Incremental benefit of myocardial contrast to combined dipyridamole-exercise stress echocardiography for the assessment of coronary artery disease

Background-Although assessment of myocardial perfusion by myocardial contrast echocardiography (MCE) is feasible, its incremental benefit to stress echocardiography is not well defined. We examined whether the addition of MCE to combined dipyridamole-exercise echocardiography (DExE) provides incremental benefit for evaluation of coronary artery disease (CAD). Methods and Results-MCE was combined with DExE in 85 patients, 70 of whom were undergoing quantitative coronary angiography and 15 patients with a low probability of CAD. MCE was acquired by low-mechanical-index imaging in 3 apical views after acquisition of standard resting and poststress images. Wall motion, left ventricular opacification, and MCE components of the study were interpreted sequentially, blinded to other data. Significant (>50%) stenoses were present in 43 patients and involved 69 coronary territories. The addition of qualitative MCE improved sensitivity for the detection of CAD (91% versus 74%, P=0.02) and accurate recognition of disease extent (87% versus 65% of territories, P=0.003), with a nonsignificant reduction in specificity. Conclusions-The addition of low-mechanical-index MCE to standard imaging during DExE improves detection of CAD and enables a more accurate determination of disease extent.

3-D magnetic resonance angiography versus conventional angiography in peripheral arterial disease: Pilot study

Angiography is usually performed as the preoperative road map for those requiring revascularization for lower extremity peripheral arterial disease (PAD). The alternative investigations are ultrasound, 3-D magnetic resonance angiography (3-D MRA) and computed tomography angiography. This pilot study aimed to assess whether 3-D MRA could replace the gold standard angiography in preoperative planning. Eight patients considered for aortoiliac or infrainguinal arterial bypass surgery were recruited. All underwent both imaging modalities within 7 days. A vascular surgeon and a radiologist each reported on the images from both the 3-D MRA and the angiography, with blinding to patient details and each others reports. Comparisons were made between the reports for the angiographic and the 3-D MRA images, and between the reports of the vascular surgeon and the radiologist. Compared to the gold standard angiogram, 3-D MRA had a sensitivity of 77% and specificity of 94% in detecting occlusion, and a sensitivity of 72% and specificity of 90% in differentiating high grade (> 50%) versus low grade (< 50%) stenoses. There was an overall concordance of 78% between the two investigations with a range of 62% in the peroneal artery to 94% in the aorta. 3-D MRA showed flow in 23% of cases where conventional angiography showed no flow. In the present pilot study, 3-D MRA had reasonable concordance with the gold standard angiography, depending on the level of the lesion. At times it showed vessel flow where occlusion was shown on conventional angiogram. 3-D MRA in peripheral vascular disease is challenging the gold standard, but is inconsistent at present.

Acute appendagitis: emergency presentation and computed tomographic appearances

Acute epiploic appendagitis is an uncommon cause of abdominal pain. It is caused by torsion of an epiploic appendage or spontaneous venous thrombosis of a draining appendageal vein.1 The diagnosis of this condition primarily relies on cross-sectional imaging and is made most often after computed tomography (CT). Clinically, it is most often mistaken for acute diverticulitis. Approximately 7.1% of patients investigated to exclude sigmoid diverticulitis have imaging findings of primary epiploic appendagitis.

Imaging features of ocular adnexal lymphoproliferative disease

Purpose To evaluate the imaging characteristics of a cohort of patients with ocular adnexal lymphoproliferative disease (OALD). Methods A noncomparative retrospective review between 1992 and 1995 and prospective study from 1995 to 2005 of the clinical, imaging and treatment of 105 patients presenting to tertiary orbital referral centre presenting with OALD. Results One hundred and five patients (mean age 61 years, range 11-90 years) with equal gender distribution were included. Fifty-three were primary and 52 were secondary. Computed tomography (CT) usually showed a well-circumscribed lesion of greater than brain density, moulding to adjacent tissues with moderate enhancement. Aggressive histology was associated with bone destruction, while moulding was associated with indolent histology (P < 0.005). MRI in OALD showed intermediate signal intensity on T1- and T2-weighted images and moderate enhancement with gadolinium. Gallium scanning sensitivity to detect ocular adnexal disease was 25 and 57% for systemic involvement. Positron emission tomography (PET) upstaged (71%) of patients with systemic lymphoproliferative involvement, having a higher sensitivity than CT in detecting distant disease (86 vs 72%). Conclusions CT and/ or MRI are essential in the evaluation of OALD and can be used to establish that an orbital lesion may be lymphoprolifetaive in nature. Further, these imaging modalities may predict the behaviour of the lymphoma in certain cases. Gallium scanning provides no additional information to CT and does not influence patient treatment. PET represents an important addition to the assessment of OALD with real impact on patient management.

