Contrast Staining in Noninfarcted Tissue after Endovascular Treatment of Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Contrast staining is a common finding after endovascular treatment of acute ischemic stroke. It typically occurs in infarcted tissue and is considered an indicator of irreversible brain damage. Contrast staining in noninfarcted tissue has not been systematically investigated. We sought to assess the incidence, risk factors, and clinical significance of contrast staining in noninfarcted tissue after endovascular treatment.

MATERIALS AND METHODS

We conducted a retrospective review of consecutive patients who underwent endovascular treatment for anterior circulation large-vessel occlusion acute ischemic stroke. Contrast staining, defined as new hyperdensity on CT after endovascular treatment, was categorized as either contrast staining in infarcted tissue if the stained region demonstrated restricted diffusion on follow-up MR imaging or contrast staining in noninfarcted tissue if the stained region demonstrated no restricted diffusion. Baseline differences between patients with and without contrast staining in noninfarcted tissue were compared. Logistic regression was used to identify independent associations for contrast staining in noninfarcted tissue after endovascular treatment.

RESULTS

Among 194 patients who underwent endovascular treatment for large-vessel occlusion acute ischemic stroke and met the inclusion criteria, contrast staining in infarcted tissue was noted in 52/194 (26.8%) patients; contrast staining in noninfarcted tissue, in 26 (13.4%) patients. Both contrast staining in infarcted tissue and contrast staining in noninfarcted tissue were noted in 5.6% (11/194). Patients with contrast staining in noninfarcted tissue were found to have a higher likelihood of having an ASPECTS of 8-10, to be associated with contrast staining in infarcted tissue, and to achieve successful reperfusion compared with those without contrast staining in noninfarcted tissue. In contrast staining in noninfarcted tissue regions, the average attenuation was 40 HU, significantly lower than the contrast staining in infarcted tissue regions (53 HU). None of the patients with contrast staining in noninfarcted tissue had clinical worsening during their hospital stay. The median discharge mRS was significantly lower in patients with contrast staining in noninfarcted tissue than in those without (3 versus 4; P = .018). No independent predictors of contrast staining in noninfarcted tissue were found.

CONCLUSIONS

Contrast staining can be seen outside the infarcted tissue after endovascular treatment of acute ischemic stroke, likely attributable to the reversible disruption of the BBB in ischemic but not infarcted tissue. While generally benign, understanding its characteristics is important because it may mimic pathologic conditions such as infarcted tissue and cerebral edema.

Differential Assessment of Internal Jugular Vein Stenosis in Patients Undergoing CT and MRI with Contrast

OBJECTIVE

Internal Jugular Vein Stenosis (IJVS) is hypothesized to play a role in the pathogenesis of diverse neurological diseases. We sought to evaluate differences in IJVS assessment between CT and MRI in a retrospective patient cohort.

METHODS

We included consecutive patients who had both MRI of the brain and CT of the head and neck with contrast from 1 June 2021 to 30 June 2022 within the same admission. The degree of IJVS was categorized into five grades (0-IV).

RESULTS

A total of 35 patients with a total of 70 internal jugular (IJ) veins were included in our analysis. There was fair intermodality agreement in stenosis grades (κ = 0.220, 95% C.I. = [0.029, 0.410]), though categorical stenosis grades were significantly discordant between imaging modalities, with higher grades more frequent in MRI (χ2 = 27.378, p = 0.002). On CT-based imaging, Grade III or IV stenoses were noted in 17/70 (24.2%) IJs, whereas on MRI-based imaging, Grade III or IV stenoses were found in 40/70 (57.1%) IJs. Among veins with Grade I-IV IJVS, MRI stenosis estimates were significantly higher than CT stenosis estimates (77.0%, 95% C.I. [35.9-55.2%] vs. 45.6%, 95% C.I. [35.9-55.2%], p < 0.001).

CONCLUSION

MRI with contrast overestimates the degree of IJVS compared to CT with contrast. Consideration of this discrepancy should be considered in diagnosis and treatment planning in patients with potential IJVS-related symptoms.

Machine Learning in Clinical Trials: A Primer with Applications to Neurology

We reviewed foundational concepts in artificial intelligence (AI) and machine learning (ML) and discussed ways in which these methodologies may be employed to enhance progress in clinical trials and research, with particular attention to applications in the design, conduct, and interpretation of clinical trials for neurologic diseases. We discussed ways in which ML may help to accelerate the pace of subject recruitment, provide realistic simulation of medical interventions, and enhance remote trial administration via novel digital biomarkers and therapeutics. Lastly, we provide a brief overview of the technical, administrative, and regulatory challenges that must be addressed as ML achieves greater integration into clinical trial workflows.

Natural Language Processing of Radiology Reports to Detect Complications of Ischemic Stroke

BACKGROUND

Abstraction of critical data from unstructured radiologic reports using natural language processing (NLP) is a powerful tool to automate the detection of important clinical features and enhance research efforts. We present a set of NLP approaches to identify critical findings in patients with acute ischemic stroke from radiology reports of computed tomography (CT) and magnetic resonance imaging (MRI).

METHODS

We trained machine learning classifiers to identify categorical outcomes of edema, midline shift (MLS), hemorrhagic transformation, and parenchymal hematoma, as well as rule-based systems (RBS) to identify intraventricular hemorrhage (IVH) and continuous MLS measurements within CT/MRI reports. Using a derivation cohort of 2289 reports from 550 individuals with acute middle cerebral artery territory ischemic strokes, we externally validated our models on reports from a separate institution as well as from patients with ischemic strokes in any vascular territory.

RESULTS

In all data sets, a deep neural network with pretrained biomedical word embeddings (BioClinicalBERT) achieved the highest discrimination performance for binary prediction of edema (area under precision recall curve [AUPRC] > 0.94), MLS (AUPRC > 0.98), hemorrhagic conversion (AUPRC > 0.89), and parenchymal hematoma (AUPRC > 0.76). BioClinicalBERT outperformed lasso regression (p < 0.001) for all outcomes except parenchymal hematoma (p = 0.755). Tailored RBS for IVH and continuous MLS outperformed BioClinicalBERT (p < 0.001) and linear regression, respectively (p < 0.001).

CONCLUSIONS

Our study demonstrates robust performance and external validity of a core NLP tool kit for identifying both categorical and continuous outcomes of ischemic stroke from unstructured radiographic text data. Medically tailored NLP methods have multiple important big data applications, including scalable electronic phenotyping, augmentation of clinical risk prediction models, and facilitation of automatic alert systems in the hospital setting.

