21 research outputs found

    Adrenal vein sampling for ACTH-producing pheochromocytomas

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    Adrenocorticotropic hormone (ACTH)-producing pheochromocytoma can cause a variety of clinical manifestations of excess catecholamine and corticosteroid. Anatomic localization of this source of ectopic ACTH is critical to facilitate unilateral adrenalectomy and prevent adrenal insufficiency due to bilateral adrenalectomy. Although nuclear scintigraphy remains the diagnostic gold standard, recent radiotracer supply shortages have necessitated alternative diagnostic paradigms to localize adrenal pheochromocytomas. We present a case where adrenal vein sampling (AVS) was utilized to lateralize an adrenal pheochromocytoma and discuss the approach and nuance as it differs from routine AVS for hyperaldosteronism or hypercortisolism

    A report of 2 cases of the use of the Inari FlowTriever System in the treatment of pulmonary embolism

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    The FlowTriever System (Inari Medical, Irvine, California) is the first FDA-approved mechanical thrombectomy device used for treatment of pulmonary embolism. This device enables nonsurgical removal of pulmonary blood clots without the use of thrombolytic medication and its associated risks. We report 2 cases of successful application of the Inari FlowTriever in treatment of pulmonary embolism and right atrial thrombus

    Applications of artificial intelligence to prostate multiparametric MRI (mpMRI): Current and emerging trends

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    Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists\u27 accuracy and speed

    Further Evidence of Emotional Allodynia in Unmedicated Young Adults with Major Depressive Disorder

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    <div><p>Background</p><p>Recent evidence suggests that sensitivity to the emotional sequela of experimental thermal pain(measured by emotional unpleasantness) is heightened in individuals with major depressive disorder(MDD), a phenomenon we termed “emotional allodynia”. The aim of this study was to examine whether acute happy and sad mood induction alters emotional allodynia in MDD. We hypothesized that emotional allodynia will be a robust characteristic of individuals with MDD compared to healthy controls. Thus, it would remain following acute mood induction, independent of valence.</p><p>Methods</p><p>Twenty-one subjects with current MDD and 21 well-matched healthy subjects(HC) received graded brief temperature stimuli following happy and sad mood inductions procedures(MIP). All subjects rated the intensity and affect(pleasantness/unpleasantness) of each stimulus. Sensory(pain intensity) and affective(pain unpleasantness) thresholds were determined by methods of constant stimuli.</p><p>Results</p><p>The MIPs reliably induced happy and sad mood and the resulting induced mood and subjective arousal were not different between the groups at the time of temperature stimulation. Compared to HC, MDD individuals demonstrated emotional allodynia. We found significantly decreased affective pain thresholds whereby significantly lower temperatures became unpleasant in the MDD compared to the HC group. This was not observed for the sensory pain thresholds. Within the MDD, the affective pain thresholds were significantly lower than the corresponding pain intensity thresholds, whereby non-painful temperatures were already unpleasant for the MDD irrespective of the induced mood. This was not observed for the HC groups where the affective and pain intensity thresholds were comparable.</p><p>Conclusions</p><p>These findings suggest that emotional allodynia may be a chronic characteristic of current MDD. Future studies should determine if emotional allodynia persists after psychological or pharmacological interventions. Finally, longitudinal work should examine whether emotional allodynia is a result of or vulnerability for depression and the role it plays in the increased susceptibility for pain complaints in this disorder.</p></div

    Experimental Design.

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    <p>Upon arrival subjects rated their mood and arousal (Rating 1). Subjects were then seated quietly in front of the laptop computer while listening to 7 min of previously chosen and individualized for each participant sad/happy music (see Appendix) and reading and re-experiencing the autobiographical event displayed on the computer screen. Mood and arousal ratings were taken immediately after (Rating 2a). This was followed by a series of brief temperature stimuli of six different intensities (T1–T6: 36, 38, 40, 42, 44, 46°C) delivered every 60 sec in random and counterbalanced order to subjects’ left forearm. After 12 temperature stimulations, mood induction was repeated with the new sad/happy music and autobiographical script, after which subjects again rated their mood and arousal (Rating 2b). A total of 24 temperature stimuli were delivered for a total duration of ∼40 min. After mood neutralization for ∼35 min (see Methods) subjects are asked to rate their mood and arousal (Rating 3). The procedure is repeated with the opposite valence.</p

    Pain Intensity and Affective Thresholds.

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    <p><b>a)</b> Highly significant group effect on the affective thresholds was observed following happy and sad mood inductions whereby significantly lower affective thresholds were found in the MDD compared to the HC group (F(1,39) = 7.473, p<0.01); <b>b</b>) No significant group effect was observed for the intensity thresholds following mood induction (F(1,39) = 0.33, p>0.05).</p

    Demographic, Clinical and Psychological Variables.

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    <p>MDD/(E) – Major Depressive Disorder/(Episode); HC – Healthy Control; BDI – Beck Depression Inventory 2;</p

    Mood Ratings.

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    <p>Subjects rated their mood prior to mood induction (M1), immediately after mood induction (M2) when temperature stimulations were applied and at the end of sad/happy experimental blocks (M3) (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080507#pone-0080507-g001" target="_blank"><b>Figure 1</b></a> and text for more details). Significant within-subjects effects of mood induction on subjects’ rating of mood in both manipulations (happy: F(2,38) = 6.113, p<0.01; sad: F(2,38) = 12.306, p<0.001) with mood ratings being significantly lower during sad than happy MIP. (<b>A</b>) <b>Happy MIP</b>: MDD subjects showed significantly lower M1 (F(1,39) = 5.199, p<0.05) and M3 ratings (F(1,39) = 13.970, p<0.01) but not M2 rating (F(1,39) = 0.894, p>0.05); (<b>B</b>) <b>Sad MIP:</b> MDD subjects showed significantly lower M1 (F(1,39) = 11.584, p<0.01) and M3 (F(1,39) = 11.133, p<0.01) rating but not M2 rating (F(1,39) = 3.720, p>0.05).</p

    Arousal Ratings.

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    <p>Subjects rated their arousal prior to the mood induction (A1), immediately after mood induction (A2) when temperature stimulations were applied and at the end of sad/happy experimental blocks (A3) (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080507#pone-0080507-g001" target="_blank"><b>Figure 1</b></a> and text for more details). ) <b>(a)</b><b>Happy MIP</b>: MDD compared to controls had higher A1 rating (F(1,39) = 9.242, p<0.01) but not A2 (F(1,39) = 2.263, p>0.05) or A3 (F(1,39) = 1.981, p>0.05) rating. <b>(b)</b><b>Sad MIP:</b> MDD compared to control group did not differ in their A1 (F(1,39) = 2.321, p>0.05) or A2 (F(1,39) = 0.972, p>0.05) rating and had higher A3 rating (F(1,39) = 6.735, p<0.05).</p
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