Evidence map›Paper›PMID 31181459›Full record

ArticleHearing research2019

Cochlear pharmacokinetics - Micro-computed tomography and learning-prediction modeling for transport parameter determination.

Sanketh S Moudgalya, Kevin Wilson, Xiaoxia Zhu, Mikalai M Budzevich, Joseph P Walton, Nathan D Cahill, Robert D Frisina, David A Borkholder

Open access · hybridAbstract read
In one paragraph

Article in Hearing research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Microtechnologies for inner ear drug delivery.Current opinion in otolaryngology & head and neck surgery · 2020
    Review
  4. Deep Volumetric Segmentation of Murine Cochlear Compartments from Micro-Computed Tomography Images.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Sanketh S MoudgalyaChester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA.
Kevin WilsonDepartment of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA.
Xiaoxia ZhuDepartment of Medical Engineering, University of Southern Florida, Tampa, FL, USA; Global Center for Hearing and Speech Research, University of Southern Florida, Tampa, FL, USA.
Mikalai M BudzevichH. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Joseph P WaltonDepartment of Medical Engineering, University of Southern Florida, Tampa, FL, USA; Global Center for Hearing and Speech Research, University of Southern Florida, Tampa, FL, USA; Department of Communication Sciences and Disorders, University of Southern Florida, Tampa, FL, USA.
Nathan D CahillChester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA; School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA.
Robert D FrisinaDepartment of Medical Engineering, University of Southern Florida, Tampa, FL, USA; Global Center for Hearing and Speech Research, University of Southern Florida, Tampa, FL, USA.
David A BorkholderDepartment of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA; Microsystems Engineering, Rochester Institute of Technology, Rochester, NY, USA. Electronic address: david.borkholder@rit.edu.
Rochester Institute of Technology · USUniversity of South Florida · USMoffitt Cancer Center · US

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI Christine O'Connell · 1998 to 2026
$93.5M
Enabling Microsystem Technologies for Advanced Drug DeliveryR01DC014568 · NIDCD · ROCHESTER INSTITUTE OF TECHNOLOGY · PI BORKHOLDER, DAVID A, FRISINA, ROBERT D · 2015 to 2019
$2.7M
NCI NIH HHS P30 CA076292NIDCD NIH HHS R01 DC014568
6 · The paper itself

Abstract

Inner ear disorders such as sensorineural deafness and genetic diseases may one day be treated with local drug delivery to the inner ear. Current pharmacokinetic models have been based on invasive methods to measure drug concentrations, limiting them in spatial resolution, and restricting the research to larger rodents. We developed an intracochlear pharmacokinetic model based on an imaging, learning-prediction (LP) paradigm for learning transport parameters in the murine cochlea. This was achieved using noninvasive micro-computed tomography imaging of the cochlea during in vivo infusion of a contrast agent at the basal end of scala tympani through a cochleostomy. Each scan was registered in 3-D to a cochlear atlas to segment the cochlear regions with high accuracy, enabling concentrations to be extracted along the length of each scala. These spatio-temporal concentration profiles were used to learn a concentration dependent diffusion coefficient, and transport parameters between the major scalae and to clearance. The LP model results are comparable to the current state of the art model, and can simulate concentrations for cases involving different infusion molecules and different drug delivery protocols. Forward simulation results with pulsatile delivery suggest the pharmacokinetic model can be used to optimize drug delivery protocols to reduce total drug delivered and the potential for toxic side effects. While developed in the challenging murine cochlea, the processes are scalable to larger animals and different drug infusion paradigms.

Indexed as

Models, BiologicalX-Ray MicrotomographyAnimalsCochleaComputer SimulationContrast MediaDiffusionInfusions, ParenteralIopamidolMice, Inbred CBATissue DistributionContrast MediaIopamidol3-D image registrationCochleaContrast agentInner earMicro-computed tomographyMouseOptimizationPharmacokineticsSegmentation

Identifiers

PMID31181459
PMCPMC6669082
OpenAlexW2947460044

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.