Multimodal deep learning for Alzheimer's disease dementia assessment

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

Anisocoria and Poor Pupil Reactivity by Quantitative Pupillometry in Patients With Intracranial Pathology

OBJECTIVES

To describe the prevalence and associated risk factors of new onset anisocoria (new pupil size difference of at least 1 mm) and its subtypes: new onset anisocoria accompanied by abnormal and normal pupil reactivities in patients with acute neurologic injuries.

DESIGN

We tested the association of patients who experienced new onset anisocoria subtypes with degree of midline shift using linear regression. We further explored differences between quantitative pupil characteristics associated with first-time new onset anisocoria and nonnew onset anisocoria at preceding observations using mixed effects logistic regression, adjusting for possible confounders.

SETTING

All quantitative pupil observations were collected at two neuro-ICUs by nursing staff as standard of care.

PATIENTS

We conducted a retrospective two-center study of adult patients with intracranial pathology in the ICU with at least a 24-hour stay and three or more quantitative pupil measurements between 2016 and 2018.

MEASUREMENTS AND MAIN RESULTS

We studied 221 patients (mean age 58, 41% women). Sixty-three percent experienced new onset anisocoria. New onset anisocoria accompanied by objective evidence of abnormal pupil reactivity occurring at any point during hospitalization was significantly associated with maximum midline shift (β = 2.27 per mm; p = 0.01). The occurrence of new onset anisocoria accompanied by objective evidence of normal pupil reactivity was inversely associated with death (odds ratio, 0.34; 95% CI, 0.16-0.71; p = 0.01) in adjusted analyses. Subclinical continuous pupil size difference distinguished first-time new onset anisocoria from nonnew onset anisocoria in up to four preceding pupil observations (or up to 8 hr prior). Minimum pupil reactivity between eyes also distinguished new onset anisocoria accompanied by objective evidence of abnormal pupil reactivity from new onset anisocoria accompanied by objective evidence of normal pupil reactivity prior to first-time new onset anisocoria occurrence.

CONCLUSIONS

New onset anisocoria occurs in over 60% of patients with neurologic emergencies. Pupil reactivity may be an important distinguishing characteristic of clinically relevant new onset anisocoria phenotypes. New onset anisocoria accompanied by objective evidence of abnormal pupil reactivity was associated with midline shift, and new onset anisocoria accompanied by objective evidence of normal pupil reactivity had an inverse relationship with death. Distinct quantitative pupil characteristics precede new onset anisocoria occurrence and may allow for earlier prediction of neurologic decline. Further work is needed to determine whether quantitative pupillometry sensitively/specifically predicts clinically relevant anisocoria, enabling possible earlier treatments.

Utilization of mental health services in pediatric patients surviving penetrating trauma resulting from interpersonal violence

BACKGROUND

Violent trauma has lasting psychological impacts. Our institution's Community Violence Response Team (CVRT) offers mental health services to trauma victims. We characterized implementation and determined factors associated with utilization by pediatric survivors of interpersonal violence-related penetrating trauma.

METHODS

Analysis included survivors (0-21 years) of violent penetrating injury at our institution (2011-2017). Injury and demographic data were collected. Nonparametric regression models determined factors associated with utilization.

RESULTS

There was initial rapid uptake of CVRT (2011-2013) after which it plateaued, serving >80% of eligible patients (2017). White race and higher injury severity were associated with receipt and duration of services. In post-hoc analysis, race was found to be associated with continued treatment but not with initial consultation.

CONCLUSION

Successful implementation required three years, aiding >80% of patients. CVRT is a blueprint to strengthen existing violence intervention programs. Efforts should be made to ensure that barriers to providing care, including those related to race, are overcome.

Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports

Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extraction could provide considerable improvement in identifying stroke in large datasets, triaging critical clinical reports, and quality improvement efforts. In this study, we developed and report a comprehensive framework studying the performance of simple and complex stroke-specific Natural Language Processing (NLP) and Machine Learning (ML) methods to determine presence, location, and acuity of ischemic stroke from radiographic text. We collected 60,564 Computed Tomography and Magnetic Resonance Imaging Radiology reports from 17,864 patients from two large academic medical centers. We used standard techniques to featurize unstructured text and developed neurovascular specific word GloVe embeddings. We trained various binary classification algorithms to identify stroke presence, location, and acuity using 75% of 1,359 expert-labeled reports. We validated our methods internally on the remaining 25% of reports and externally on 500 radiology reports from an entirely separate academic institution. In our internal population, GloVe word embeddings paired with deep learning (Recurrent Neural Networks) had the best discrimination of all methods for our three tasks (AUCs of 0.96, 0.98, 0.93 respectively). Simpler NLP approaches (Bag of Words) performed best with interpretable algorithms (Logistic Regression) for identifying ischemic stroke (AUC of 0.95), MCA location (AUC 0.96), and acuity (AUC of 0.90). Similarly, GloVe and Recurrent Neural Networks (AUC 0.92, 0.89, 0.93) generalized better in our external test set than BOW and Logistic Regression for stroke presence, location and acuity, respectively (AUC 0.89, 0.86, 0.80). Our study demonstrates a comprehensive assessment of NLP techniques for unstructured radiographic text. Our findings are suggestive that NLP/ML methods can be used to discriminate stroke features from large data cohorts for both clinical and research-related investigations.

Development and validation of an interpretable deep learning framework for Alzheimer's disease classification

Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and MRI to identify likely cases, yet effective practices remain variably applied and lacking in sensitivity and specificity. Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Our framework linked a fully convolutional network, which constructs high resolution maps of disease probability from local brain structure to a multilayer perceptron and generates precise, intuitive visualization of individual Alzheimer's disease risk en route to accurate diagnosis. The model was trained using clinically diagnosed Alzheimer's disease and cognitively normal subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 417) and validated on three independent cohorts: the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) (n = 382), the Framingham Heart Study (n = 102), and the National Alzheimer's Coordinating Center (NACC) (n = 582). Performance of the model that used the multimodal inputs was consistent across datasets, with mean area under curve values of 0.996, 0.974, 0.876 and 0.954 for the ADNI study, AIBL, Framingham Heart Study and NACC datasets, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n = 11), and high-risk cerebral regions predicted by the model closely tracked post-mortem histopathological findings. This framework provides a clinically adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease.

