Main Page/SlicerCommunity/2018 - Revision history

Marianna at 20:31, 12 February 2020

2020-02-12T20:31:07Z

Marianna: /* Association of Anemia and Hemoglobin Decrease during Acute Stroke Treatment with Infarct Growth and Clinical Outcome */

2020-02-12T15:35:58Z

Association of Anemia and Hemoglobin Decrease during Acute Stroke Treatment with Infarct Growth and Clinical Outcome

Marianna: /* Non-invasive Magnetic Resonance Imaging of Oils in Botryococcus Braunii Green Algae: Chemical Shift Selective and Diffusion-weighted Imaging */

2020-02-12T15:29:17Z

Non-invasive Magnetic Resonance Imaging of Oils in Botryococcus Braunii Green Algae: Chemical Shift Selective and Diffusion-weighted Imaging

Marianna at 20:11, 11 February 2020

2020-02-11T20:11:42Z

Marianna at 19:37, 11 February 2020

2020-02-11T19:37:13Z

Show changes

Marianna: /* Gray Matter Atrophy in Multiple Sclerosis Despite Clinical and Lesion Stability During Natalizumab Treatment */

2020-02-11T18:57:12Z

Gray Matter Atrophy in Multiple Sclerosis Despite Clinical and Lesion Stability During Natalizumab Treatment

Marianna: /* Mammographic Breast Density Assessed with Fully Automated Method and its Risk for Breast Cancer */

2020-02-11T18:23:48Z

Mammographic Breast Density Assessed with Fully Automated Method and its Risk for Breast Cancer

Marianna: /* Variations in the Size and Shape of Human Cochlear Malformation Types */

2020-02-11T18:20:39Z

Variations in the Size and Shape of Human Cochlear Malformation Types

Marianna: /* A Wearable Mixed-reality Holographic Computer for Guiding External Ventricular Drain Insertion at the Bedside */

2020-02-11T16:37:30Z

A Wearable Mixed-reality Holographic Computer for Guiding External Ventricular Drain Insertion at the Bedside

Marianna: /* Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer */

2020-02-10T14:56:36Z

Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer

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-==Accuracy Assessment Of 3D-Printed Tooth Replicas==
+==Accuracy Assessment of 3D-Printed Tooth Replicas==
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-==Computed Tomography Trachea Volumetry in Patients with Scleroderma: Association With Clinical and Functional Findings==
+==Computed Tomography Trachea Volumetry in Patients With Scleroderma: Association With Clinical and Functional Findings==
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-==Automatic Segmentation of Stereoelectroencephalography (Seeg) Electrodes Post-Implantation Considering Bending==
+==Automatic Segmentation of Stereoelectroencephalography (SEEG) Electrodes Post-Implantation Considering Bending==
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 Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.
 "We used UKF tractography implemented in the [http://www.slicer.org '''3D Slicer'''] to perform whole-brain tractography"
 |}

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 | align="right" |[[image:Owens-fig3.jpg|thumb|300px| '''User inputs for initializing semi-automatic segmentation tools''' <br>
 (A) LSTK requires the user to select a seed within the tumor (red) to initiate the segmentation algorithm. Defining the maximum tumor radius generates a 3D bounding box (green) centered about the seed, within which the segmentation result will be confined. (B) GrowCut requires the user to label foreground (blue) and background (yellow) pixels to initiate the segmentation algorithm. Once labels were established, the GrowCut algorithm was followed by manual editing of the GrowCut-generated contours. Note that only the transverse view is shown here. Observers also labeled foreground and background pixels in the coronal and sagittal planes for each tumor case.]]
 |}

