OSCR

Long-term effects of preterm birth on cortical folding trajectories in early childhood.

A correction to this paper has been published: the notice, 42614990, from Europe PMC.

Code ↔ Paper

3 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 3 matches
  1. [1] § Materials and methods › Structural data processing ↔ wrapper/PARSE_ARGS.h, lines 36 to 89 · score 0.69 · icosahedron subdivision, surface registration, cortical surface, spherical, resampled, weighted · Report a mismatch
  2. [2] § Materials and methods › Morphological feature extraction ↔ src/Gyrification.h, lines 18 to 94 · score 0.62 · hull surface, tensor, propagation, smoothing, speed, outer · Report a mismatch
  3. [3] § Materials and methods › Morphological feature extraction ↔ wrapper/PARSE_ARGS.h, lines 23 to 65 · score 0.57 · cerebral hull, speed, outer, kernel, cortex, propagation · Report a mismatch

Paper

Loaded from Europe PMC by your browser; OSCR does not store it: doi.org · Europe PMC

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The authors' code

C/C++ header · 91 lines · 5.9 KB · MIT · 1 match

  1. #include <cstring>
  2. #include <vector>
  3. #include "CLI11.hpp"
  5. std::string dirProperty;
  6. std::string dirSphere;
  7. std::string dirOutput;
  8. std::string dirLandmark;
  9. std::string dirCoeff;
  10. std::string dirSurf;
  11. std::vector<std::string> listProperty;
  12. std::vector<std::string> listSphere;
  13. std::vector<std::string> listOutputCoeff;
  14. std::vector<std::string> listOutput;
  15. std::vector<std::string> listLandmark;
  16. std::vector<std::string> listCoeff;
  17. std::vector<std::string> listSurf;
  18. float weightMap = 1;
  19. std::vector<float> listWeight;
  20. float idprior = 625;
  21. int degree = 15;
  22. int maxIter = 20;
  23. int icosa = 7;
  24. float weightLoc = 0;
  25. std::vector<std::string> listFilter;
  26. std::string tmpVariance;
  27. std::string icoMesh;
  28. bool realtimeCoeff = false;
  29. bool noguess = false;
  30. bool resampling = false;
  31. int nThreads = 0;
  32. int guessRes = 3;
  33. std::vector<int> listFixedSubj;
  34. int nCThreads = 0;
  36. void PARSE_ARGS(int argc, char **argv)
  37. {
  38. std::string desc("Hierarchical Spherical Deformation for Cortical Surface Registration "
  39. HSD_VERSION "\n"
  40. "Author: Ilwoo Lyu\n"
  41. "Please refer to the following papers for details:\n"
  42. "[1] Lyu et al., Hierarchical Spherical Deformation for Shape Correspondence, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2018, LNCS11070, 853-861, 2018.\n"
  43. "[2] Lyu et al., Hierarchical Spherical Deformation for Cortical Surface Registration, Medical Image Analysis, 57, 72-88, 2019.\n"
  44. );
  46. CLI::App app(desc);
  48. /*
  49. app.add_option("--sphereDir", dirSphere, "Specify a directory of sphere files")->check(CLI::ExistingDirectory)->group("Directory inputs");
  50. app.add_option("--propertyDir", dirProperty, "Specify a directory of property files")->check(CLI::ExistingDirectory)->group("Directory inputs");
  51. app.add_option("--outputDir", dirOutput, "Specify a directory of output files")->check(CLI::ExistingDirectory)->group("Directory inputs");
  52. //app.add_option("--landmarkDir", dirLandmark, "Specify a directory of landmark files")->check(CLI::ExistingDirectory);
  53. app.add_option("--coefficientDir", dirCoeff, "Specify a directory of previous spherical harmonics coefficient files")->check(CLI::ExistingDirectory)->group("Directory inputs");
  54. app.add_option("--filter", listFilter, "Specify a list of suffix filters to select desired property files")->group("Directory inputs");
  55. //app.add_option("--surfaceDir", dirSurf, "Specify a directory of surface model files for location information")->check(CLI::ExistingDirectory);*/