Delayed lung expansion after decortication in a case of trapped lung resulting from catamenial haemothorax

Herein, we report the case of a 35-year-old female with a trapped right lung secondary to catamenial haemothorax. Following surgical decortication, re-expansion of the lung was not observed until postoperative day 81. This delay represents a heretofore unencountered complication that should be considered in the surgical management of catamenial haemothorax due to thoracic endometriosis syndrome.

Peripheral Blood Lymphocytes and Platelets Are Prognostic in Surgical pT1 Non-Small Cell Lung Cancer

BACKGROUND

There is a paucity of prognostic factors for patients with stage I non-small cell lung cancer (NSCLC) undergoing operations. We investigated the prognostic role of preoperative complete blood count values in patients with stage I NSCLC patients undergoing operations.

METHODS

A retrospective medical record review was performed of patients who underwent operations for stage I NSCLC between 2000 and 2015. Patients who died within 30 days of the operations were excluded. The primary end point was recurrence. Preoperative complete blood count values were analyzed, and a median value was used as the cutoff. Statistical analysis used χ² and t tests along with univariate and multivariate analyses by Cox regression modeling.

RESULTS

The study included 103 patients. A high lymphocyte count was significantly associated with recurrence (5-year recurrence-free survival [RFS] of 69.8% for high vs 95.7% for low, P = .003), as well as high platelet (5-year RFS of 72.0% for high vs 91.8% for low, P = .02). Independent prognostic factors on multivariate analysis were high lymphocyte (hazard ratio [HR], 7.27; P = .005) and platelet counts (HR, 7.49; P = .003) as well as tumor (HR, 5.40; P = .008) and treatment characteristics (HR, 4.59; P = .01). Among patients with pT1 lesions, high lymphocyte (HR, 8.41; P = .03) and high platelet counts (HR, 19.78; P = .004) remained independent prognostic factors. Neither NLR nor PLR were significantly associated with recurrence.

CONCLUSIONS

In patients with pathologic stage I NSCLC undergoing surgical resection, the preoperative blood count from peripheral blood may provide prognostic value. Of significance, in patients with pT1 N0 NSCLC, high lymphocyte count and high platelet count were associated with higher recurrence.

An ion trap time-of-flight mass spectrometer with high mass resolution for cold trapped ion experiments

Trapping molecular ions that have been sympathetically cooled with laser-cooled atomic ions is a useful platform for exploring cold ion chemistry. We designed and characterized a new experimental apparatus for probing chemical reaction dynamics between molecular cations and neutral radicals at temperatures below 1 K. The ions are trapped in a linear quadrupole radio-frequency trap and sympathetically cooled by co-trapped, laser-cooled, atomic ions. The ion trap is coupled to a time-of-flight mass spectrometer to readily identify product ion species and to accurately determine trapped ion numbers. We discuss, and present in detail, the design of this ion trap time-of-flight mass spectrometer and the electronics required for driving the trap and mass spectrometer. Furthermore, we measure the performance of this system, which yields mass resolutions of m/Δm ≥ 1100 over a wide mass range, and discuss its relevance for future measurements in chemical reaction kinetics and dynamics.

The development of a population of 4D pediatric XCAT phantoms for imaging research and optimization

PURPOSE

We previously developed a set of highly detailed 4D reference pediatric extended cardiac-torso (XCAT) phantoms at ages of newborn, 1, 5, 10, and 15 yr with organ and tissue masses matched to ICRP Publication 89 values. In this work, we extended this reference set to a series of 64 pediatric phantoms of varying age and height and body mass percentiles representative of the public at large. The models will provide a library of pediatric phantoms for optimizing pediatric imaging protocols.

METHODS

High resolution positron emission tomography-computed tomography data obtained from the Duke University database were reviewed by a practicing experienced radiologist for anatomic regularity. The CT portion of the data was then segmented with manual and semiautomatic methods to form a target model defined using nonuniform rational B-spline surfaces. A multichannel large deformation diffeomorphic metric mapping algorithm was used to calculate the transform from the best age matching pediatric XCAT reference phantom to the patient target. The transform was used to complete the target, filling in the nonsegmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. The mass for each major tissue was calculated and compared to linearly interpolated ICRP values for different ages.

RESULTS

Sixty four new pediatric phantoms were created in this manner. Each model contains the same level of detail as the original XCAT reference phantoms and also includes parameterized models for the cardiac and respiratory motions. For the phantoms that were 10 yr old and younger, we included both sets of reproductive organs. This gave them the capability to simulate both male and female anatomy. With this, the population can be expanded to 92. Wide anatomical variation was clearly seen amongst the phantom models, both in organ shape and size, even for models of the same age and sex. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities.

CONCLUSIONS

This work provides a large cohort of highly detailed pediatric phantoms with 4D capabilities of varying age, height, and body mass. The population of phantoms will provide a vital tool with which to optimize 3D and 4D pediatric imaging devices and techniques in terms of image quality and radiation-absorbed dose.

A set of 4D pediatric XCAT reference phantoms for multimodality research

PURPOSE

The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols.

METHODS

Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection.

RESULTS

The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities.

CONCLUSIONS

The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.

Macro- and microstructural changes in patients with spinocerebellar ataxia type 6: assessment of phylogenetic subdivisions of the cerebellum and the brain stem

BACKGROUND AND PURPOSE

Site-specific degeneration patterns of the infratentorial brain in relation to phylogenetic origins may relate to symptoms in patients with spinocerebellar degeneration, but the patterns are still unclear. We investigated macro- and microstructural changes of the infratentorial brain based on phylogenetic origins and their correlation with symptoms in patients with spinocerebellar ataxia type 6.

MATERIALS AND METHODS

MR images of 9 patients with spinocerebellar ataxia type 6 and 9 age- and sex-matched controls were obtained. We divided the infratentorial brain on the basis of phylogenetic origins and performed an atlas-based analysis. Comparisons of the 2 groups and a correlation analysis assessed with the International Cooperative Ataxia Rating Scale excluding age effects were performed.

