computational medical imaging analysis chapter 7: biomedical applications

Post on 15-Jan-2016

50 Views

Category:

Documents

0 Downloads

Preview:

Click to see full reader

DESCRIPTION

Computational Medical Imaging Analysis Chapter 7: Biomedical Applications. Jun Zhang Laboratory for Computational Medical Imaging & Data Analysis Department of Computer Science University of Kentucky Lexington, KY 40506. 7.1a: Neuronal Microanatomy and Function. - PowerPoint PPT Presentation

TRANSCRIPT

Chapter 7: CS689 1

Computational Medical Imaging Analysis Chapter 7: Biomedical Applications

Jun Zhang

Laboratory for Computational Medical Imaging & Data AnalysisDepartment of Computer Science

University of KentuckyLexington, KY 40506

Chapter 7: CS689 2

7.1a: Neuronal Microanatomy and Function

Rapid growth of 3D visualization of microscopic structures happens with the advent of

Light and electron microscopy (classical) Confocal microscopy Atomic force microscopy Tunneling microscopy

Chapter 7: CS689 3

7.1b: Light and Electron Microscopy Light microscopy images digitized directly from the

microscope can provide a 3D volume image by incrementally adjusting the focal plane

It is usually followed by image processing to deconvolve the image to remove blurred, out-of-focus structures

Electron microscopy can generate multiple planes by controlling the depth of focus

Further processing is necessary for selective focal plane reconstruction

Chapter 7: CS689 4

7.1b*: Light Microscopes

Chapter 7: CS689 5

7.1b**: Electron Microscope ($69,000)

Chapter 7: CS689 6

7.1c: Confocal Microscopy

Confocal microscopy uses incoherent light or laser with precise optical control to selectively image specific parallel sections within the microscopic structure

Multiple image planes can be selected, providing direct volume image acquisition without the need of signal from structures outside of the plane of interest

These images are often acquired using specific fluorescent dyes to selectively image a particular component of the structure under study

Chapter 7: CS689 7

7.1c*: Confocal Microscope

Chapter 7: CS689 8

7.1c**: Confocal Microscopy Images

Chapter 7: CS689 9

7.1c**: Confocal Microscopy Images

Chapter 7: CS689 10

7.1d: Neuron Visualization

The morphology and function of neurons from selected ganglia in the mammalian peripheral autonomic nervous system can be visualized

Information about a neuron’s shape and dimensions is needed to integrate and localize multiple synaptic inputs

The number and location of selective neurotransmitter receptor sites provides valuable information about the potential response of a neuron to a specific transmitter

Such visualization applications are termed as “spatial physiology” in which the function of microstructures are studies

Chapter 7: CS689 11

7.1d*: Neuron Illustration

Chapter 7: CS689 12

7.1d*: Single Neuron

Chapter 7: CS689 13

7.1f: Imaging Neuron Architecture Visualization of the architectural relationships

between neurons is less well advanced Nerve plexes, where millions of sensory nerve cells

are packed into a few cubic millimeters of tissue, offer an opportunity to image a tractable number of cells in situ

This difficulty underscores the need for computer-assisted techniques to reconstruct neuronal architectures in vivo

They may not be visible directly from the images, but they can be visualized with assisting techniques

Chapter 7: CS689 14

7.1f*: Rat Neuron

Chapter 7: CS689 15

7.2a: Corneal Cell Analysis

The density and arrangement of corneal cells is an indicator of the general health of the cornea

These factors are routinely evaluated to determine suitability for transplant

The corneal confocal microscope is a reflected-light scanning aperture microscope fitted for direct contact with a living human cornea

The image is a 3D tomographic optical image of the cornea

Algorithms are developed for automated measurement of local keratocyte nuclear density in the cornea

Chapter 7: CS689 16

7.2b: Human Cornea

Chapter 7: CS689 17

7.2c: Local Keratocyte Density The sectional images represent a section

about 15 microns thick and at 1 micron intervals through the entire depth of the cornea

Both global and local automated density counts in rabbit corneas correlate well to those obtained from conventional histologic evaluation of cornea tissue

A decrease in keratocyte density toward the posterior of the cornea was found

Chapter 7: CS689 18

7.2d: Keratocyte Density Images

Left: Corneal confocal image. Right: Nuclei counting

Chapter 7: CS689 19

7.2e: In Vivo Study of Cornea Density In vivo confocal

microscopy images showthe presence of denselypacked ovoid or ellipticalcell bodies, decreasingafter birth for a neonate