  56. app.add_option("-s,--sphere", listSphere, "Specify a list of sphere files")->required()->check(CLI::ExistingFile)->group("File inputs");
  57. app.add_option("-p,--property", listProperty, "Specify a list of property files")->required()->check(CLI::ExistingFile)->group("File inputs");
  58. app.add_option("-o,--output", listOutput, "Specify a list of output sphere files")->group("File inputs");
  59. app.add_option("--outputcoeff", listOutputCoeff, "Specify a list of output coeff files")->group("File inputs");
  60. //app.add_option("-l,--landmark", listLandmark, "Specify a list of landmark files")->check(CLI::ExistingFile);
  61. app.add_option("-c,--coefficient", listCoeff, "Specify a list of previous spherical harmonics coefficient files")->check(CLI::ExistingFile)->group("File inputs");
  62. //app.add_option("--surface", listSurf, "Specify a list of surface model files for location information")->check(CLI::ExistingFile);
  63. //app.add_option("--weightMap", weightMap, "Specify an overall property weight (eta)", true)->check(CLI::NonNegativeNumber);
  64. app.add_option("-d,--degree", degree, "Specify a degree of spherical harmonics decomposition", true)->check(CLI::NonNegativeNumber)->group("Optimization");
  65. app.add_option("--icosahedron", icosa, "Select a icosahedral subdivision level for uniform sampling points", true)->check(CLI::Range(0,7))->group("Optimization");
  66. app.add_option("--weight", listWeight, "Specify weights for each property")->check(CLI::NonNegativeNumber)->group("Optimization");
  67. app.add_option("--idprior", idprior, "Specify inverse of distortion prior for the regularization", true)->check(CLI::NonNegativeNumber)->group("Optimization");
  68. app.add_option("--maxIter", maxIter, "Specify the maxmum number of iterations at the final phase", true)->check(CLI::NonNegativeNumber)->group("Optimization");
  69. //app.add_option("--locationWeight", weightLoc, "Specify a weighting factor of location information", true);
  70. app.add_option("--icomesh", icoMesh, "Specify a pre-defined icosahedral mesh, which overrides --icosaherdon")->check(CLI::ExistingFile)->group("Optimization");
  71. app.add_option("--gres", guessRes, "Specify a search resolution for initial guess", true)->check(CLI::PositiveNumber)->group("Optimization");
  72. app.add_flag("--noguess", noguess, "Do not execute an initial guess for rigid alignment")->group("Optimization");
  73. app.add_flag("--resample", resampling, "Resample geometric properties using the current icosahedral level")->group("Optimization");
  74. app.add_flag("--writecoeff", realtimeCoeff, "Write coefficient whenever the energy is minimized, which may lead to significant IO overhead")->group("Optimization");
  75. app.add_option("--fixedSubjects", listFixedSubj, "Select indices (starting from 0) of the subjects not being deformed during the optimization (typically for template models)")->check(CLI::NonNegativeNumber)->group("Pair-wise registration");
  76. app.add_option("--tmpVar", tmpVariance, "Specify a prior of feature variance (only works on pairwise registration)")->check(CLI::ExistingFile)->group("Pair-wise registration");
  77. app.add_option("--nThreads", nThreads, "Specify the number of OpenMP cores (0: OMP_NUM_THREADS or 1)", true)->check(CLI::NonNegativeNumber)->group("Multi-threading");
  78. #ifdef _USE_CUDA_BLAS
  79. app.add_option("--nStreams", nCThreads, "Specify the number of CUDA streams (0: use full GPU capacity)", true)->check(CLI::NonNegativeNumber)->group("Multi-threading");
  80. #endif
  81. try
  82. {
  83. app.parse(argc, argv);
  84. }
  85. catch (const CLI::ParseError &e)
  86. {
  87. exit(app.exit(e));
  88. }
  89. }