RESULTS

A significant decrease of fractional volume and an increase of mean diffusivity were seen in all subdivisions of the cerebellum and in all the cerebellar peduncles except mean diffusivity in the inferior cerebellar peduncle in patients compared with controls (P < .0001 to <.05). The bilateral anterior lobes showed the strongest atrophy. Fractional volume decreased mainly in old regions, whereas mean diffusivity increased mainly in new regions of the cerebellum. Reflecting this tendency, the International Cooperative Ataxia Rating Scale total score showed strong correlations in fractional volume in the right flocculonodular lobe and the bilateral deep structures and in mean diffusivity in the bilateral posterior lobes (r = 0.73 to ±0.87).

CONCLUSIONS

We found characteristic macro- and microstructural changes, depending on phylogenetic regions of the infratentorial brain, that strongly correlated with clinical symptoms in patients with spinocerebellar ataxia type 6.

Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization

PURPOSE

The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms.

METHODS

The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models.

RESULTS

Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve as a jumping point from which to create an unlimited number of 3D and 4D variations for imaging research.

CONCLUSIONS

A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. The series of anatomically variable phantoms developed in this work provide a valuable resource for investigating 3D and 4D imaging devices and the effects of anatomy and motion in imaging. Combined with Monte Carlo simulation programs, the phantoms also provide a valuable tool to investigate patient-specific dose and image quality, and optimization for adults undergoing imaging procedures.

Representing and computing regular languages on massively parallel networks

A general method is proposed for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach establishes the formal connection of rules to Chomsky grammars and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibbs representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochastic diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs probability law. This coupling yields the result that fully parallel stochastic cellular automata can be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determine the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.

Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly

Structural deformity of the hippocampus is characteristic of individuals with very mild and mild forms of dementia of the Alzheimer type (DAT). The purpose of this study was to determine whether a similar deformity of the hippocampus can predict the onset of dementia in nondemented elders. Using high dimensional diffeomorphic transformations of a neuroanatomical template, hippocampal volumes and surfaces were defined in 49 nondemented elders; the hippocampal surface was subsequently partitioned into three zones (i.e., lateral, superior and inferior-medial), which were proximal to the underlying CA1 subfield, CA2-4 subfields plus dentate gyrus, and subiculum, respectively. Annual clinical assessments using the Clinical Dementia Rating scale (CDR), where CDR 0 indicates no dementia and CDR 0.5 indicates very mild dementia, were then performed for a mean of 4.9 years (range 0.9-7.1 years) to monitor subjects who converted from CDR 0 to CDR 0.5. Inward variation of the lateral zone and left hippocampal volume significantly predicted conversion to CDR 0.5 in separate Cox proportional hazards models. When hippocampal surface variation and volume were included in a single model, inward variation of the lateral zone of the left hippocampal surface was selected as the only significant predictor of conversion. The pattern of hippocampal surface deformation observed in nondemented subjects who later converted to CDR 0.5 was similar to the pattern of hippocampal surface deformation previously observed to discriminate subjects with very mild DAT and nondemented subjects. These results suggest that inward deformation of the left hippocampal surface in a zone corresponding to the CA1 subfield is an early predictor of the onset of DAT in nondemented elderly subjects.

3D brain mapping using a deformable neuroanatomy

This paper presents two different mathematical methods that can be used separately or in conjunction to accommodate shape variabilities between normal human neuroanatomies. Both methods use a digitized textbook to represent the complex structure of a typical normal neuroanatomy. Probabilistic transformations on the textbook coordinate system are defined to accommodate shape differences between the textbook and images of other normal neuroanatomies. The transformations are constrained to be consistent with the physical properties of deformable elastic solids in the first method and those of viscous fluids in the second. Results presented in this paper demonstrate how a single deformable textbook can be used to accommodate normal shape variability.

Statistics on diffeomorphisms via tangent space representations

In this paper, we present a linear setting for statistical analysis of shape and an optimization approach based on a recent derivation of a conservation of momentum law for the geodesics of diffeomorphic flow. Once a template is fixed, the space of initial momentum becomes an appropriate space for studying shape via geodesic flow since the flow at any point along the geodesic is completely determined by the momentum at the origin through geodesic shooting equations. The space of initial momentum provides a linear representation of the nonlinear diffeomorphic shape space in which linear statistical analysis can be applied. Specializing to the landmark matching problem of Computational Anatomy, we derive an algorithm for solving the variational problem with respect to the initial momentum and demonstrate principal component analysis (PCA) in this setting with three-dimensional face and hippocampus databases.

Labeled cortical mantle distance maps of the cingulate quantify differences between dementia of the Alzheimer type and healthy aging

The cingulate gyri in 37 subjects with and without early dementia of the Alzheimer type (DAT) were studied by using MRI at 1.0 mm3 isotropic resolution. Groups were segregated into young controls (n = 10), age-matched normal controls (n = 10), very mild DAT (n = 8), and mild DAT (n = 9). By using automated Bayesian segmentation of the cortex and gray matter/white matter (GM/WM) isosurface generation, tissue compartments were labeled into gray, white, and cerebrospinal fluid as a function of distance from the GM/WM isosurface. Cortical mantle distance maps are generated profiling the GM volume and cortical mantle distribution as a function of distance from the cortical surface. Probabilistic tests based on generalizations of Wilcoxon-Mann-Whitney tests were applied to quantify cortical mantle distribution changes with normal and abnormal aging. We find no significant change between young controls and healthy aging as measured by the GM volume and cortical mantle distribution as a function of distance in both anterior and posterior regions of the cingulate. Significant progression of GM loss is seen in the very mild DAT and mild DAT groups in all areas of the cingulate. Posterior regions show both GM volume loss as well as significant cortical mantle distribution decrease with the onset of mild DAT. The "shape of the cortical mantle" as measured by the cortical mantle distance profiles manifests a pronounced increase in variability with mild DAT.