Stage is not a reliable indicator of tumor volume in non-small cell lung cancer: a preliminary analysis of the trans-tasman radiation oncology group 99-05 database

Background: Tumor volume has been shown to be a prognostic factor for the response of some tumors to radiotherapy. TNM stage has prognostic value for patients treated surgically for non-small cell lung cancer (NSCLC), but its value is less clear for patients treated by nonsurgical means. This may be because tumor size is not a consistent determinant of T stage or stage group. As part of the preliminary analyses for the Trans-Tasman Radiation Oncology Group 99-05 study, the authors performed this analysis to determine to what extent stage reflects tumor volume. Methods: In this prospective multicenter observational study, patients had to have histologically proven NSCLC, no evidence of disease beyond the primary site or thoracic lymph nodes, and been planned for radical radiotherapy with or without chemotherapy. Tumor volume measurements were based on computed tomography-based treatment planning images. Results: Four hundred four patients were available for analysis. There was a strong correlation between (log) maximum tumor diameter and (log) tumor volume (r = 0.93, p < 0.001). Although there was a highly significant trend of increasing volume with increasing T stage and stage group, when tumors were categorized into four groups according to increasing volume, there was only 55% concordance with T stage and 67% concordance with stage group. Conclusions: There is limited correlation between tumor size and disease stage in patients with NSCLC. This justifies documentation and investigation of size as a potential prognostic factor independent of stage. Maximum tumor diameter may be an adequate substitute for volume as a measurement of size.

EFEITOS ESQUELÉTICOS DA TRAÇÃO REVERSA DA MAXILA UTILIZANDO TOMOGRAFIA COMPUTADORIZADA

Este estudo avaliou os efeitos esqueléticos da tração reversa da maxila utilizando imagens 2D (telerradiografia lateral) geradas a partir da tomografia de feixe cônico (imagens 3D). A amostra foi composta por 20 crianças (15 do gênero feminino, e 5 do masculino), com idade variando de 5,6 a 10,7 anos que apresentavam má-oclusão de Classe III de Angle. A tomografia foi realizada antes do tratamento (T1) e logo após o tratamento (T2). O tratamento foi realizado por meio da tração reversa da maxila utilizando-se o aparelho expansor Hyrax associado à máscara facial individualizada, com força de 600 a 800g de cada lado, durante 14 horas por dia. A correção da relação de caninos em Classe I ou com sua sobrecorreção em Classe II foi obtida após 4 a 8 meses de tratamento. Para verificar o erro sistemático e casual foi utilizado o teste t pareado e a fórmula de Dahlberg, respectivamente. O teste t pareado (p<0,05) mostrou diferença significante entre as medidas cefalométricas obtidas em T1 e T2. Na maxila houve aumento do SNA 2,2°, A-Nperp 1,47mm e em Co-A 2,58mm. Na mandíbula, SNB diminuiu -0,54° e P-Nperp, -1,45mm, enquanto Co-Gn aumentou 1,04mm. Houve melhora na relação maxilo-mandibular ANB 2,74° e Wits 4,23mm. As variáveis GoGn.SN, Gn.SN, FH.Md, Mx.Md, e AFAI aumentaram demonstrando que houve uma rotação da mandíbula no sentido horário. O plano palatino rotacionou no sentido anti-horário. Pode se concluir que o tratamento de tração reversa da maxila na idade precoce promoveu uma melhora na relação maxilo-mandibular devido a um avanço da maxila e um deslocamento da mandíbula para baixo e para trás.

AVALIAÇÃO TOMOGRÁFICA DA INCLINAÇÃO E DAS TÁBUAS ÓSSEAS VESTIBULAR E LINGUAL DE INCISIVOS NO TRATAMENTO DA CLASSE II DIVISÃO 1 COM O APARELHO FORSUS®

