoma) [1; 2]. Current techniques of ICP measurement, such as lumbar puncture,are invasive, need technical expertise, and can lead to medical complications [3]. The optic nerve head (ONH) lies at the interface of intraocular pressure (IOP) and ICP compartments, and hence, can be leveraged for non-invasive estimation of ICP. Optical coherence tomography (OCT) is commonly used in ophthalmology clinics to inspect the ONH structure noninvasively [4]. Morphological quantifications from the OCT scans (e.g., retinal thickness and lamina cribrosa depth) facilitate the diagnosis and treatment planning of many blinding diseases [5; 6; 7; 8]. The shape of peripapillary retinal pigment epithelium-basement membrane (ppRPE/BM) layer has attracted much attention due to its relationship with ICP fluctuations [9]. Specifically, [PERSON] et al. used a manual segmentation method for selected patients with symmetrical temporal-nasal scans, and observed that the ppRPE/BM layer exhibited a deeper V-shape following the ICP-lowering intervention [10]. [PERSON] et al. adopted the same labor-intensive segmentation approach and detected the alternations of ppRPE/BM layer within 1 h after lumbar puncture (LP) to lower the ICP. There are several limitations to the methods used by these groups. The principal component analysis (PCA) method was generally used in the aforementioned shape analysis [9; 11]. However, the principal components depend on the choice of dataset [12; 13], and the shape analysis results highly depend on the choice of OCT scan direction. Moreover, only one OCT scan per patient was used for the ppRPE/BM layer shape analysis (mostly the temporal-nasal scan) [9; 11; 14; 10] due to the labor intensive methods for manual segmentations. However, one recent study showed that the ppRPE/BM layer shapes were different across various radial directions [15]. A three-dimensional (3D) characterizations of the ppRPE/BM layer is needed for better mechanistic understanding of ONH morphology following ICP changes [16].  
In this work, we developed a semi-automatic method to quantitatively characterize the 3D morphology of the ppRPE/BM layer in patients undergoing LP. Following the segmentation of the ppRPE/BM layers, linear regression models were fitted using the least squares approach. The ppRPE/BM layer angle was measured as the slope of the linear regression line. To compensate for image tilting, we obtained the average of ppRPE/BM layer angles from the right and left zone in each radial OCT scan. The scan angles obtained from two independent graders or using our semi-automatic method were compared, and the inter-observer agreement and reliability were evaluated. We tested our method using OCT images of nineteen patients undergoing medically necessary LP. Statistical analysis was performed to evaluate the LP-induced cross-sectional ppRPE/BM layer angle change. To the best of our knowledge, this is the first semi-automatic method that could efficiently quantify the 3D ppRPE/BM layer by integrating all radial OCT scans.