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Biomedical subjects

David Haynor

Publications and source records attributed to David Haynor.

8 recordsLinked to original sources
PubMed2006

Impact of basilar artery vasospasm on outcome in patients with severe cerebral vasospasm after aneurysmal subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: The purpose of the present study was to evaluate the impact of basilar artery (BA) vasospasm on outcome in patients with severe vasospasm after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: Sixty-five patients with clinically suspect severe cerebral vasospasm after aSAH underwent cerebral angiography before endovascular treatment. Vasospasm severity was assessed for each patient by transcranial Doppler measurements, angiography, and (99m)Tc-ethylcysteinate dimer single-photon emission computed tomography (ECD-SPECT) imaging. Percentage of BA narrowing was calculated in reference to the baseline angiogram. RESULTS: BA narrowing >or=25% was found in 23 of 65 patients, and delayed brain stem (BS) hypoperfusion, as estimated by ECD-SPECT, was found in 16. Fourteen of 23 patients with BA narrowing >or=25% experienced BS hypoperfusion, whereas only 2 of 42 patients with >or=25% BA narrowing experienced BS ischemia (P<0.001). Stepwise logistic regression after adjusting for age with Hunt and Hess grade, Fisher grade, hydrocephalus, and aneurysmal location as covariables revealed BA narrowing >or=25% and delayed BS hypoperfusion to be significantly and independently associated with unfavorable 3-month outcome (P=0.0001; odds ratio, 10.1; 95% CI, 2.5 to 40.8; and P=0.007; odds ratio, 13.8, 95% CI, 2.18 to 91.9, respectively). CONCLUSIONS: These findings suggest for the first time that BA vasospasm after aSAH is an independent and significant prognostic factor associated with poor outcome in patients with severe cerebral vasospasm requiring endovascular therapy. Further study should be done to evaluate the role of interventional therapy on outcome in patients with posterior circulation vasospasm.

Adult↗
PubMed2006

Modelling the network of cell cycle transcription factors in the yeast Saccharomyces cerevisiae.

BACKGROUND: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing transcription factor binding data in conjunction with expression data. Of these approaches, several have focused on the reconstruction of the cell cycle regulatory network of Saccharomyces cerevisiae. The emphasis of these studies has been to model the relationships between transcription factors and their target genes. In contrast, here we focus on reverse-engineering the network of relationships among transcription factors that regulate the cell cycle in S. cerevisiae. RESULTS: We have developed a technique to reverse-engineer networks of the time-dependent activities of transcription factors that regulate the cell cycle in S. cerevisiae. The model utilizes linear regression to first estimate the activities of transcription factors from expression time series and genome-wide transcription factor binding data. We then use least squares to construct a model of the time evolution of the activities. We validate our approach in two ways: by demonstrating that it accurately models expression data and by demonstrating that our reconstructed model is similar to previously-published models of transcriptional regulation of the cell cycle. CONCLUSION: Our regression-based approach allows us to build a general model of transcriptional regulation of the yeast cell cycle that includes additional factors and couplings not reported in previously-published models. Our model could serve as a starting point for targeted experiments that test the predicted interactions. In the future, we plan to apply our technique to reverse-engineer other systems where both genome-wide time series expression data and transcription factor binding data are available.

Cell Cycle Proteins↗
PubMed2005

FDG-PET/CT imaging for preradiotherapy staging of head-and-neck squamous cell carcinoma.

