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An algorithm to improve lateralization accuracy of inferior petrosal sinus sampling: procedural nuances for complex patterns of venous drainage. Patient series. JOURNAL OF NEUROSURGERY: CASE LESSONS 2021; 2:CASE21374. [PMID: 35854787 PMCID: PMC9265235 DOI: 10.3171/case21374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 07/19/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND
Inferior petrosal sinus sampling (IPSS) is a useful technique in the diagnosis of Cushing’s disease (CD) when the imaging finding is negative or equivocal. Different authors have reported considerable variability in the ability to determine tumor laterality with IPSS. Here the authors present a retrospective case series of 7 patients who underwent IPSS using a systematic algorithm to improve lateralization accuracy by identifying optimal sampling sites on the basis of individual cavernous sinus drainage patterns in each patient.
OBSERVATIONS
Of the 7 patients identified, 6 were determined to have CD and subsequently underwent surgery. IPSS was accurate in all patients from whom laterality was predicted. Arterial and venous angiography were used to define cavernous sinus drainage patterns and determine optimal sampling sites. All patients who underwent surgery achieved hormonal cure.
LESSONS
All IPSS predictions of lateralization were correct when available, and all patients who underwent surgery achieved hormonal cure. Advances in angiographic techniques for identification of the site of primary drainage from the cavernous sinus and subsequent optimization of microcatheter placement may improve the ability to predict tumor laterality.
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Isopycnic analysis of intact cells - IV: Comparison of anaerobic shift-down with autonomous phage shut-down in Escherichia coli. Biochem Biophys Res Commun 1981; 100:1209-13. [PMID: 7023478 DOI: 10.1016/0006-291x(81)91952-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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