PARSE_ARGS.h at commit f169595, under MIT · at the source

Overview

Authors: Yong Hun Jang1, Jong Min Kim2, Bong Gun Lee3, Jeong-Kyu Hoh4, Gang Yi Lee5, Hyun Ho Kim6, Ilwoo Lyu2,7, Hyun Ju Lee1,8
  1. Department of Paediatrics, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
  2. Graduate School of Artificial Intelligence, POSTECH, Pohang 37673, South Korea
  3. Department of Orthopaedic Surgery, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
  4. Department of Obstetrics and Gynaecology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
  5. Department of Translational Medicine, Hanyang University Graduate School of Biomedical Science and Engineering, Seoul 04763, Republic of Korea
  6. Department of Paediatrics, Jeonbuk National University School of Medicine, Jeonju 54896, Republic of Korea
  7. Department of Computer Science and Engineering, POSTECH, Pohang 37673, South Korea
  8. Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul 04763, Republic of Korea
Institutions: Hanyang University Seoul Hospital (South Korea); Hanyang University (South Korea); Pohang University of Science and Technology (South Korea); Jeonbuk National University Hospital (South Korea); Jeonbuk National University (South Korea)
Journal: Brain communications, volume 8, issue 3, article fcag097
Dates: received 18 August 2025; accepted 24 April 2026; published online 18 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag097 · PMID 42158848 · PMCID PMC13181400 · OpenAlex W7161536315
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: human (organism), other condition (population), developmental (subfield)
Methods: Connectivity, Statistics, fMRI & imaging, Physiology & signal measures
Keywords: preterm infants, early childhood, cortical folding, local gyrification index, sulcal depth
Topic: Infant Development and Preterm Care (Pediatrics, Perinatology and Child Health, Medicine), according to OpenAlex
Funding: National Research Foundation of Korea (RS-2023-NR077125, RS-2024-00333931, RS-2025-02216257); Institute for Information & Communications Technology Planning & Evaluation (RS-2019-II191906)
Citations: not cited yet (Europe PMC); 99 references in the paper
Notices: A correction to this paper has been published (42614990, from Europe PMC)

Abstract

Cortical folding emerges in the late prenatal period and undergoes rapid reorganization during early childhood. However, the long-term impact of folding alterations associated with preterm birth remains unclear. Herein, we analysed the structural MRI data of 56 preterm children and 206 full-term peers aged 1–7 years. We derived cortical metrics from the reconstructed cortical surfaces using a vertex-wise computation framework to characterize regional folding patterns. We then conducted a combined analysis of the local gyrification index and sulcal depth to explain folding patterns in the preterm brain. Compared with their full-term peers, preterm children exhibited a region-specific impairment pattern characterized by a significantly reduced local gyrification index and sulcal depth in the bilateral superior temporal gyrus and left superior frontal gyrus (P < 0.05). Notably, the sulcal depth in the superior temporal cortex showed significant differences between preterm and full-term children in its association with neurodevelopmental outcomes (P < 0.05), indicating an atypical structure–function relationship in preterm children. The local gyrification index was significantly reduced in the right isthmus cingulate and posterior cingulate gyri (P < 0.05), reflecting a simplified gyral configuration. The study findings suggest several folding patterns that capture diverse mechanisms of morphogenetic disruption, indicating that preterm birth induces persistent region-specific impairments in cortical folding that may affect neurodevelopmental domains. These folding-sensitive markers provide critical insights into the development of targeted interventions to optimize long-term neurodevelopmental outcomes.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

ilwoolyu/LocalGyrificationIndex

License: MIT
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: b9fa7609caf2f9b3445238abbfddae8db63f2ebf, 12 October 2020
Languages: MATLAB (9), C++ (2), C/C++ (2)
Size: 19 files, 13 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Image Processing Toolbox (1 file), Optimization Toolbox (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
15 files
At the source: github.com/ilwoolyu/LocalGyrificationIndex

ilwoolyu/HSD

License: MIT
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: f1695956bf833d5f83659db4264ef3cc6faaf950, 21 June 2021
Languages: C/C++ (5), C++ (2), CUDA (2)
Size: 23 files, 9 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
11 files
At the source: github.com/ilwoolyu/HSD

