Browsing by Subject "Dynamic imaging"

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    Atlanto-axial rotary instability (Fielding type 1): characteristic clinical and radiological findings, and treatment outcomes following alignment, fusion, and stabilization
    (Springer, 2021) Henderson, Fraser C.; Rosenbaum, Robert; Narayanan, Malini; Koby, Myles; Tuchman, Kelly; Rowe, Peter C.; Francomano, Clair; Medical and Molecular Genetics, School of Medicine
    Atlanto-axial instability (AAI) is common in the connective tissue disorders, such as rheumatoid arthritis, and increasingly recognized in the heritable disorders of Stickler, Loeys-Dietz, Marfan, Morquio, and Ehlers-Danlos (EDS) syndromes, where it typically presents as a rotary subluxation due to incompetence of the alar ligament. This retrospective, IRB-approved study examines 20 subjects with Fielding type 1 rotary subluxation, characterized by anterior subluxation of the facet on one side, with a normal atlanto-dental interval. Subjects diagnosed with a heritable connective tissue disorder, and AAI had failed non-operative treatment and presented with severe headache, neck pain, and characteristic neurological findings. Subjects underwent a modified Goel-Harms posterior C1-C2 screw fixation and fusion without complication. At 15 months, two subjects underwent reoperation following a fall (one) and occipito-atlantal instability (one). Patients reported improvement in the frequency or severity of neck pain (P < 0.001), numbness in the hands and lower extremities (P = 0.001), headaches, pre-syncope, and lightheadedness (all P < 0.01), vertigo and arm weakness (both P = 0.01), and syncope, nausea, joint pain, and exercise tolerance (all P < 0.05). The diagnosis of Fielding type 1 AAI requires directed investigation with dynamic imaging. Alignment and stabilization is associated with improvement of pain, syncopal and near-syncopal episodes, sensorimotor function, and exercise tolerance.
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    Comparison of tracer kinetic models for 68Ga-PSMA-11 PET in intermediate-risk primary prostate cancer patients
    (Springer, 2024-01-10) Smith, Nathaniel J.; Green, Mark A.; Bahler, Clinton D.; Tann, Mark; Territo, Wendy; Smith, Anne M.; Hutchins, Gary D.; Radiology and Imaging Sciences, School of Medicine
    Background: 68Ga-PSMA-11 positron emission tomography enables the detection of primary, recurrent, and metastatic prostate cancer. Regional radiopharmaceutical uptake is generally evaluated in static images and quantified as standard uptake values (SUVs) for clinical decision-making. However, analysis of dynamic images characterizing both tracer uptake and pharmacokinetics may offer added insights into the underlying tissue pathophysiology. This study was undertaken to evaluate the suitability of various kinetic models for 68Ga-PSMA-11 PET analysis. Twenty-three lesions in 18 patients were included in a retrospective kinetic evaluation of 55-min dynamic 68Ga-PSMA-11 pre-prostatectomy PET scans from patients with biopsy-demonstrated intermediate- to high-risk prostate cancer. Three kinetic models-a reversible one-tissue compartment model, an irreversible two-tissue compartment model, and a reversible two-tissue compartment model, were evaluated for their goodness of fit to lesion and normal reference prostate time-activity curves. Kinetic parameters obtained through graphical analysis and tracer kinetic modeling techniques were compared for reference prostate tissue and lesion regions of interest. Results: Supported by goodness of fit and information loss criteria, the irreversible two-tissue compartment model optimally fit the time-activity curves. Lesions exhibited significant differences in kinetic rate constants (K1, k2, k3, Ki) and semiquantitative measures (SUV and %ID/kg) when compared with reference prostatic tissue. The two-tissue irreversible tracer kinetic model was consistently appropriate across prostatic zones. Conclusions: An irreversible tracer kinetic model is appropriate for dynamic analysis of 68Ga-PSMA-11 PET images. Kinetic parameters estimated by Patlak graphical analysis or full compartmental analysis can distinguish tumor from normal prostate tissue.