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Study Complete Details




Project Accession: IBIAP_1000000010
Title: Histopathological images of thyroid lesions
Representative Image:
Description: The dataset comprises 154,498 images derived from 134 slides, representing 125 thyroid nodules from 118 patients. These images encompass six types of thyroid lesions: NIFTP, HTN, FA, IEFVPTC, IFSPTC, and CPTC.
Publications: https://link.springer.com/article/10.1007/s12022-025-09865-0
Associated Codes (URL only): N/A
Funding agency: DBT
Grant Number: BT/PR34211/AI/133/1/2019
Ethics Statement: N/A
Any Other Information : N/A
Additional File: N/A
Acknowledgments: This work was supported by the Department of Biotechnology (DBT) [grant numbers BT/PR34211/AI/133/1/2019 and BT/PR40151/BTIS/137/5/2021]. We would like to express our gratitude to the patients who participated in the study, as well as to the AIIMS and ICGEB for providing the necessary infrastructure for conducting the study. We acknowledge Chhaya, Ashish, Divya and Dhairya's crucial assistance in image QC data curation.

Sr.No First name Last name Email Organization Designation
1 Shweta Birla sbirla84@gmail.com International Centre for Genetic Engineering Biotechnology (ICGEB) Postdoctoral Researcher
2 Nimisha Tiwari nimi.tiwari08@gmail.com International Centre for Genetic Engineering Biotechnology (ICGEB) Research Scholar
3 Pragati Shyamal pragatishyamal1@gmail.com All India Institute of Medical Sciences (AIIMS) Unspecified
4 Arundhati Sharma arundhatisharma1@gmail.com All India Institute of Medical Sciences (AIIMS) Co-Investigator
5 Shipra Agarwal drshipra0902@gmail.com All India Institute of Medical Sciences (AIIMS) Principal Investigator
6 Dinesh Gupta dinesh@icgeb.res.in International Centre for Genetic Engineering Biotechnology (ICGEB) Co-Principal Investigator

Study Accession: HISTOS_1000000014
Title: Utility of Artificial Intelligence in differentiating Non- invasive Follicular Thyroid Neoplasm with Papillary like Nuclear Features from other follicular-patterned thyroid benign and malignant lesions
Imaging Type: Histopathology (HISTO)
Imaging Sub-type: Diagnostic Pathology
Summary: The introduction of the term non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) in 2016 marked a pivotal shift in the classification of encapsulated follicular variants of papillary thyroid carcinoma (eFVPTC) lacking invasive features. While this reclassification significantly reduced overtreatment, the histopathological diagnosis of NIFTP remains challenging due to overlapping features with other thyroid lesions and inter-observer variability. This study presents a novel deep learning (DL)-based, three-stage diagnostic pipeline for distinguishing NIFTP from a wide spectrum of thyroid lesions, including benign and malignant mimics. By replicating the diagnostic strategy of histopathologists, the algorithm evaluates architectural patterns and nuclear features with high precision. Our approach has a potential to enhance diagnostic accuracy in a cost-effective and scalable manner, complementing existing diagnostic methods and thus optimizing clinical decision-making and improving the management of patients with thyroid neoplasms.
Keywords: Histopathology; Deep-Learning; Differential Diagnosis; Thyroid Cancers
Additional / Any Other Information: N/A
Release Date: June 2, 2025
Access Licence Type: Open Access

Table 1. The sample types registered under this study are as follows:
Sample Type IDOrganismTaxon IDBiological EntityLateralitySource TissueSource Cell/Cell-lineCell Organelle
HISTOSMT_10000000038Homo sapiens 9606 Thyroid GlandNot ApplicableThyroid gland tissueN/AN/A