O objetivo deste estudo prospectivo foi avaliar os efeitos do aparelho Forsus® nos incisivos centrais superiores e inferiores. A amostra constituiu-se de 22 tomografias computadorizadas de 11 pacientes (sexo masculino e feminino) idade média de 15,8 anos com má oclusão de Classe II que foram tratados com o aparelho Forsus® na clínica do programa de pós-graduação em Odontologia, área de concentração Ortodontia, da Universidade Metodista de São Paulo. As tomografias foram obtidas em dois momentos T1 (final de nivelamento e antes da instalação do Forsus® e T2 (remoção do Forsus®). Para avaliar a distância do ápice até a tábua óssea, as imagens a serem examinadas foram obtidas com o auxílio do viewer do próprio i-CAT® , o iCATVision® e examinadas com o CorelDRAW X5® já para as medidas cefalométricas IMPA e 1.PP as imagens cefalométricas ortogonais foram obtidas em proporção 1:1 com auxílio do software Dolphin 3D® (Dolphin Imaging and Management Solutions, Chatsworth, EUA) e em seguida examinadas com o software Radiocef Studio 2 (Radio Memory, Belo Horizonte, Brasil). Para a obtenção do erro intra-examinador foi feito o teste t de Student pareado para o erro sistemático e a fórmula de DAHLBERG para estimar a ordem de grandeza dos erros casuais e na análise estatística dos resultados utilizou-se: o teste t para a determinação das diferenças entres as fases de observação e o teste de correlação de Pearson para avaliar a correlação entres as alterações. Observou-se: um aumento significativo (p<0,05) tanto no IMPA quanto no 1.PP, aproximação do ápice dos incisivos inferiores da tábua óssea lingual, aproximação do ápice dos incisivos superiores da tábua óssea vestibular, uma correlação negativa muito forte entre o IMPA e a distância do ápice do incisivo até a tábua óssea lingual e uma correlação negativa moderada entre 1.PP e a distância do ápice do incisivo até a tábua óssea vestibular. Sendo assim o aparelho Forsus® no tratamento da Classe II teve como efeito: vestibularização significativa dos incisivos centrais inferiores, uma verticalização significativa dos incisivos centrais superiores, aproximação do ápice dos incisivos inferiores da cortical óssea lingual e aproximação do ápice dos incisivos superiores da cortical óssea vestibular.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.

Contributions to HEVC Prediction for Medical Image Compression

Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compression where either near-lossless or lossless coding is required. In this dissertation, two different approaches to improve lossless coding of volumetric medical images, such as Magnetic Resonance and Computed Tomography, were studied and implemented using the latest standard High Efficiency Video Encoder (HEVC). In a first approach, the use of geometric transformations to perform inter-slice prediction was investigated. For the second approach, a pixel-wise prediction technique, based on Least-Squares prediction, that exploits inter-slice redundancy was proposed to extend the current HEVC lossless tools. Experimental results show a bitrate reduction between 45% and 49%, when compared with DICOM recommended encoders, and 13.7% when compared with standard HEVC.

Development and Optimization of Four-dimensional Magnetic Resonance Imaging (4D-MRI) for Radiation Therapy

A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.

Tissue Equivalent Phantom Design for Optimization of a Coherent Scatter Imaging System

Scatter in medical imaging is typically cast off as image-related noise that detracts from meaningful diagnosis. It is therefore typically rejected or removed from medical images. However, it has been found that every material, including cancerous tissue, has a unique X-ray coherent scatter signature that can be used to identify the material or tissue. Such scatter-based tissue-identification provides the advantage of locating and identifying particular materials over conventional anatomical imaging through X-ray radiography. A coded aperture X-ray coherent scatter spectral imaging system has been developed in our group to classify different tissue types based on their unique scatter signatures. Previous experiments using our prototype have demonstrated that the depth-resolved coherent scatter spectral imaging system (CACSSI) can discriminate healthy and cancerous tissue present in the path of a non-destructive x-ray beam. A key to the successful optimization of CACSSI as a clinical imaging method is to obtain anatomically accurate phantoms of the human body. This thesis describes the development and fabrication of 3D printed anatomical scatter phantoms of the breast and lung.

The purpose of this work is to accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Tissue-equivalent anatomical phantoms were designed to assess the capability of the CACSSI system to classify different types of breast tissue (adipose, fibroglandular, malignant). These phantoms were 3D printed based on DICOM data obtained from CT scans of prone breasts. The phantoms were tested through comparison of measured scatter signatures with those of adipose and fibroglandular tissue from literature. Tumors in the phantom were modeled using a variety of biological tissue including actual surgically excised benign and malignant tissue specimens. Lung based phantoms have also been printed for future testing. Our imaging system has been able to define the location and composition of the various materials in the phantom. These phantoms were used to characterize the CACSSI system in terms of beam width and imaging technique. The result of this work showed accurate modeling and characterization of the phantoms through comparison of the tissue-equivalent form factors to those from literature. The physical construction of the phantoms, based on actual patient anatomy, was validated using mammography and computed tomography to visually compare the clinical images to those of actual patient anatomy.

Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe.