PURPOSE: Image localization of head-and-neck squamous cell carcinoma lags behind current techniques to deliver a precise radiation dose with intensity-modulated radiotherapy. This pilot study prospectively examined the use of registered 18-F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/CT for preradiotherapy staging of the neck. METHODS AND MATERIALS: Sixty-three patients with squamous cell carcinoma of the oral cavity, oropharynx, larynx, or hypopharynx were enrolled into an institutional FDG-PET imaging protocol between September 2000 and June 2003. Of these patients, 20 went on to immediate neck dissection surgery and were studied further. Of these 20, 17 (85%) had American Joint Committee on Cancer Stage III or IV disease. All patients underwent preoperative FDG-PET and contrast-enhanced CT of the head and neck. FDG-PET/CT images were created using a nonrigid image registration algorithm developed at the University of Washington. Alternate primary and nodal gross tumor volumes were contoured with radiotherapy treatment planning software, blinded to each other and to the pathology results. One set of volumes was designed with CT guidance alone and the other with the corresponding FDG-PET/CT images. Neck dissection specimens were subdivided into surgical nodal levels intraoperatively, and the histopathologic findings were correlated with the CT and FDG-PET/CT nodal level findings. RESULTS: FDG-PET/CT detected 17 of 17 heminecks and 26 of 27 nodal zones histologically positive by dissection (100% and 96% sensitivity, respectively). The nodal level staging sensitivity and specificity for FDG-PET/CT was 96% (26 of 27) and 98.5% (68 of 69), respectively. FDG-PET/CT correctly detected nodal disease in 2 patients considered to have node-negative disease by CT alone. Agreement between the imaging results and pathology findings was stronger for FDG-PET/CT (kappa 0.95, 95% confidence interval 0.82-0.99) than for CT alone (kappa 0.81, 95% confidence interval 0.63-0.91; p = 0.06 by two-sided McNemar's testing). CONCLUSION: These early findings suggest that FDG-PET/CT is superior to CT alone for geographic localization of diseased neck node levels. Confirmatory trials to substantiate the accuracy of FDG-PET/CT neck staging should be prioritized.

Adult↗
PubMed2005

FDG-PET/CT-guided intensity modulated head and neck radiotherapy: a pilot investigation.

BACKGROUND: 2-deoxy-2[(18)F]fluoro-D-glucose-positron emission tomography (FDG-PET) imaging can be registered with CT images and can potentially improve neck staging sensitivity and specificity in patients with head and neck squamous cell cancer. The intent of this study was to examine the use of registered FDG-PET/CT imaging to guide head and neck intensity modulated radiotherapy (IMRT) planning. METHODS: Twenty patients with squamous cell carcinoma of the oral cavity, oropharynx, larynx, or hypopharynx underwent FDG-PET and contrast-enhanced CT imaging of the head and neck before neck dissection surgery. Combined FDG-PET/CT images were created by use of a nonrigid image registration algorithm. All IMRT plans were theoretical and were not used for treatment. We prescribed 66 Gy in 30 fractions to FDG-avid CT abnormalities and nodal zones directly involved with disease, without prophylactic coverage of uninvolved neck levels. Matched CT-guided IMRT plans designed according to the specifications of Radiation Therapy Oncology Group (RTOG) H-0022 were available for comparison. We investigated the feasibility of FDG-PET/CT-directed IMRT dose escalation in five patients with FDG-avid disease located away from critical normal structures. After 66 Gy, FDG-avid disease with 0.5-cm margins was boosted in 220 cGy increments until dose-limiting criteria were reached. RESULTS: Elimination of prophylactic coverage to FDG-PET/CT-negative neck levels markedly reduced mean dose (Dmean) to the contralateral parotid gland (p < .001) and Dmean to the laryngeal cartilage (p = .001). No FDG-PET/CT-directed plan missed pathologically verified nodal disease. During the dose escalation exercise, we successfully increased the dose to 95% of the planning target volume (PTV95%) to a mean of 7490 cGy (range, 7153-8098 cGy). CONCLUSIONS: We demonstrate early proof of the principle that FDG-PET/CT-guided IMRT planning can selectively target and intensify treatment of head and neck disease while reducing critical normal tissue doses. Routine clinical use of such planning should not be engaged until the accuracy of FDG-PET/CT is fully validated. Future directions, including refinement of treatment to gross disease and radiologically uninvolved neck nodal levels, are discussed.

Adult↗
PubMed2005

Characterization of genetically defined types of Charcot-Marie-Tooth neuropathies by using magnetic resonance neurography.

