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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_10000063148 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000218960 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063150 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000218992 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063152 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219088 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063154 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219120 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063156 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219280 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063158 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219312 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063160 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219408 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063162 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219440 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063164 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219344 N/A N/A XH6SY0 / XH0Q59 / XH29M4 PTC like features
HISTOSMT_10000000038 HISTOSM_10000063166 N/A N/A 5A01.2 FND
HISTOSMT_10000000038 HISTOSM_10000219376 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_10000122483 HISTOET_10000000015 HISTOE_10000122335 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122484 HISTOET_10000000015 HISTOE_10000122336 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122486 HISTOET_10000000015 HISTOE_10000122338 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122502 HISTOET_10000000015 HISTOE_10000122354 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000082300 HISTOET_10000000015 HISTOE_10000080539 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000082301 HISTOET_10000000015 HISTOE_10000080540 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122503 HISTOET_10000000015 HISTOE_10000122355 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122505 HISTOET_10000000015 HISTOE_10000122357 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000082303 HISTOET_10000000015 HISTOE_10000080542 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122521 HISTOET_10000000015 HISTOE_10000122373 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122522 HISTOET_10000000015 HISTOE_10000122374 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122524 HISTOET_10000000015 HISTOE_10000122376 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122540 HISTOET_10000000015 HISTOE_10000122392 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122541 HISTOET_10000000015 HISTOE_10000122393 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122543 HISTOET_10000000015 HISTOE_10000122395 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122559 HISTOET_10000000015 HISTOE_10000122411 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122560 HISTOET_10000000015 HISTOE_10000122412 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122562 HISTOET_10000000015 HISTOE_10000122414 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122578 HISTOET_10000000015 HISTOE_10000122430 Derived N/A Hematoxylin and Eosin (H&E) 40x 10% Neutral buffered formalin Training Dataset
HISTOSM_10000122579 HISTOET_10000000015 HISTOE_10000122431 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_10000062365thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_226.tiff Unable to preview image
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308K
HISTOE_10000062366thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_227.tiff Unable to preview image
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276K
HISTOE_10000062367thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_228.tiff Unable to preview image
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260K
HISTOE_10000062368thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_229.tiff Unable to preview image
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280K
HISTOE_10000062369thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_22.tiff Unable to preview image
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232K
HISTOE_10000062370thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_230.tiff Unable to preview image
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312K
HISTOE_10000062371thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_231.tiff Unable to preview image
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304K
HISTOE_10000062372thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_232.tiff Unable to preview image
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268K
HISTOE_10000062373thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_233.tiff Unable to preview image
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304K
HISTOE_10000062374thyroid_lesions/STAGE1_BTID/ET_BTID/ET_FND/ET_FND_234.tiff Unable to preview image
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284K