The Neuromelanin-related T2* Contrast in Postmortem Human Substantia Nigra with 7T MRI

High field magnetic resonance imaging (MRI)-based delineation of the substantia nigra (SN) and visualization of its inner cellular organization are promising methods for the evaluation of morphological changes associated with neurodegenerative diseases; however, corresponding MR contrasts must be matched and validated with quantitative histological information. Slices from two postmortem SN samples were imaged with a 7 Tesla (7T) MRI with T1 and T2* imaging protocols and then stained with Perl???s Prussian blue, Kluver-Barrera, tyrosine hydroxylase, and calbindin immunohistochemistry in a serial manner. The association between T2* values and quantitative histology was investigated with a co-registration method that accounts for histology slice preparation. The ventral T2* hypointense layers between the SNr and the crus cerebri extended anteriorly to the posterior part of the crus cerebri, which demonstrates the difficulty with an MRI-based delineation of the SN. We found that the paramagnetic hypointense areas within the dorsolateral SN corresponded to clusters of neuromelanin (NM). These NM-rich zones were distinct from the hypointense ventromedial regions with high iron pigments. Nigral T2* imaging at 7T can reflect the density of NM-containing neurons as the metal-bound NM macromolecules may decrease T2* values and cause hypointense signalling in T2* imaging at 7T.ope

Field-portable pixel super-resolution colour microscope.

Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm(2). This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate 'rainbow' like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings

Microscopy with ultraviolet surface excitation for rapid slide-free histology.

Histologic examination of tissues is central to the diagnosis and management of neoplasms and many other diseases, and is a foundational technique for preclinical and basic research. However, commonly used bright-field microscopy requires prior preparation of micrometre-thick tissue sections mounted on glass slides, a process that can require hours or days, that contributes to cost, and that delays access to critical information. Here, we introduce a simple, non-destructive slide-free technique that within minutes provides high-resolution diagnostic histological images resembling those obtained from conventional haematoxylin-and-eosin-histology. The approach, which we named microscopy with ultraviolet surface excitation (MUSE), can also generate shape and colour-contrast information. MUSE relies on ~280-nm ultraviolet light to restrict the excitation of conventional fluorescent stains to tissue surfaces, and it has no significant effects on downstream molecular assays (including fluorescence in situ hybridization and RNA-seq). MUSE promises to improve the speed and efficiency of patient care in both state-of-the-art and low-resource settings, and to provide opportunities for rapid histology in research

Development of Multigene Expression Signature Maps at the Protein Level from Digitized Immunohistochemistry Slides

Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC) is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps) of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions

On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis

Background: Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. Methods: The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object’s centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. Results: After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field – were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. Conclusions: The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction

Prostate Tumor Volume Measurement on Digital Histopathology and Magnetic Resonance Imaging

An accurate assessment of prostate tumour burden supports appropriate treatment selection, ranging from active surveillance through focal therapy, to radical whole-prostate therapies. For selected patients, knowledge of the three-dimensional locations and sizes of prostate tumours on pre-procedural imaging supports planning of effective focal therapies that preferentially target tumours, while sparing surrounding healthy tissue. In the post-prostatectomy context, pathologic measurement of tumour burden in the surgical specimen may be an independent prognostic factor determining the need for potentially life-saving adjuvant therapy. An accurate and repeatable method for tumour volume assessment based on histology sections taken from the surgical specimen would be supportive both to the clinical workflow in the post-prostatectomy setting and to imaging validation studies correlating tumour burden measurements on pre-prostatectomy imaging with reference standard histologic tumour volume measurements. Digital histopathology imaging is enabling a transition to a more objective quantification of some surgical pathology assessments, such as tumour volume, that are currently visually estimated by pathologists and subject to inter-observer variability. Histologic tumour volume measurement is challenged by the traditional 3–5 mm sparse spacing of images acquired from sections of radical prostatectomy specimens. Tumour volume estimates may benefit from a well-motivated approach to inter-slide tumour boundary interpolation that crosses these large gaps in a smooth fashion. This thesis describes a new level set-based shape interpolation method that reconstructs smooth 3D shapes based on arbitrary 2D tumour contours on digital histology slides. We measured the accuracy of this approach and used it as a reference standard against which to compare previous approaches in the literature that are simpler to implement in a clinical workflow, with the aim of determining a method for histologic tumour volume estimation that is both accurate and amenable to widespread implementation. We also measured the effect of decreasing inter-slide spacing on the repeatability of histologic tumour volume estimation. Furthermore, we used this histologic reference standard for tumour volume to measure the accuracy, inter-observer variability, and inter-sequence variability of prostate tumour volume estimation based on radiologists’ contouring of multi-parametric magnetic resonance imaging (MPMRI). Our key findings were that (1) simple approaches to histologic tumour volume estimation that are based on 2- or 3-dimensional linear tumour measurements are more accurate than those based on 1-dimensional measurements; (2) although tumour shapes produced by smooth through-slide interpolation are qualitatively substantially different from those obtained from a planimetric approach normally used as a reference standard for histologic tumour volume, the volumes obtained were similar; (3) decreasing inter-slide spacing increases repeatability of histologic tumour volume estimates, and this repeatability decreases rapidly for inter-slide spacing values greater than 5 mm; (4) on MPMRI, observers consistently overestimated tumour volume as compared to the histologic reference standard; and (5) inter-sequence variability in MPMRI-based tumour volume estimation exceeded inter-observer variability