Chapter 7: CS689 20

7.2f: Cornea Density of Neonate

Laser scanning micrographs of neonatal corneasshow decreasingcell density afterbirth, confirmingthe in vivo confocal microscopy images

Chapter 7: CS689 21

7.3a: Trabecular Tissue Analysis in Glaucoma The trabecular tissue of the eye is a ring of

spongy, fluid-filled tissue situated at the junction of cornea, iris, and sclera

This tissue lies in the only outflow path for aqueous humor, it has long been implicated in the eye disease glaucoma

The architecture of the trabecular tissue is so complex that most studies have focused on the architecture of the connected fluid space

Chapter 7: CS689 22

7.3a*: Trabecular Tissue Image

Chapter 7: CS689 23

7.3b: Connected Fluid Space Analysis The fluid space is generally continuous from

the anterior chamber through the trabecular tissue into Schlemm’s canal

Morphometric analysis (in which small chambers were successively closed) revealed that the interconnection is maintained by very small chambers

There are a large number of these narrowings, and they occur at all regions of the tissue

Chapter 7: CS689 24

7.3c: Connected Fluid Space in Human Trabecular Tissue

Before (left) and after (right) morphological opening

Chapter 7: CS689 25

7.4a: Prostate Microvessels

It is common practice to surgically remove cancerous prostates, even though subsequent pathological examination of excised tissues suggest that some surgeries could have been avoided

There is a great need for improved non-invasive preoperative techniques that can more accurately measure tumor volume and extent

The measures of prostate tumor size and microvessel density are useful indicators of the metastatic potential of tumor

Chapter 7: CS689 26

7.4a*: Prostate Cancer

Chapter 7: CS689 27

7.4b: 3D Visualization of Microvessels 3D image analyses show that the ratio of

gland volume to vessel length exhibits a twofold increase between benign and malignant tumors

The normal tissue shows a characteristic circumferential pattern of the microvessels relative to the glandular tissue

In region with adenocarcinoma, the pattern of microvessels is tortuous and radically diffused throughout the glandular volume

Chapter 7: CS689 28

7.4b**: Tumor & Neovasculature

Chapter 7: CS689 29

7.4b*: Frog Microvessel

Chapter 7: CS689 30

7.4c: Measurements of Microvessels Neovasculature exhibits a statistically significantly

larger standard deviation of curvature than the normal vessels

These measurements can be done with the images Volume of tissue required for the histologic analysis

is similar to that obtained via needle biospy 3D image with biospy sample provides a marker for

presurgical stage and outcome, improve patient population stratification and eliminate unnecessary surgeries

Chapter 7: CS689 31

7.4c*: Stages of Prostate Cancer

Chapter 7: CS689 32

7.5a: Prostate Surgery Planning Radical prostatectomy is the most commonly

performed surgical procedure The procedure has significant morbidity Minimizing these negative affects needs a

careful balance between completely removal of all cancerous prostate tissue and sparing neural and vascular structures

Routine surgical rehearsal using patient specific data could have significant effect on procedural success

Chapter 7: CS689 33

7.5b: Prostate Cancer Surgery

Chapter 7: CS689 34

7.5c: Presurgical Rehearsal

Presurgical MR volume images of patients scanned with a rectal coil can be segmented to identify and locate the prostate, bladder, and other tissues

The segmented images can be constructed into faithful patient-specific models and reviewed by surgeons interactively before the surgery

The approach, margins, and critical tradeoffs can be evaluated and determined upon seeing the pathology localized relative to normal anatomy

Rendered views of patient-specific models of prostate cancer can be used to accurately assess the tumor size and location relative to sensitive structures

Chapter 7: CS689 35

7.5d: Prostate Surgical Planning

Chapter 7: CS689 36

7.6a: Craniofacial Surgery Planning and Evaluation Craniofacial surgery (CFS) involves surgery of the

facial and cranial skeleton and soft tissues Preoperative information is most often acquired

using X-ray CT scanning for the bony structures, with MRI used for imaging the soft internal tissues

3D visualization facilitates accurate measurement of structures of interest, allowing precise design of surgical procedures

It also minimizes the duration of surgery, reducing the risk of postoperative complication and cost

Chapter 7: CS689 37

7.6b: Craniofacial Surgery (I)

Chapter 7: CS689 38

7.6c: Craniofacial Surgery (II)

Chapter 7: CS689 39

7.6d: Craniofacial Surgery Planning

Chapter 7: CS689 40

7.6e: Craniofacial Reconstruction (I)

