1
|
Ratnanather JT. Structural neuroimaging of the altered brain stemming from pediatric and adolescent hearing loss-Scientific and clinical challenges. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2019; 12:e1469. [PMID: 31802640 DOI: 10.1002/wsbm.1469] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 10/01/2019] [Accepted: 10/13/2019] [Indexed: 12/20/2022]
Abstract
There has been a spurt in structural neuroimaging studies of the effect of hearing loss on the brain. Specifically, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) technologies provide an opportunity to quantify changes in gray and white matter structures at the macroscopic scale. To date, there have been 32 MRI and 23 DTI studies that have analyzed structural differences accruing from pre- or peri-lingual pediatric hearing loss with congenital or early onset etiology and postlingual hearing loss in pre-to-late adolescence. Additionally, there have been 15 prospective clinical structural neuroimaging studies of children and adolescents being evaluated for cochlear implants. The results of the 70 studies are summarized in two figures and three tables. Plastic changes in the brain are seen to be multifocal rather than diffuse, that is, differences are consistent across regions implicated in the hearing, speech and language networks regardless of modes of communication and amplification. Structures in that play an important role in cognition are affected to a lesser extent. A limitation of these studies is the emphasis on volumetric measures and on homogeneous groups of subjects with hearing loss. It is suggested that additional measures of morphometry and connectivity could contribute to a greater understanding of the effect of hearing loss on the brain. Then an interpretation of the observed macroscopic structural differences is given. This is followed by discussion of how structural imaging can be combined with functional imaging to provide biomarkers for longitudinal tracking of amplification. This article is categorized under: Developmental Biology > Developmental Processes in Health and Disease Translational, Genomic, and Systems Medicine > Translational Medicine Laboratory Methods and Technologies > Imaging.
Collapse
Affiliation(s)
- J Tilak Ratnanather
- Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland.,Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| |
Collapse
|
2
|
Ceyhan E, Nishino T, Botteron KN, Miller MI, Ratnanather JT. Analysis of cortical morphometric variability using labeled cortical distance maps. STATISTICS AND ITS INTERFACE 2016; 10:313-341. [PMID: 37476472 PMCID: PMC10358742 DOI: 10.4310/sii.2017.v10.n2.a13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
Morphometric (i.e., shape and size) differences in the anatomy of cortical structures are associated with neurodevelopmental and neuropsychiatric disorders. Such differences can be quantized and detected by a powerful tool called Labeled Cortical Distance Map (LCDM). The LCDM method provides distances of labeled gray matter (GM) voxels from the GM/white matter (WM) surface for specific cortical structures (or tissues). Here we describe a method to analyze morphometric variability in the particular tissue using LCDM distances. To extract more of the information provided by LCDM distances, we perform pooling and censoring of LCDM distances. In particular, we employ Brown-Forsythe (BF) test of homogeneity of variance (HOV) on the LCDM distances. HOV analysis of pooled distances provides an overall analysis of morphometric variability of the LCDMs due to the disease in question, while the HOV analysis of censored distances suggests the location(s) of significant variation in these differences (i.e., at which distance from the GM/WM surface the morphometric variability starts to be significant). We also check for the influence of assumption violations on the HOV analysis of LCDM distances. In particular, we demonstrate that BF HOV test is robust to assumption violations such as the non-normality and within sample dependence of the residuals from the median for pooled and censored distances and are robust to data aggregation which occurs in analysis of censored distances. We recommend HOV analysis as a complementary tool to the analysis of distribution/location differences. We also apply the methodology on simulated normal and exponential data sets and assess the performance of the methods when more of the underlying assumptions are satisfied. We illustrate the methodology on a real data example, namely, LCDM distances of GM voxels in ventral medial prefrontal cortices (VMPFCs) to see the effects of depression or being of high risk to depression on the morphometry of VMPFCs. The methodology used here is also valid for morphometric analysis of other cortical structures.
Collapse
Affiliation(s)
- E. Ceyhan
- Dept. of Mathematics, Koç University, 34450, Sarıyer, Istanbul, Turkey
| | - T. Nishino
- Dept. of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - K. N. Botteron
- Dept. of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Dept. of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - M. I. Miller
- Center for Imaging Science, The Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD 21218, USA
- Dept. of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
| | - J. T. Ratnanather
- Center for Imaging Science, The Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD 21218, USA
- Dept. of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
| |
Collapse
|
3
|
Ratnanather JT, Cebron S, Ceyhan E, Postell E, Pisano DV, Poynton CB, Crocker B, Honeycutt NA, Mahon PB, Barta PE. Morphometric differences in planum temporale in schizophrenia and bipolar disorder revealed by statistical analysis of labeled cortical depth maps. Front Psychiatry 2014; 5:94. [PMID: 25132825 PMCID: PMC4117114 DOI: 10.3389/fpsyt.2014.00094] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 07/16/2014] [Indexed: 12/25/2022] Open
Abstract
Differences in cortical thickness in the lateral temporal lobe, including the planum temporale (PT), have been reported in MRI studies of schizophrenia (SCZ) and bipolar disorder (BPD) patients. Most of these studies have used a single-valued global or local measure for thickness. However, additional and complementary information can be obtained by generating labeled cortical distance maps (LCDMs), which are distances of labeled gray matter (GM) voxels from the nearest point on the GM/white matter (WM) (inner) cortical surface. Statistical analyses of pooled and censored LCDM distances reveal subtle differences in PT between SCZ and BPD groups from data generated by Ratnanather et al. (Schizophrenia Research, http://dx.doi.org/10.1016/j.schres.2013.08.014). These results confirm that the left planum temporale (LPT) is more sensitive than the right PT in distinguishing between SCZ, BPD, and healthy controls. Also confirmed is a strong gender effect, with a thicker PT seen in males than in females. The differences between groups at smaller distances in the LPT revealed by pooled and censored LCDM analysis suggest that SCZ and BPD have different effects on the cortical mantle close to the GM/WM surface. This is consistent with reported subtle changes in the cortical mantle observed in post-mortem studies.
Collapse
Affiliation(s)
- J Tilak Ratnanather
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA ; Institute for Computational Medicine, Johns Hopkins University , Baltimore, MD , USA ; Department of Biomedical Engineering, Johns Hopkins University , Baltimore, MD , USA
| | - Shannon Cebron
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA
| | - Elvan Ceyhan
- Department of Mathematics, Koç University , Istanbul , Turkey
| | - Elizabeth Postell
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA
| | - Dominic V Pisano
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA
| | - Clare B Poynton
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA
| | - Britni Crocker
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA
| | - Nancy A Honeycutt
- Department of Psychiatry, Johns Hopkins University School of Medicine , Baltimore, MD , USA
| | - Pamela B Mahon
- Department of Psychiatry, Johns Hopkins University School of Medicine , Baltimore, MD , USA
| | - Patrick E Barta
- Center for Imaging Science, Johns Hopkins University , Baltimore, MD , USA ; Institute for Computational Medicine, Johns Hopkins University , Baltimore, MD , USA
| |
Collapse
|