Atlas of Clinical Imaging and Anatomy of the Equine Head

Larry Kimberlin, Alex zur Linden, Lynn Ruoff

• Publisher: Wiley-Blackwell
• Year: 2016
• ISBN:
  9781118988992
• Edition: 1
• Topic: Médecine
• Subtopic: Médecine vétérinaire

Atlas of Clinical Imaging and Anatomy of the Equine Head presents a clear and complete view of the complex anatomy of the equine head using cross-sectional imaging.

• Provides a comprehensive comparative atlas to structures of the equine head
• Pairs gross anatomy with radiographs, CT, and MRI images
• Presents an image-based reference for understanding anatomy and pathology
• Covers radiography, computed tomography, and magnetic resonance imaging

CHAPTER 1
Overview of CT and MRI of the Equine Head

The diagnosis of conditions affecting the equine head is challenging for the veterinary practitioner due to its large size, complex anatomy, and the multitude of different tissues present and thus the large number of potential disease processes. Disease processes of the teeth include caries, periodontal disease, tooth root abscess, tooth fracture, dentigerous cysts, and malocclusion to name a few [1]. The tongue can be affected by trauma, infection, or neoplasia. The nasal passages and paranasal sinuses are important parts of the equine head that can be the site of sinusitis, ethmoid hematomas, cysts, or neoplasia. The diverticulum of the auditory tube (guttural pouch) can develop fungal granulomas, empyema, blood clots, or tympany. Laryngeal hemiplegia, dorsal displacement of the soft palate, epiglottic entrapment, rostral displacement of the palatopharyngeal arches, arytenoid chondritis, and pharyngeal narrowing can affect the pharyngeal region [2]. Other tissues in the head such as the lymph nodes and salivary glands can be affected by infectious or non‐infectious inflammation, or neoplasia. The brain can be affected by trauma, bleeding, infarction, neoplasms, cholesterinic granulomas, ventriculomegaly (hydrocephalus), and infection (meningitis or meningoencephalitis). Trauma to the head can result in fractures of the calvarium, mandible, temporomandibular joint, basisphenoid bone, and nuchal crest of the occipital bone. Although uncommon in horses, neoplasia that can be found in the head includes melanoma, adenocarcinoma or rhabdomyosarcoma of the tongue, lacrimal gland adenocarcinoma and ophthalmic tumors associated with the eye, and multicentric lymphoma affecting the lymph nodes in the head [2]. The hyoid bones can be affected by fractures or temporohyoid osteoarthropathy. The eyes and ears are also prone to a variety of pathological conditions. Many of these conditions can be diagnosed on physical examination; however, many require further diagnostics.

Diagnostic imaging of the equine head is most commonly done via radiography (Figure 1) or endoscopy. Routine radiographic examination can include orthogonal projections of the area of interest, oblique projections of the dental arcades or temporomandibular joints and intraoral projections for the rostral mandible/maxilla. Due to the size of the adult head and the limited size of the X‐ray cassette or imaging plate, multiple radiographs are needed to image the entire head, although this is not routinely performed in clinical practice. Radiographs offer superior spatial resolution compared to more advanced imaging options; however, due to the superimposition of anatomy, lesion localization can be quite challenging using radiography. The anatomy of the head is complex and radiographs do not provide adequate contrast of the soft tissues of the head. Radiographic anatomy has been thoroughly described elsewhere and is outside the scope of this book.

Figure 1 A lateral (a) and dorsoventral radiograph (b) of the head from an older adult equine cadaver that was used in the making of this book. Two radiographs are spliced together to create each image of the whole head. These radiographs demonstrate the excellent contrast between the air‐filled nasal passages, paranasal sinuses and guttural pouches, and the mineral opaque bones and teeth. The soft tissues are difficult to differentiate unless they are surrounded by gas or bone.