Structural validation of oral mucosal tissue using optical coherence tomography

Background: Optical coherence tomography (OCT) is a non-invasive optical technology using near-infrared light to produce cross-sectional tissue images with lateral resolution. Objectives: The overall aims of this study was to generate a bank of normative and pathological OCT data of the oral tissues to allow identification of cellular structures of normal and pathological processes with the aim to create a diagnostic algorithm which can be used in the early detection of oral disorders. Material and methods: Seventy-three patients with 78 suspicious oral lesions were referred for further management to the UCLH Head and Neck Centre, London. The entire cohort had their lesions surgically biopsied (incisional or excisional). The immediate ex vivo phase involved scanning the specimens using optical coherence tomography. The specimens were then processed by a histopathologist. Five tissue structures were evaluated as part of this study, including: keratin cell layer, epithelial layer, basement membrane, lamina propria and other microanatomical structures. Two independent assessors (clinician and pathologist trained to use OCT) assessed the OCT images and were asked to comment on the cellular structures and changes involving the five tissue structures in non-blind fashion. Results: Correct identification of the keratin cell layer and its structural changes was achieved in 87% of the cohort; for the epithelial layer it reached 93.5%, and 94% for the basement membrane. Microanatomical structures identification was 64% for blood vessels, 58% for salivary gland ducts and 89% for rete pegs. The agreement was “good” between the clinician and the pathologist. OCT was able to differential normal from pathological tissue and pathological tissue of different entities in this immediate ex vivo study. Unfortunately, OCT provided inadequate cellular and subcellular information to enable the grading of oral premalignant disorders. Conclusion: This study enabled the creation of OCT bank of normal and pathological oral tissues. The pathological changes identified using OCT enabled differentiation between normal and pathological tissues, and identification of different tissue pathologies. Further studies are required to assess the accuracy of OCT in identification of various pathological processes involving the oral tissues

Surgical and histological evidence of case reports showing Schwannomas in the nasal area

Introduction and importance: Schwannomas are benign neurogenic neoplasms with an uncommon involvement of the nasal cavity and paranasal sinus, which usually appear as a painless formation. We report two cases of nasal schwannoma that was successfully treated by surgical excision with satisfactory functional outcomes. The aim of this study is to discuss the clinical assessment and imaging, (CT, MRI) differential diagnosis, histological examination, surgical approaches of this rarely encountered neoplasm in the sinus-nasal area. Case presentation: Case 1: a 53 years-old Caucasian male, hospitalized in the ENT Department with a 5-month progressive history of right nasal obstruction without epistaxis was diagnosed as a Schwannoma following clinical, histology and ENT endoscopy examination. Case 2: a 45 years-old Caucasian male with asymptomatic swelling arising 4 months before in the nasal tip area with progressive nasal deformity, diagnosed as a schwannoma and analyzed with MRI. Clinical discussion: Case 1: The patient had an uneventful post-operative course and a follow-up examination at 36 months showed no recurrence of the neoplasm with satisfactory functional result. Case 2: The patient had an uneventful post-operative course and a follow-up examination at 5 years showed no recurrence of the neoplasm and satisfactory aesthetic result. Conclusions: Schwannomas arising from sinonasal area are extremely rare, painless and with slow-growing evolution. The surgical option and histologic analysis are mandatory for a correct diagnosis

Automated Vascular Smooth Muscle Segmentation, Reconstruction, Classification and Simulation on Whole-Slide Histology

Histology of the microvasculature depicts detailed characteristics relevant to tissue perfusion. One important histologic feature is the smooth muscle component of the microvessel wall, which is responsible for controlling vessel caliber. Abnormalities can cause disease and organ failure, as seen in hypertensive retinopathy, diabetic ischemia, Alzheimer’s disease and improper cardiovascular development. However, assessments of smooth muscle cell content are conventionally performed on selected fields of view on 2D sections, which may lead to measurement bias. We have developed a software platform for automated (1) 3D vascular reconstruction, (2) detection and segmentation of muscularized microvessels, (3) classification of vascular subtypes, and (4) simulation of function through blood flow modeling. Vessels were stained for α-actin using 3,3\u27-Diaminobenzidine, assessing both normal (n=9 mice) and regenerated vasculature (n=5 at day 14, n=4 at day 28). 2D locally adaptive segmentation involved vessel detection, skeletonization, and fragment connection. 3D reconstruction was performed using our novel nucleus landmark-based registration. Arterioles and venules were categorized using supervised machine learning based on texture and morphometry. Simulation of blood flow for the normal and regenerated vasculature was performed at baseline and during demand based on the structural measures obtained from the above tools. Vessel medial area and vessel wall thickness were found to be greater in the normal vasculature as compared to the regenerated vasculature (p\u3c0.001) and a higher density of arterioles was found in the regenerated tissue (p\u3c0.05). Validation showed: a Dice coefficient of 0.88 (compared to manual) for the segmentations, a 3D reconstruction target registration error of 4 μm, and area under the receiver operator curve of 0.89 for vessel classification. We found 89% and 67% decreases in the blood flow through the network for the regenerated vasculature during increased oxygen demand as compared to the normal vasculature, respectively for 14 and 28 days post-ischemia. We developed a software platform for automated vasculature histology analysis involving 3D reconstruction, segmentation, and arteriole vs. venule classification. This advanced the knowledge of conventional histology sampling compared to whole slide analysis, the morphological and density differences in the regenerated vasculature, and the effect of the differences on blood flow and function