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 22 scripts, each with its path and the digest of its content;
  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

The cohort datasets generated and/or analysed during the current study are not publicly available because of the inability to share personal information according to research ethics but are available from the corresponding author upon reasonable request. Correspondence and requests for materials should be addressed to YHJ () and HJL (). All codes and computational tools used in this study are publicly accessible. The shape-adaptive local gyrification index algorithm is available at: https://github.com/ilwoolyu/LocalGyrificationIndex. The hierarchical spherical deformation framework for cortical surface registration is available at: https://github.com/ilwoolyu/HSD. Statistical analyses were performed using SurfStat (https://www.math.mcgill.ca/keith/surfstat/). A Docker image that integrates cortical morphometry tools, including local gyrification index, sulcal depth and hierarchical spherical deformation, is available at: https://hub.docker.com/r/ilwoolyu/cmorph. These code resources are also provided in the Supplementary Materials.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 8 authors, 5 keywords, 2 funders, 96 references, 1 integrity notice.

Cite

This paper

Jang, Y. H., Kim, J. M., Lee, B. G., Hoh, J.-K., Lee, G. Y., Kim, H. H., Lyu, I., & Lee, H. J. (2026). Long-term effects of preterm birth on cortical folding trajectories in early childhood. Brain communications, 8(3), fcag097. https://doi.org/10.1093/braincomms/fcag097

BibTeX

@article{jang2026long,
author = {Jang, Yong Hun and Kim, Jong Min and Lee, Bong Gun and Hoh, Jeong-Kyu and Lee, Gang Yi and Kim, Hyun Ho and Lyu, Ilwoo and Lee, Hyun Ju},
title = {{Long-term effects of preterm birth on cortical folding trajectories in early childhood}},
journal = {Brain communications},
year = {2026},
month = may,
volume = {8},
number = {3},
pages = {fcag097},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag097},
url = {https://doi.org/10.1093/braincomms/fcag097},
pmid = {42158848},
pmcid = {PMC13181400}
}

RIS

TY - JOUR
AU - Jang, Yong Hun
AU - Kim, Jong Min
AU - Lee, Bong Gun
AU - Hoh, Jeong-Kyu
AU - Lee, Gang Yi
AU - Kim, Hyun Ho
AU - Lyu, Ilwoo
AU - Lee, Hyun Ju
TI - Long-term effects of preterm birth on cortical folding trajectories in early childhood
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/05/18
VL - 8
IS - 3
SP - fcag097
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag097
UR - https://doi.org/10.1093/braincomms/fcag097
LA - en
ER -

CSL-JSON

{
"id": "10.1093/braincomms/fcag097",
"type": "article-journal",
"title": "Long-term effects of preterm birth on cortical folding trajectories in early childhood",
"container-title": "Brain communications",
"author": [
{
"family": "Jang",
"given": "Yong Hun"
},
{
"family": "Kim",
"given": "Jong Min"
},
{
"family": "Lee",
"given": "Bong Gun"
},
{
"family": "Hoh",
"given": "Jeong-Kyu"
},
{
"family": "Lee",
"given": "Gang Yi"
},
{
"family": "Kim",
"given": "Hyun Ho"
},
{
"family": "Lyu",
"given": "Ilwoo"
},
{
"family": "Lee",
"given": "Hyun Ju"
}
],
"container-title-short": "Brain Commun",
"volume": "8",
"issue": "3",
"page": "fcag097",
"DOI": "10.1093/braincomms/fcag097",
"PMID": "42158848",
"PMCID": "PMC13181400",
"ISSN": "2632-1297",
"publisher": "Oxford University Press",
"URL": "https://doi.org/10.1093/braincomms/fcag097",
"language": "en",
"issued": {
"date-parts": [
[
2026,
5,
18
]
]
}
}

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