Photoacoustic tomography (PAT) of genetically encoded probes allows for imaging of targeted biological processes deep in tissues with high spatial resolution; however, high background signals from blood can limit the achievable detection sensitivity. Here we describe a reversibly switchable nonfluorescent bacterial phytochrome for use in multiscale photoacoustic imaging, BphP1, with the most red-shifted absorption among genetically encoded probes. BphP1 binds a heme-derived biliverdin chromophore and is reversibly photoconvertible between red and near-infrared light-absorption states. We combined single-wavelength PAT with efficient BphP1 photoswitching, which enabled differential imaging with substantially decreased background signals, enhanced detection sensitivity, increased penetration depth and improved spatial resolution. We monitored tumor growth and metastasis with ∼ 100-μm resolution at depths approaching 10 mm using photoacoustic computed tomography, and we imaged individual cancer cells with a suboptical-diffraction resolution of ∼ 140 nm using photoacoustic microscopy. This technology is promising for biomedical studies at several scales.

Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Coding Strategies for X-ray Tomography

This work focuses on the construction and application of coded apertures to compressive X-ray tomography. Coded apertures can be made in a number of ways, each method having an impact on system background and signal contrast. Methods of constructing coded apertures for structuring X-ray illumination and scatter are compared and analyzed. Apertures can create structured X-ray bundles that investigate specific sets of object voxels. The tailored bundles of rays form a code (or pattern) and are later estimated through computational inversion. Structured illumination can be used to subsample object voxels and make inversion feasible for low dose computed tomography (CT) systems, or it can be used to reduce background in limited angle CT systems.

On the detection side, coded apertures modulate X-ray scatter signals to determine the position and radiance of scatter points. By forming object dependent projections in measurement space, coded apertures multiplex modulated scatter signals onto a detector. The multiplexed signals can be inverted with knowledge of the code pattern and system geometry. This work shows two systems capable of determining object position and type in a 2D plane, by illuminating objects with an X-ray `fan beam,' using coded apertures and compressive measurements. Scatter tomography can help identify materials in security and medicine that may be ambiguous with transmission tomography alone.

Open-source virtual bronchoscopy for image guided navigation

This thesis describes the development of an open-source system for virtual bronchoscopy used in combination with electromagnetic instrument tracking. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. The open-source platform 3D Slicer was used for creating freely available algorithms for virtual bronchscopy. Firstly, the development of an open-source semi-automatic algorithm for prediction of solitary pulmonary nodule malignancy is presented. This approach may help the physician decide whether to proceed with biopsy of the nodule. The user-selected nodule is segmented in order to extract radiological characteristics (i.e., size, location, edge smoothness, calcification presence, cavity wall thickness) which are combined with patient information to calculate likelihood of malignancy. The overall accuracy of the algorithm is shown to be high compared to independent experts' assessment of malignancy. The algorithm is also compared with two different predictors, and our approach is shown to provide the best overall prediction accuracy. The development of an airway segmentation algorithm which extracts the airway tree from surrounding structures on chest Computed Tomography (CT) images is then described. This represents the first fundamental step toward the creation of a virtual bronchoscopy system. Clinical and ex-vivo images are used to evaluate performance of the algorithm. Different CT scan parameters are investigated and parameters for successful airway segmentation are optimized. Slice thickness is the most affecting parameter, while variation of reconstruction kernel and radiation dose is shown to be less critical. Airway segmentation is used to create a 3D rendered model of the airway tree for virtual navigation. Finally, the first open-source virtual bronchoscopy system was combined with electromagnetic tracking of the bronchoscope for the development of a GPS-like system for navigating within the lungs. Tools for pre-procedural planning and for helping with navigation are provided. Registration between the lungs of the patient and the virtually reconstructed airway tree is achieved using a landmark-based approach. In an attempt to reduce difficulties with registration errors, we also implemented a landmark-free registration method based on a balanced airway survey. In-vitro and in-vivo testing showed good accuracy for this registration approach. The centreline of the 3D airway model is extracted and used to compensate for possible registration errors. Tools are provided to select a target for biopsy on the patient CT image, and pathways from the trachea towards the selected targets are automatically created. The pathways guide the physician during navigation, while distance to target information is updated in real-time and presented to the user. During navigation, video from the bronchoscope is streamed and presented to the physician next to the 3D rendered image. The electromagnetic tracking is implemented with 5 DOF sensing that does not provide roll rotation information. An intensity-based image registration approach is implemented to rotate the virtual image according to the bronchoscope's rotations. The virtual bronchoscopy system is shown to be easy to use and accurate in replicating the clinical setting, as demonstrated in the pre-clinical environment of a breathing lung method. Animal studies were performed to evaluate the overall system performance.