Dynamic programming generation of boundaries of local coordinatized submanifolds in the neocortex: application to the planum temporale

Dynamic programming is used to define boundaries of cortical submanifolds with focus on the planum temporale (PT) of the superior temporal gyrus (STG), which has been implicated in a variety of neuropsychiatric disorders. To this end, automated methods are used to generate the PT manifold from 10 high-resolution MRI subvolumes ROI masks encompassing the STG. A procedure to define the subvolume ROI masks from original MRI brain scans is developed. Bayesian segmentation is then used to segment the subvolumes into cerebrospinal fluid, gray matter (GM), and white matter (WM). 3D isocontouring using the intensity value at which there is equal probability of GM and WM is used to reconstruct the triangulated graph representing the STG cortical surface, enabling principal curvature at each point on the graph to be computed. Dynamic programming is used to delineate the PT manifold by tracking principal curves from the retro-insular end of the Heschl's gyrus (HG) to the STG, along the posterior STG up to the start of the ramus and back to the retro-insular end of the HG. A coordinate system is then defined on the PT manifold. The origin is defined by the retro-insular end of the HG and the y-axis passes through the point on the posterior STG where the ramus begins. Automated labeling of GM in the STG is robust with L(1) distances between Bayesian and manual segmentation in the range 0.001-0.12 (n = 20). PT reconstruction is also robust with 90% of the vertices of the reconstructed PT within about 1 voxel (n = 20) from semiautomated contours. Finally, the reliability index (based on interrater intraclass correlation) for the surface area derived from repeated reconstructions is 0.96 for the left PT and 0.94 for the right PT, thus demonstrating the robustness of dynamic programming in defining a coordinate system on the PT. It provides a method with potential significance in the study of neuropsychiatric disorders.

Validating cortical surface analysis of medial prefrontal cortex

This paper describes cortical analysis of 19 high resolution MRI subvolumes of medial prefrontal cortex (MPFC), a region that has been implicated in major depressive disorder. An automated Bayesian segmentation is used to delineate the MRI subvolumes into cerebrospinal fluid (CSF), gray matter (GM), white matter (WM), and partial volumes of either CSF/GM or GM/WM. The intensity value at which there is equal probability of GM and GM/WM partial volume is used to reconstruct MPFC cortical surfaces based on a 3-D isocontouring algorithm. The segmented data and the generated surfaces are validated by comparison with hand segmented data and semiautomated contours, respectively. The L(1) distances between Bayesian and hand segmented data are 0.05-0.10 (n = 5). Fifty percent of the voxels of the reconstructed surface lie within 0.12-0.28 mm (n = 14) from the semiautomated contours. Cortical thickness metrics are generated in the form of frequency of occurrence histograms for GM and WM labelled voxels as a function of their position from the cortical surface. An algorithm to compute the surface area of the GM/WM interface of the MPFC subvolume is described. These methods represent a novel approach to morphometric chacterization of regional cortex features which may be important in the study of psychiatric disorders such as major depression.

Statistical analysis of hippocampal asymmetry in schizophrenia

The asymmetry of brain structures has been studied in schizophrenia to better understand its underlying neurobiology. Brain regions of interest have previously been characterized by volumes, cross-sectional and surface areas, and lengths. Using high-dimensional brain mapping, we have developed a statistical method for analyzing patterns of left-right asymmetry of the human hippocampus taken from high-resolution MR scans. We introduce asymmetry measures that capture differences in the patterns of high-dimensional vector fields between the left and right hippocampus surfaces. In 15 pairs of subjects previously studied (J. G. Csernansky et al., 1998, Proc. Natl. Acad. Sci. USA 95, 11406-11411). we define the difference in hippocampal asymmetry patterns between the groups. Volume analysis indicated a large normative asymmetry between left and right hippocampus (R > L), and shape analysis allowed us to visualize the normative asymmetry pattern of the hippocampal surfaces. We observed that the right hippocampus was wider along its lateral side in both schizophrenia and control subjects. Also, while patterns of hippocampal asymmetry were generally similar in the schizophrenia and control groups, a principal component analysis based on left-right asymmetry vector fields detected a statistically significant difference between the two groups, specifically related to the subiculum.

Mapping visual cortex in monkeys and humans using surface-based atlases

We have used surface-based atlases of the cerebral cortex to analyze the functional organization of visual cortex in humans and macaque monkeys. The macaque atlas contains multiple partitioning schemes for visual cortex, including a probabilistic atlas of visual areas derived from a recent architectonic study, plus summary schemes that reflect a combination of physiological and anatomical evidence. The human atlas includes a probabilistic map of eight topographically organized visual areas recently mapped using functional MRI. To facilitate comparisons between species, we used surface-based warping to bring functional and geographic landmarks on the macaque map into register with corresponding landmarks on the human map. The results suggest that extrastriate visual cortex outside the known topographically organized areas is dramatically expanded in human compared to macaque cortex, particularly in the parietal lobe.

Early DAT is distinguished from aging by high-dimensional mapping of the hippocampus. Dementia of the Alzheimer type

OBJECTIVE

To determine the feasibility of using high-dimensional brain mapping (HDBM) to assess the structure of the hippocampus in older human subjects, and to compare measurements of hippocampal volume and shape in subjects with early dementia of the Alzheimer type (DAT) and in healthy elderly and younger control subjects.

BACKGROUND

HDBM represents the typical structures of the brain via the construction of templates and addresses their variability by probabilistic transformations applied to the templates. Local application of the transformations throughout the brain (i.e., high dimensionality) makes HDBM especially valuable for defining subtle deformities in brain structures such as the hippocampus.

METHODS

MR scans were obtained in 18 subjects with very mild DAT, 18 healthy elderly subjects, and 15 healthy younger subjects. HDBM was used to obtain estimates of left and right hippocampal volume and eigenvectors that represented the principal dimensions of hippocampal shape differences among the subject groups.

RESULTS

Hippocampal volume loss and shape deformities observed in subjects with DAT distinguished them from both elderly and younger control subjects. The pattern of hippocampal deformities in subjects with DAT was largely symmetric and suggested damage to the CA1 hippocampal subfield. Hippocampal shape changes were also observed in healthy elderly subjects, which distinguished them from healthy younger subjects. These shape changes occurred in a pattern distinct from the pattern seen in DAT and were not associated with substantial volume loss.

CONCLUSIONS

Assessments of hippocampal volume and shape derived from HDBM may be useful in distinguishing early DAT from healthy aging.

Bayesian construction of geometrically based cortical thickness metrics

This paper describes the construction of cortical metrics quantifying the probabilistic occurrence of gray matter, white matter, and cerebrospinal fluid compartments in their correlation to the geometry of the neocortex as measured in 0.5-1.0 mm magnetic resonance imagery. These cortical profiles represent the density of the tissue types as a function of distance to the cortical surface. These metrics are consistent when generated across multiple brains indicating a fundamental property of the neocortex. Methods are proposed for incorporating such metrics into automated Bayes segmentation.