← Older revision		Revision as of 20:11, 11 February 2020
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	\| align="right" \|[[image:vonJonquieres-ActaNeuropathol2018-fig1.jpg\|thumb\|300px\| Pathological consequences of manipulation of NAA metabolism. a qRT-PCR analysis of Aspa and Nat8l mRNA expression in CNS tissue from DKO and the parental single gene mutants (n = 3; expression relative to Hprt). Segmentation of images was performed in '''[https://www.slicer.org/ 3D Slicer]''' outlining brain surface (yellow) and ventricles (blue). ]]		\| align="right" \|[[image:vonJonquieres-ActaNeuropathol2018-fig1.jpg\|thumb\|300px\| Pathological consequences of manipulation of NAA metabolism. a qRT-PCR analysis of Aspa and Nat8l mRNA expression in CNS tissue from DKO and the parental single gene mutants (n = 3; expression relative to Hprt). Segmentation of images was performed in '''[https://www.slicer.org/ 3D Slicer]''' outlining brain surface (yellow) and ventricles (blue). ]]
	\|}		\|}
		+
		+
		+	----
		+	Go to <big>[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2019 2019] ::
		+	[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2018 2018] ::
		+	[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2017 2017] ::
		+	[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2016 2016] ::
		+	[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2015 2015] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2011-2014 2014-2011]:: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2005-2010 2010-2005]</big>
		+	----

← Older revision		Revision as of 18:57, 11 February 2020
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	\| align="right" \|[[image:Ha-fig1.jpg\|thumb\|300px\| '''a–c:''' Representative images after pre-processing of metastatic lymph nodes.]]]		\| align="right" \|[[image:Ha-fig1.jpg\|thumb\|300px\| '''a–c:''' Representative images after pre-processing of metastatic lymph nodes.]]]

−	\|}
−
−	~~==Gray Matter Atrophy in Multiple Sclerosis Despite Clinical and Lesion Stability During Natalizumab Treatment==~~
−
−	~~{\| width="100%"~~
−	\|
−	~~'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/30576361 PLoS One. 2018 Dec 21;13(12):e0209326. PMID: 30576361] \| [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303064/pdf/pone.0209326.pdf PDF]~~
−
−	~~'''Authors:''' Koskimäki F, Bernard J, Yong J, Arndt N, Carroll T, Lee SK, Reder AT, Javed A.~~
−
−	~~'''Institution:''' Division of Clinical Neurosciences, Turku University Hospital and University of Turku, Turku, Finland.~~
−
−	~~'''Abstract:''' BACKGROUND:~~
−	Brain volume loss is an important surrogate marker for assessing disability in MS; however, contribution of gray and white matter to the whole brain volume loss needs further examination in the context of specific MS treatment.
−
−	~~OBJECTIVES:~~
−	~~To examine whole and segmented gray, white, thalamic, and corpus callosum volume loss in stable patients receiving natalizumab for 2-5 years.~~
−
−	~~METHODS:~~
−	This was a retrospective study of 20 patients undergoing treatment with natalizumab for 24-68 months. Whole brain volume loss was determined with SIENA. Gray and white matter segmentation was done using FAST. Thalamic and corpus callosum volumes were determined using Freesurfer. T1 relaxation values of chronic hypointense lesions (black holes) were determined using a quantitative, in-house developed method to assess lesion evolution.
−
−	~~RESULTS:~~
−	Over a mean of 36.6 months, median percent brain volume change (PBVC) was -2.0% (IQR 0.99-2.99). There was decline in gray (p = 0.001) but not white matter (p = 0.6), and thalamic (p = 0.01) but not corpus callosum volume (p = 0.09). Gray matter loss correlated with PBVC (Spearman's r = 0.64, p = 0.003) but not white matter (Spearman's r = 0.42, p = 0.07). Age significantly influenced whole brain volume loss (p = 0.010, multivariate regression), but disease duration and baseline T2 lesion volume did not. There was no change in T1 relaxation values of lesions or T2 lesion volume over time. All patients remained clinically stable.
−
−	~~CONCLUSIONS:~~
−	~~These results demonstrate that brain volume loss in MS is primarily driven by gray matter changes and may be independent of clinically effective treatment.~~
−
−	~~"FLAIR images were used to determine T2 lesion volume using [http://www.slicer.org '''3D Slicer''']."~~
−
−	~~'''Funding:'''~~
−
−	*Turku University Hospital, Division of Clinical Neurosciences, Finland.
	\|}		\|}

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 The dataset consists of a (a) T1-weighted image with labels as overlay; (b) postcontrast T1-weighted
 image; (c) T2-weighted image; and (d) Fluid Attenuated Inversion Recovery (FL) image]]]
 |}