Table 2. The samples registered under this study are as follows:
Sample Type ID Sample ID Method used for Sample Collection Cell Phenotype Studied ICD-11 Code (patient health condition) Presentation / Clinical Diagnosis
HISTOSMT_10000000038 HISTOSM_10000063056 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217872 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063058 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217904 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063060 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217936 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063062 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217968 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063064 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000218096 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063066 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217649 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063068 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217776 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063070 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000217808 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063072 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000218000 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063074 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000218032 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features

Table 3. The experiment types registered under this study are as follows:
Experiment Type IDInstrument NameInstrument TypeManufacturerModel
HISTOET_10000000015Digital Slide Scanning SystemDigital Slide ScannerMoticVM1


Experimental Design Summary (HISTOET_10000000015)
Hematoxylin and Eosin (H&E)-stained slides of histopathologically-confirmed cases of FND, HTN,FA, NIFTP, IEFVPTC, IFSPTC, and CPTC patients were retrieved from the archives of the Department of Pathology, All India Institute of Medical Sciences (AIIMS), New Delhi, India, spanning the period from 2015 to 2023. The corresponding slides were further reviewed by an experienced endocrine pathologist to reconfirm the diagnosis and select representative slides for further analysis. The diagnosis adhered to the criteria outlined in the most recent WHO classification of thyroid neoplasms The selected H&E slides were scanned at 40x magnification (equivalent to 0.25 μm/pixel) using the Motic VM1 whole slide scanner to generate whole slide images (WSIs). The slides were than subjected to AI studies.

Acquired Images Annotation Description (HISTOET_10000000015)
WHO defining criteria for the various thyroid lesions included in the study. For more details, please refer to "Additional File" of the "Project" section for this record.

Table 4. The experiments registered under this study are as follows:
Sample ID Experiment Type ID Experiment ID Image type (Original / Derived / Unknown) Any Other Information Staining Type Images Magnification Tissue / Tumor Fixative Used Dataset Split Type (Training / Validation / Test)
HISTOSM_10000122255 HISTOET_10000000015 HISTOE_10000122107 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122256 HISTOET_10000000015 HISTOE_10000122108 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000082264 HISTOET_10000000015 HISTOE_10000080504 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122258 HISTOET_10000000015 HISTOE_10000122110 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122274 HISTOET_10000000015 HISTOE_10000122126 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122275 HISTOET_10000000015 HISTOE_10000122127 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122277 HISTOET_10000000015 HISTOE_10000122129 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122293 HISTOET_10000000015 HISTOE_10000122145 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122294 HISTOET_10000000015 HISTOE_10000122146 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122296 HISTOET_10000000015 HISTOE_10000122148 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122312 HISTOET_10000000015 HISTOE_10000122164 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122313 HISTOET_10000000015 HISTOE_10000122165 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122315 HISTOET_10000000015 HISTOE_10000122167 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122331 HISTOET_10000000015 HISTOE_10000122183 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122332 HISTOET_10000000015 HISTOE_10000122184 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122334 HISTOET_10000000015 HISTOE_10000122186 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122350 HISTOET_10000000015 HISTOE_10000122202 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122351 HISTOET_10000000015 HISTOE_10000122203 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122353 HISTOET_10000000015 HISTOE_10000122205 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122369 HISTOET_10000000015 HISTOE_10000122221 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset

Experiment ID Image File Name (with path) Image Preview Image Size
HISTOE_10000062345thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_208.tiff Unable to preview image
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284K
HISTOE_10000062346thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_209.tiff Unable to preview image
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252K
HISTOE_10000062347thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_20.tiff Unable to preview image
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268K
HISTOE_10000062348thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_210.tiff Unable to preview image
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264K
HISTOE_10000062349thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_211.tiff Unable to preview image
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288K
HISTOE_10000062350thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_212.tiff Unable to preview image
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264K
HISTOE_10000062351thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_213.tiff Unable to preview image
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284K
HISTOE_10000062352thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_214.tiff Unable to preview image
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252K
HISTOE_10000062353thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_215.tiff Unable to preview image
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288K
HISTOE_10000062354thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_216.tiff Unable to preview image
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296K