Mesial temporal sclerosis and temporal lobe epilepsy: MR imaging deformation-based segmentation of the hippocampus in five patients

In five patients with mesial temporal sclerosis, the authors verified the precision and reproducibility of hippocampal segmentations with deformation-based magnetic resonance (MR) imaging. The overall percentage overlap between automated segmentations was 92.8% (SD, 3.5%), between manual segmentations was 73.1% (SD, 9.5%), and between automated and manual segmentations was 74.8% (SD, 10.3%). Deformation-based hippocampal segmentations provided a precise method of hippocampal volume measurement in this patient population.

Magnetic resonance imaging deformation-based segmentation of the hippocampus in patients with mesial temporal sclerosis and temporal lobe epilepsy

We compared manual and automated segmentations of the hippocampus in patients with mesial temporal sclerosis. This comparison showed good precision of the deformation-based automated segmentations.

Landmark matching via large deformation diffeomorphisms

This paper describes the generation of large deformation diffeomorphisms phi:Omega=[0,1]3<-->Omega for landmark matching generated as solutions to the transport equation dphi(x,t)/dt=nu(phi(x,t),t),epsilon[0,1] and phi(x,0)=x, with the image map defined as phi(.,1) and therefore controlled via the velocity field nu(.,t),epsilon[0,1]. Imagery are assumed characterized via sets of landmarks {xn, yn, n=1, 2, ..., N}. The optimal diffeomorphic match is constructed to minimize a running smoothness cost parallelLnu parallel2 associated with a linear differential operator L on the velocity field generating the diffeomorphism while simultaneously minimizing the matching end point condition of the landmarks. Both inexact and exact landmark matching is studied here. Given noisy landmarks xn matched to yn measured with error covariances Sigman, then the matching problem is solved generating the optimal diffeomorphism phi;(x,1)=integral0(1)nu(phi(x,t),t)dt+x where nu(.)=argmin(nu.)integral1(0) integralOmega parallelLnu(x,t) parallel2dxdt +Sigman=1N[yn-phi(xn,1)] TSigman(-1)[yn-phi(xn,1)]. Conditions for the existence of solutions in the space of diffeomorphisms are established, with a gradient algorithm provided for generating the optimal flow solving the minimum problem. Results on matching two-dimensional (2-D) and three-dimensional (3-D) imagery are presented in the macaque monkey.

Brain segmentation and the generation of cortical surfaces

This paper describes methods for white matter segmentation in brain images and the generation of cortical surfaces from the segmentations. We have developed a system that allows a user to start with a brain volume, obtained by modalities such as MRI or cryosection, and constructs a complete digital representation of the cortical surface. The methodology consists of three basic components: local parametric modeling and Bayesian segmentation; surface generation and local quadratic coordinate fitting; and surface editing. Segmentations are computed by parametrically fitting known density functions to the histogram of the image using the expectation maximization algorithm [DLR77]. The parametric fits are obtained locally rather than globally over the whole volume to overcome local variations in gray levels. To represent the boundary of the gray and white matter we use triangulated meshes generated using isosurface generation algorithms [GH95]. A complete system of local parametric quadratic charts [JWM+95] is superimposed on the triangulated graph to facilitate smoothing and geodesic curve tracking. Algorithms for surface editing include extraction of the largest closed surface. Results for several macaque brains are presented comparing automated and hand surface generation.

Hippocampal morphometry in schizophrenia by high dimensional brain mapping

Theories of the pathophysiology of schizophrenia have implicated the hippocampus, but controversy remains regarding hippocampal abnormalities in patients with schizophrenia. In vivo studies of hippocampal anatomy using high resolution magnetic resonance scanning and manual methods for volumetric measurement have yielded inconclusive results, perhaps because of the normal variability in hippocampal volume and the error involved in manual measurement techniques. To resolve this controversy, high dimensional transformations of a computerized brain template were used to compare hippocampal volumes and shape characteristics in 15 matched pairs of schizophrenia and control subjects. The transformations were derived from principles of general pattern matching and were constrained according to the physical properties of fluids. The analysis and comparison of hippocampal shapes based on these transformations were far superior to the comparison of hippocampal volumes or other global indices of hippocampal anatomy in showing a statistically significant difference between the two groups. In the schizophrenia subjects, hippocampal shape deformations were found to be localized to subregions of the structure that send projections to prefrontal cortex. The results of this study demonstrate that abnormalities of hippocampal anatomy occur in schizophrenia and support current hypotheses that schizophrenia involves a disturbance of hippocampal-prefrontal connections. These results also show that comparisons of neuroanatomical shapes can be more informative than volume comparisons for identifying individuals with neuropsychiatric diseases, such as schizophrenia.

Functional and structural mapping of human cerebral cortex: solutions are in the surfaces

The human cerebral cortex is notorious for the depth and irregularity of its convolutions and for its variability from one individual to the next. These complexities of cortical geography have been a chronic impediment to studies of functional specialization in the cortex. In this report, we discuss ways to compensate for the convolutions by using a combination of strategies whose common denominator involves explicit reconstructions of the cortical surface. Surface-based visualization involves reconstructing cortical surfaces and displaying them, along with associated experimental data, in various complementary formats (including three-dimensional native configurations, two-dimensional slices, extensively smoothed surfaces, ellipsoidal representations, and cortical flat maps). Generating these representations for the cortex of the Visible Man leads to a surface-based atlas that has important advantages over conventional stereotaxic atlases as a substrate for displaying and analyzing large amounts of experimental data. We illustrate this by showing the relationship between functionally specialized regions and topographically organized areas in human visual cortex. Surface-based warping allows data to be mapped from individual hemispheres to a surface-based atlas while respecting surface topology, improving registration of identifiable landmarks, and minimizing unwanted distortions. Surface-based warping also can aid in comparisons between species, which we illustrate by warping a macaque flat map to match the shape of a human flat map. Collectively, these approaches will allow more refined analyses of commonalities as well as individual differences in the functional organization of primate cerebral cortex.

Effects of finasteride on hematuria associated with benign prostatic hyperplasia: long-term follow-up

OBJECTIVES

To report long-term follow-up in 18 patients with gross hematuria associated with benign prostatic hyperplasia (BPH) who have been treated with finasteride and to report preliminary follow-up in an additional 10 patients.

METHODS

The charts of the 18 original patients, and 10 additional patients who had been placed on finasteride (5 mg daily) for intermittent gross hematuria associated with BPH, were reviewed. All had evaluations that were negative for tumor. A hematuria grading system was devised using grades 0, 1, 2, and 3 (grade 0 the least severe, grade 3 the most severe hematuria).