Chapter 7: CS689 41

7.6f: Craniofacial Reconstruction (II)

Chapter 7: CS689 42

7.7a: Neurosurgery Planning

Neurosurgery needs extended knowledge and understanding of intricate relationships between normal anatomy and pathology

Multimodality scans are coregistered to help neurosurgeon understand anatomy of interest

Specific anatomical objects may be identified and segmented, creating object maps within the digital volumetric dataset

The diagnostic information is used to determine the margins of pathology, to avoid critical structures, e.g., cerebral vasculature and eloquent cortical tissue

Chapter 7: CS689 43

7.7a*: Virtual Surgery Planning

Chapter 7: CS689 44

7.7b: Neurosurgery Planning in Epilepsy

Chapter 7: CS689 45

7.7c: Neurosurgery Planning in Tumor Resection

Chapter 7: CS689 46

7.7d: Neurosurgery (I)

Chapter 7: CS689 47

7.7e: Neurosurgery (II)

Chapter 7: CS689 48

7.7f: Neurosurgery (III)

Chapter 7: CS689 49

7.7g: Intraoperative Guidance Interactive computation of line-of-sight oblique

planar images for planning neurosurgical approach to large tumor

Neurosurgeon will have direct visualization of image planes along the path of surgical approach

T1-weighted MRI prior to contrast enhancement (2nd row), T1-wieghted MRI with gadolinium to define tumor size (3rd row), MR angiogram to localize position of important vessels (4th row)

Chapter 7: CS689 50

7.7g*: Neurosurgery (IV)

Chapter 7: CS689 51

7.8a: Intraoperative Imaging

Brain changes position during the neurosurgical intervention, shifting as skull and dura are opened

Use of preoperative images for navigation needs to be carefully calibrated against the brain shift

Accurate segmented brain models can be provided by optical tracking or global positioning system

A heads up display system can allow the surgeon to view 3D models transparently through the surface of the cerebra cortex

Chapter 7: CS689 52

7.8b: Intraoperative ultrasound images combined with fMRI

Chapter 7: CS689 53

7.9a: Epilepsy Imaging

Epilepsy is a prevalent disease (10-20%) caused by abnormal electrical activity in the brain

This abnormal electrical signal usually originates at a specific location in the brain, and spreads from a central focus to other regions

The location of the abnormal signal focus determines the characteristics of the seizure activity exhibited by the patient

Typicals are abnormal motor activity or other unusual sensory behavior

Chapter 7: CS689 54

7.9b: Abnormal Epilepsy Behaviors

Chapter 7: CS689 55

7.9c: Epilepsy Brain Signal Activities

Chapter 7: CS689 56

7.9d: Difficulty to Locate Focus Abnormal electrical activities does not always

correspond to any identifiable discrete pathology (e.g., a tumor)

Electrical signal sampling with standard electroencephalogram (EEG) recording may give an overall picture of the pattern of electrical activity causing the seizure

It will not allow (point out) accurate location to a specific part of the brain

Even subdurally implanted electrodes on the cortical surface of the brain do not allow precise identification of regional brain tissue causing the seizure focus

Chapter 7: CS689 57

7.9e: Monitoring Brain Electrical Activities

Chapter 7: CS689 58

7.9f: Epilepsy Imaging Using SISCOM A combination of SPECT and MR imaging for

improved diagnosis of areas of regional activation in the brain during seizure

Subtraction ictal SPECT coregistered to MRI (SISCOM), takes advantages of the transient focal increase in cerebral blood flow in the region of seizure focus

It images and statistically identifies the part of the brain involved in the seizure activity

SPECT has demonstrated ability to map ictal (during seizure) and interictal (resting, between seizures) blood flow patterns, provides potential for using these in combination to localize the seizure focus

Chapter 7: CS689 59

7.9g: SISCOM ImagesA: MRIB: PETC: PET and MRI

D: 2nd MRI from SISCOME: Difference SPECTF: SISCOM

Chapter 7: CS689 60

7.9h: Axial Images of Mesial Temporal Lobe Epilepsy (MRI, composite SISCOM)

Chapter 7: CS689 61

7.9i: Coronal Images of MTLE

MRI, composite SISCOM, composite subtraction SPECT, and rainbow color scales for anterior (top) and posteriortemporal (bottom) regions of left MTLE group

Chapter 7: CS689 62

7.9j: Sagittal Images of left MTLE group

MRI, composite SISCOM, composite SPECT, rainbow colorscale for left MTLE group

top related