A computed tomography (CT) unit consists of a high‐powered X‐ray tube mounted in a circular gantry across from a detector array. The gantry is able to rotate around the patient using slip‐ring technology so it is not tethered electronically to the rest of the unit. As the gantry rotates, the patient moves either into or out of the gantry as the X‐rays are absorbed, scattered, or pass through the patient. The X‐rays that reach the detector array are used to construct an image.

For digital radiographs, the attenuation of the X‐rays results in a two‐dimensional image involving multiple pixels. CT uses a similar method to display an image by converting a volume of tissue to a three‐dimensional pixel called a voxel. CT will determine the average linear attenuation coefficient of X‐rays for each voxel in a patient at a particular location [3]. Each voxel can be given a quantifiable number in terms of its gray scale, termed a Hounsfield unit (HU). As a reference, pure water has a HU of 0 and air is –1000 HU. Adipose tissue can vary from –30 to –80 HU, soft tissues +30 to +220, while bone and iodinated contrast media can be close to +2000 to +3000. Each voxel is then interpreted as a pixel when displayed as a two‐dimensional CT image.

Most CT images are reconstructed in an axial plane. If the depth of the slice thickness (z‐direction of the voxel) is the same as the size of the pixel (x and y directions), then the voxel is considered isotropic, or near isotropic if it is similar in size. Isotropic voxels allow for high‐resolution reconstructions of the CT dataset into multiple different planes. These reconstructions allow one to view the anatomy in different planes to identify the extent of a disease process or to better visualize the “three‐dimensional” (3D) anatomy using a two‐dimensional interface. Isotropic voxels can also be used to produce high‐resolution reconstructions that appear three‐dimensional, even though they are still a two‐dimensional image. This is demonstrated in Figure 2c and d, where a 3D reconstruction can be useful to get an overall look at the scanned anatomical structures.

Figure 2 CT scan of an adult horse that presented with a facial deformity from an unknown trauma and signs of sinusitis. The patient was imaged in dorsal recumbency for the CT scan. (a,b) Transverse images at the level of the fracture in a bone filter and window (a) and a soft tissue filter and window (b), demonstrating thickened and irregular margins of the frontal, nasal, and lacrimal bones. Fluid is also noted in the conchofrontal sinus and caudally displaced ventral conchal sinus. The lining of the sinuses is thickened, consistent with sinusitis. (c,d) “Three‐dimensional” reconstructions of the CT dataset with a dorsal view (c) and left dorsolateral view (d) of the skull. These images help to get an overall look at the bones of the skull and to determine that this deformity was likely caused by a concussive trauma to a sharp linear object, such as the corner of a beam or post. The displacement of the ventral conchal sinus and concha caused by the trauma caused narrowing of the conchomaxillary opening that impeded drainage, resulting in the sinusitis.

Computed tomography images are reconstructed from a very large collection of voxels (raw image data), each with its own Hounsfield unit and location in space. The computer uses an algorithm or filter to adjust how each pixel looks on a two‐dimensional image and this algorithm can be modified to alter the spatial resolution and contrast differences of different tissues. The primary two algorithms used in this book are referred to generically as a bone filter or algorithm and a soft tissue filter or algorithm. The bone algorithm has a higher spatial resolution and the bone and teeth are seen in gray with well‐defined edges, whereas all the soft tissues are homogenously gray. The soft tissue algorithm has a reduced spatial resolution but the contrast of the soft tissues is more noticeable, and the bone and teeth are completely white.

The appearance of the CT images can be adjusted by the viewer for either algorithm using the window width/window level adjustment function found on all image viewing systems. The window width (WW) is the range of displayed Hounsfield units. The window level (WL) is the Hounsfield unit in the center of the window width. In this book, the bone algorithm is shown in a bone window, with a WW of ~3500 and a WL of ~650. The soft tissue algorithm is shown in a soft tissue window, with a WW of ~500 and a WL of ~70. So, for the bone setting a wide window of 3500 densities allows for a lot of different densities to be displayed, centered on 650 HU (+4150 to –2850 HU). For the soft tissue setting, a short window width of 500 is used, centered at 70 HU, near the density of the soft ti...