RESULTS

Sixteen of 18 patients have continued finasteride therapy. Mean follow-up is 31 months (range 10 to 47). Twelve had undergone prior prostatectomy. In this group, 3 patients had grade 1, 5 grade 2, and 4 grade 3 hematuria prior to treatment with finasteride. During finasteride therapy, 9 patients had grade 0, 2 grade 1 (pretreatment grades 2 and 3), and 1 grade 3 (pretreatment grade 3) hematuria. Of the 4 patients without prior prostate surgery, 2 had grade 0 (pretreatment grades 1 and 3), and 2 had grade 1 (pretreatment grade 2) hematuria. In summary, 14 of 16 patients improved according to their hematuria grade. We have since added another 10 patients to our study, with a mean follow-up of 11 months. Six of 7 patients who had previous prostatectomies in this group now have grade 0 hematuria. Overall, 8 of the 10 have improved according to hematuria grade.

CONCLUSIONS

Long-term follow-up has confirmed the efficacy of finasteride in treating gross hematuria associated with BPH and we now recommend finasteride as first line therapy in the treatment of BPH-associated gross hematuria. reserved.

Curve matching on brain surfaces using Frenet distances

This paper describes methods for diffeomorphic matching of curves on brain surfaces. Distances between curves are defined by Frenet representation via speed, curvature, and torsion. The curvematching algorithm is based on bipartite graph matching, with weights defined by the Frenet distance over diffeomorphic maps of one curve onto the other (Sedgewick [1983]: Algorithms). We follow Khaneja ([1996]: Statistics and Geometry of Cortical Features) and define fundus curves on the brain surfaces as extremal curvature lines generated using dynamic programming. Examples are shown for fundus curve matchings on macaque brain surfaces.

Volumetric transformation of brain anatomy

This paper presents diffeomorphic transformations of three-dimensional (3-D) anatomical image data of the macaque occipital lobe and whole brain cryosection imagery and of deep brain structures in human brains as imaged via magnetic resonance imagery. These transformations are generated in a hierarchical manner, accommodating both global and local anatomical detail. The initial low-dimensional registration is accomplished by constraining the transformation to be in a low-dimensional basis. The basis is defined by the Green's function of the elasticity operator placed at predefined locations in the anatomy and the eigenfunctions of the elasticity operator. The high-dimensional large deformations are vector fields generated via the mismatch between the template and target-image volumes constrained to be the solution of a Navier-Stokes fluid model. As part of this procedure, the Jacobian of the transformation is tracked, insuring the generation of diffeomorphisms. It is shown that transformations constrained by quadratic regularization methods such as the Laplacian, biharmonic, and linear elasticity models, do not ensure that the transformation maintains topology and, therefore, must only be used for coarse global registration.

Stochastic threshold characterization of the intensity of active channel dynamical action potential generation

Stochastic threshold characterization of the intensity of active channel dynamical action potential generation. J. Neurophysiol. 78: 2616-2630, 1997. This paper develops a stochastic intensity description for action potential generation formulated in terms of stochastic processes, which are direct analogues of the physiological processes of the pre- and postsynaptic complex of the cochlear nerve: 1) neurotransmitter release is modeled as an inhomogeneous Poisson counting process with release intensity mu t, 2) the excitatory postsynaptic conductance (EPSC) process is modeled as a marked, linearly filtered Poisson process resulting from the linear superposition of standard shaped postsynaptic conductances of size G, and 3) action potential generation is modeled as resulting from the EPSC exceeding a random threshold determined by active channel dynamics of the Hodgkin-Huxley type. The random threshold is defined to be the least upper bound in the size of a standard-shaped neurotransmitter release injected at time t given the previous action potential time and the number of releases occurring in a short preconditioning time increment. The action potential process is modeled as a self-exciting point process with stochastic intensity resulting from the probability that the random threshold process crosses the threshold in some small time increment that is a function of time since previous action potential, release intensity, and the probability that a single synaptic event exceeds the stochastic threshold. The stochastic intensity model is consistent with a direct simulation of the nonlinear Hodgkin-Huxley differential equations over a variety of parameters for the vesicle release intensity, vesicle size, vesicle duration, and temperatures. Results are presented showing that the regularity properties seen in the vestibular primary afferent in the lizard, Calotes versicolor, associated with a slow-to-activate potassium channel resulting in a long afterhyperpolarization can be accommodated directly by the stochastic intensity description. The stimulus dependence of the model is attributed to synaptic transmission and the probabilistic nature to the threshold conductance process, which is dependent upon the EPSC process. The stochastic intensity is seen to have a form consistent with the phenomenologically based Siebert-Gaumond model, a stimulus-related function of time multiplied by a refractory-related function of time since previous action potential.

Apoptosis in the rat penis after penile denervation

PURPOSE

Despite the advances in nerve sparing prostatectomy for prostate cancer, some patients develop impotence or subjectively complain of a decrease in penile size. We hypothesized that these clinical observations may be explained by injury to the cavernous nerves resulting in programmed cell death (apoptosis) within the penis. We utilized a rat model of penile denervation in order to demonstrate apoptosis after denervation.

METHODS AND MATERIALS

Fifteen male Sprague Dawley rats underwent abdominal exploration and bilateral cavernous neurotomy. Fifteen sham operations were performed as normal controls. The rats were sacrificed on postoperative day 1,2,3,6, and 10 and their penises were harvested. Messenger RNA was extracted and probed on a northern blot for sulfated glycoprotein-2 (SGP-2). SGP-2 is a gene product reported to be elevated in apoptotic tissues. Separate denervated and sham rats were used for DNA extraction (sacrificed postoperative day #2) in order to demonstrate the internucleosomal DNA fragmentation (laddering) found in apoptotic tissues. In addition, in situ histology was performed with ISEL techniques (in situ end labeling) to stain for apoptotic nuclei in denervated rats.

RESULTS

Northern blot analysis showed a large increase in SGP-2 mRNA expression in the denervated rats with little detected in the sham operated group. DNA extraction studies revealed the presence of internucleosomal DNA fragmentation on agarose gel (a marker for apoptosis) in the denervated group versus intact high molecular weight DNA in the sham rats. In addition, in situ staining of denervated penile erectile tissue demonstrated apoptotic nuclei in the cavernous tissue.