← Older revision		Revision as of 18:20, 11 February 2020
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	\| align="right" \|[[image:Saikaran-fig1.jpg\|thumb\|300px\| Left craniocaudal mammogram of a 41-year-old woman with a negative screening exam (b) example of density segmentation using '''[http://slicer.org 3D Slicer]''' software tool showing automatic identification of mammographic density.]]		\| align="right" \|[[image:Saikaran-fig1.jpg\|thumb\|300px\| Left craniocaudal mammogram of a 41-year-old woman with a negative screening exam (b) example of density segmentation using '''[http://slicer.org 3D Slicer]''' software tool showing automatic identification of mammographic density.]]
−
−	\|}
−
−	~~==Variations in the Size and Shape of Human Cochlear Malformation Types==~~
−
−	~~{\| width="100%"~~
−	\|
−	'''Publication:''' [https://www.ncbi.nlm.nih.gov/pubmed/30980504 Anat Rec (Hoboken). 2019 Oct;302(10):1792-9. PMID: 30980504] \| [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767414/pdf/AR-302-1792.pdf PDF]
−
−
−	~~'''Authors:''' Dhanasingh A.~~
−
−	~~'''Institution:''' MED-EL GmbH, Innsbruck, Austria.~~
−
−	'''Abstract:''' The objective of this study is to determine the variations in size and shape of the most widely recognized cochlear malformation types using three-dimensional (3D) visualization. Using '''[http://slicer.org 3D Slicer]''' freeware, the complete inner-ear structures were segmented from 46 anonymized high-resolution computed tomography (HRCT) image datasets. Cochlear height, internal auditory canal height, and width were measured from the axial plane. Cochlear basal turn diameter was measured from the oblique coronal plane. Number of cochlear turns was measured from the 3D images and the corresponding cochlear duct length (CDL) was estimated using the CDL equations given in Alexiades et al. [Otol Neurotol 36 (2015) 904-907]. Out of 46 preoperative HRCT image datasets of human temporal bone, cochlear anatomy types including normal anatomy (4), enlarged vestibular aqueduct syndrome (3), cochlear aplasia (2), incomplete partition Types I (8), II (Mondini's deformity) (3), and III (X-linked) (4), cochlear hypoplasia (CH) (17), and common cavity (CC) (5) were identified. Majority of CH cases had cochlear height shorter than 4 mm whereas the CC cases measured cochlear height above 6 mm. For all the other malformation types, cochlear height was between 4 and 6 mm. In terms of "A" value, majority of CH cases showed shorter "A" value of <7.5 mm, which is in the lower end in comparison to the rest of the malformation types reported in this study. 3D-visualization shows the size and shape variations of all the structures of inner ear and also improves the clinicians' ability to visualize cochlear anatomy and nearby structures much easier than from the 2D image slices.
−
−	\| align="right" \|[[image:Dhanasing-fig001.jpg\|thumb\|300px\| Segmentation of the inner ear from every image slice available in the image dataset. Summing up all the segmented images transforms into a 3D model.]]]

	\|}		\|}

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+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/30485188 J Neurosurg. 2018 Oct 1:1-8. PMID: 30485188]| [https://thejns.org/downloadpdf/journals/j-neurosurg/aop/article-10.3171-2018.4.JNS18124.xml PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/30485188 J Neurosurg. 2018 Oct 1:1-8. PMID: 30485188]   | [https://thejns.org/downloadpdf/journals/j-neurosurg/aop/article-10.3171-2018.4.JNS18124.xml PDF]
 '''Authors:''' Li Y, Chen X, Wang N, Zhang W, Li D, Zhang L, Qu X, Cheng W, Xu Y, Chen W, Yang Q.

@@ Line 1,535: / Line 1,535: @@
 {| width="100%"
+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/29167070 Acad Radiol. 2018 Mar;25(3):349-58. PMID: 29167070]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/29167070 Acad Radiol. 2018 Mar;25(3):349-58. PMID: 29167070] | [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535050/pdf/nihms-1029787.pdf PDF]
 '''Authors:''' Chatterjee A, He D, Fan X, Wang S, Szasz T, Yousuf A, Pineda F, Antic T, Mathew M, Karczmar GS, Oto A.