OBJECT: Charcot-Marie-Tooth (CMT) disease is a collection of related genetic disorders affecting peripheral nerves with an incidence of one in every 2500 individuals. A diagnosis of CMT disease has classically relied on a medical history, examination, and measurement of nerve conduction velocities. Advancements in genetic testing and magnetic resonance (MR) imaging techniques may provide clinicians with a more precise diagnostic armamentarium. The authors investigated MR neurography as a possible method to characterize CMT subtypes. METHODS: The authors performed MR neurography to evaluate sciatic nerves in the mid-thigh area of seven patients with genetically defined subtypes of CMT, one patient with chronic inflammatory demylinating polyneuropathy, and one patient without neuropathy. The authors correlate their findings with normal nerve conduction velocities (NCVs) and present their results as a descriptive case series. Although MR neurography could not be used to distinguish subtypes of CMT disease on nerve area or fascicle number, it appears to characterize phenotypic features and disease progression noninvasively in patients with some subtypes. CONCLUSIONS: In conjunction with NCV measurements, MR neurography may be useful in the diagnosis of CMT neuropathies and in monitoring disease progression.

Adult↗
PubMed2004

Protein interaction networks.

The study of protein interactions is playing an ever increasing role in our attempts to understand cells and diseases on a system-wide level. This article reviews several experimental approaches that are currently being used to measure protein-protein, protein-DNA and gene-gene interactions. These techniques have now been scaled up to produce extensive genome-wide data sets that are providing us with a first glimpse of global interaction networks. Complementing these experimental approaches, several computational methodologies to predict protein interactions are also reviewed. Existing databases that serve as repositories for protein interaction information and how such databases are used to analyze high-throughput data from a pathway perspective is also addressed. Finally, current efforts to combine multiple data types to obtain more accurate and comprehensive models of protein interactions are discussed. It is clear that the evolution of these experimental and computational approaches is rapidly changing our view of biology, and promises to provide us with an unprecedented ability to model cells and organisms at a system-wide level.

Animals↗
PubMed2003

Application of a neural network to improve nodal staging accuracy with 18F-FDG PET in non-small cell lung cancer.

UNLABELLED: We proposed to train a back-propagation artificial neural network (aNN) on a cohort of surgically proven non-small cell lung cancers (NSCLCs) and compare its accuracy with that of a trained (18)F-FDG PET reader. We plan to show that an aNN trained on (18)F-FDG PET- and CT-derived data is more accurate in predicting the true surgicopathologic nodal stage than a human reader. METHODS: One hundred thirty-three NSCLC patients with surgically proven N status treated at the University of Washington Medical Center or the Veterans Affairs Puget Sound Health Care System between February 1998 and September 2002 were used as inputs for the creation of an aNN. From CT of the thorax and (18)F-FDG PET (neck to pelvis) performed before surgery, we extracted the primary tumor size and uptake (maximum pixel SUV [maxSUV]), normal lung and mediastinal uptake, and nodal uptake (maxSUV). Using the same 133 cases, the same output (surgical N status, N(0) to N(3)), and the same software configuration settings, scenarios were created to assess which input parameters were most influential in creating an optimal aNN. To compute this optimal aNN, cases were split randomly 100 times into a training subset of 103 cases and a testing subset of 30 cases having the same proportion of N(0), N(1), N(2), and N(3) cases. N status predicted by the aNN was compared with the proven surgical N status to calculate the aNN accuracy. The N status readings from (18)F-FDG PET were also compared with the surgical N status for the same cases to determine (18)F-FDG PET accuracy. RESULTS: Statistical tests demonstrate that the best aNN accuracy is achieved by using N(1)-N(2)- N(3) nodal maxSUV divided by background uptake, the primary tumor size, and primary tumor maxSUV as inputs. The aNN correctly predicted the N stage in 87.3% of the testing cases compared with 73.5% for the (18)F-FDG PET expert reader. Accuracy of the aNN increased to 94.8% (PET, 89.4%) when comparing N(0) + N(1) with N(2) or N(3) status and to 94.9% (PET, 91.9%) when comparing N(0) + N(1) with N(2) + N(3) status. CONCLUSION: A back-propagation aNN can be trained to predict hilar and mediastinal nodal involvement with greater accuracy than an expert (18)F-FDG PET reader. Such a tool could be used to improve clinical interpretations and for clinical training.

Aged↗