CONCLUSION

Apoptosis of penile erectile tissue occurs after denervation of the rat penis. This has not been previously described in the literature and may offer some explanation at the molecular level concerning the mechanism of impotence and/or decrease in penile size after radical prostatectomy.

Three-dimensional hippocampal MR morphometry with high-dimensional transformation of a neuroanatomic atlas

PURPOSE

To test automated three-dimensional magnetic resonance (MR) imaging morphometry of the human hippocampus, to determine the potential gain in precision compared with conventional manual morphometry.

MATERIAL AND METHODS

A canonical three-dimensional MR image atlas was used as a deformable template and automatically matched to three-dimensional MR images of 10 individuals (five healthy and five schizophrenic subjects). A subvolume containing the hippocampus was defined by using 16 landmarks that constrained the automated search for hippocampal boundaries. Transformation of the hippocampus template was automatically performed by using global pattern matching through a sequence of low-then high-dimensional translations, rotations, and scalings.

RESULTS

The average test-retest volume difference measured with the automatic method was 3.1%, compared with the manual test-retest difference of 7.1%. Correlation between automated and manually determined volumes demonstrated the validity of the automated technique (intraclass correlation coefficient = .86).

CONCLUSION

The automated method estimates hippocampal volumes with less variability (ie, lower variance) than that of manual out-lining.

Automatic target recognition organized via jump-diffusion algorithms

Proposes a framework for simultaneous detection, tracking, and recognition of objects via data fused from multiple sensors. Complex dynamic scenes are represented via the concatenation of simple rigid templates. The variability of the infinity of pose is accommodated via the actions of matrix Lie groups extending the templates to individual instances. The variability of target number and target identity is accommodated via the representation of scenes as unions of templates of varying types, with the associated group transformations of varying dimension. We focus on recognition in the air-to-ground and ground-to-air scenarios. The remote sensing data is organized around both the coarse scale associated with detection as provided by tracking and range radars, along with the fine scale associated with pose and identity supported by high-resolution optical, forward looking infrared and delay-Doppler radar imagers. A Bayesian approach is adopted in which prior distributions on target scenarios are constructed via dynamical models of the targets of interest. These are combined with physics-based sensor models which define conditional likelihoods for the coarse/fine scale sensor data given the underlying scene. Inference via the Bayes posterior is organized around a random sampling algorithm based on jump-diffusion processes. New objects are detected and object identities are recognized through discrete jump moves through parameter space, the algorithm exploring scenes of varying complexity as it proceeds. Between jumps, the scale and rotation group transformations are generated via continuous diffusions in order to smoothly deform templates into individual instances of objects.

An enormous testicular sex cord/gonadal stromal tumor

Testicular sex cord/gonadal stromal tumors are relatively rare non-germ cell neoplasms. The authors describe an unusual case of an enormous unclassified sex cord/gonadal stromal tumor, which histologically appeared benign. The implications of the pathological findings and the surgical management are discussed.

Etiology of voiding dysfunction in men less than 50 years of age

OBJECTIVES

Chronic lower urinary tract symptoms in young men are often attributed to misdiagnosed chronic nonbacterial prostatitis. The purpose of this study was to analyze etiology of chronic voiding dysfunction in men less than 50 years of age.

METHODS

The videourodynamic studies of 137 men 50 years of age or less with chronic voiding dysfunction, performed between January 1990 and October 1995, were retrospectively analyzed.

RESULTS

The distribution of urodynamic abnormalities included 74 (54%) patients with primary vesical neck obstruction, 33 (24%) with obstruction localized to membranous urethra (pseudodyssnergia), 23 (17%) with impaired bladder contractility, and the remaining 7 (5%) with an acontractile bladder. Detrusor instability was present in 67 men (49%).

CONCLUSIONS

Voiding dysfunction among young men is common and is often misdiagnosed. Videourodynamic evaluation is very useful in establishing the correct diagnosis and ultimately in delivery of appropriate therapy.

Hippocampal MR imaging morphometry by means of general pattern matching

PURPOSE

To determine the repeatability and validity of a pattern-matching method for the segmentation and measurement of hippocampi on magnetic resonance (MR) images.

MATERIALS AND METHODS

Comparable two-dimensional MR images obtained in 18 subjects (nine healthy control subjects [six men, three women; aged 24-54 years] and nine patients with schizophrenia [six men, three women; aged 22-61 years]) were twice segmented manually and twice segmented by using pattern matching with digital atlas transformation. The atlas transformation was accomplished in two steps: global followed by local matching. Global matching was performed with use of landmarks; local matching was performed with use of a viscous fluid model.

RESULTS

The mean percentage of difference between two atlas-based measurements was 1.33% +/- 1.23 (+/- standard deviation); that between two manual measurements was 4.67% +/- 4.71. The validity of the atlas transformation measurements was demonstrated by means of the high correlation (intraclass correlation coefficient = .96) with manual segmentation measurements. Schizophrenic hippocampal areas tended to be smaller; however, no differences in hippocampal shape were found between patients with schizophrenia and patients with control subjects.

CONCLUSION

General pattern matching of a digital brain atlas to an individual MR image is a mathematically robust method of measurement that is reproducible and less variable than manual measurement.

Deformable templates using large deformation kinematics

A general automatic approach is presented for accommodating local shape variation when mapping a two-dimensional (2-D) or three-dimensional (3-D) template image into alignment with a topologically similar target image. Local shape variability is accommodated by applying a vector-field transformation to the underlying material coordinate system of the template while constraining the transformation to be smooth (globally positive definite Jacobian). Smoothness is guaranteed without specifically penalizing large-magnitude deformations of small subvolumes by constraining the transformation on the basis of a Stokesian limit of the fluid-dynamical Navier-Stokes equations. This differs fundamentally from quadratic penalty methods, such as those based on linearized elasticity or thin-plate splines, in that stress restraining the motion relaxes over time allowing large-magnitude deformations. Kinematic nonlinearities are inherently necessary to maintain continuity of structures during large-magnitude deformations, and are included in all results. After initial global registration, final mappings are obtained by numerically solving a set of nonlinear partial differential equations associated with the constrained optimization problem. Automatic regridding is performed by propagating templates as the nonlinear transformations evaluated on a finite lattice become singular. Application of the method to intersubject registration of neuroanatomical structures illustrates the ability to account for local anatomical variability.