3T magnetic resonance spectroscopy as a powerful diagnostic modality for assessment of thyroid nodules

Aghaghazvini, Leila; Pirouzi, Pirouz; Sharifian, Hashem; Yazdani, Nasrin; Kooraki, Soheil; Ghadiri, Afsoon; Assadi, Majid

doi:10.20945/2359-3997000000069

Cited by 6 publications

(5 citation statements)

References 24 publications

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“…Magnetic resonance spectroscopy (MRS) is a specific modality for the evaluation of thyroid nodules in differentiation of benign from malignant thyroid tissues [30]. PET is a type of nuclear medicine images, as scintigraphy technique, it is a common and useful medical imaging technique that is used clinically in the field of oncology, cardiology, and neurology [7].…”

Section: Medical Image Modalitiesmentioning

confidence: 99%

Review Research of Medical Image Analysis Using Deep Learning

Mohammed

Al-Ani

2020

UHD J SCI TECH

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In modern globe, medical image analysis significantly participates in diagnosis process. In general, it involves five processes, such as medical image classification, medical image detection, medical image segmentation, medical image registration, and medical image localization. Medical imaging uses in diagnosis process for most of the human body organs, such as brain tumor, chest, breast, colonoscopy, retinal, and many other cases relate to medical image analysis using various modalities. Multi-modality images include magnetic resonance imaging, single photon emission computed tomography (CT), positron emission tomography, optical coherence tomography, confocal laser endoscopy, magnetic resonance spectroscopy, CT, X-ray, wireless capsule endoscopy, breast cancer, papanicolaou smear, hyper spectral image, and ultrasound use to diagnose different body organs and cases. Medical image analysis is appropriate environment to interact with automate intelligent system technologies. Among the intelligent systems deep learning (DL) is the modern one to manipulate medical image analysis processes and processing an image into fundamental components to extract meaningful information. The best model to establish its systems is deep convolutional neural network. This study relied on reviewing of some of these studies because of these reasons; improvements of medical imaging increase demand on automate systems of medical image analysis using DL, in most tested cases, accuracy of intelligent methods especially DL methods higher than accuracy of hand-crafted works. Furthermore, manually works need a lot of time compare to systematic diagnosis.

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Section: Medical Image Modalitiesmentioning

confidence: 99%

Review Research of Medical Image Analysis Using Deep Learning

Mohammed

Al-Ani

2020

UHD J SCI TECH

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“…Intrinsically, thyroid nodules are the most common and typical presentation of TC and are radiographically apparent lesions in the thyroid gland, and the vast majority of thyroid nodules are benign, with an approximate malignancy rate of 5% in adult patients with no history of radiation exposure 3,4 . Currently, the diagnosis of thyroid nodules mainly depends on imaging examinations, including ultrasound (US), 5 computed tomography (CT), 6 and magnetic resonance (MR) 7 . Nevertheless, these diagnostic methods still have certain limitations.…”

Section: Introductionmentioning

confidence: 99%

“…3,4 Currently, the diagnosis of thyroid nodules mainly depends on imaging examinations, including ultrasound (US), 5 computed tomography (CT), 6 and magnetic resonance (MR). 7 Nevertheless, these diagnostic methods still have certain limitations. Specifically, the low reproducibility and operator-depending performance might reduce the diagnostic value of US examination, and therefore, only US images are suboptimal to diagnose TC.…”

Section: Introductionmentioning

confidence: 99%

“…21 Additionally, of the exceedingly used cell proliferation biomarkers, Ki-67 is considered an independent prognostic factor in TC patients, and its high expression is associated with tumor deterioration and poor survival. 22,23 (4) with hypertension, hyperlipidemia, or hyperglycemia; (5) with other malignant tumors; (6) with a history of suffering from thyroid diseases and drug therapy; (7) with large areas of calcification in the lesion; (8) with other endocrine diseases.…”

Section: Introductionmentioning

confidence: 99%

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Application of dual‐source computed tomography in the diagnosis of thyroid cancer and evaluation of biological behaviors

Fang

et al. 2022

J of Clinical Ultrasound

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Objective Thyroid cancer (TC) is an extremely prevailing malignant endocrine tumor. Therefore, effective diagnostic tools are necessary. This study explored the application value of dual‐source computed tomography (DSCT) in TC diagnosis and biological behavior assessment. Methods This study retrospectively selected 68 TC patients and another 74 benign patients with thyroid adenoma, nodular goiter, or adenomatous hyperplasia. All patients were confirmed by pathological examination and underwent DSCT examination. The iodine concentration (IC) obtained from plain computed tomography (CT) scanning and normalized iodine concentration (NIC) in the arterial phase and venous phase were recorded. The positive expression rates of estrogen receptor alpha (ERα), estrogen receptors beta (ERβ), and Ki67 in pathological tissues were determined by immunohistochemistry, and their correlation with IC in plain CT was assessed by Pearson correlation analysis, respectively. The diagnostic values of IC in plain CT and venous phase NIC in TC patients were evaluated using the receiver operating characteristic curve. Results Malignant patients had lower IC in plain DSCT scanning, venous phase NIC, and ERβ, and higher ERα and Ki67 than benign patients. IC level in plain DSCT scanning was inversely‐correlated with ERα and Ki‐67 positive expression rates, but positively‐related to ERβ to different degrees. For the diagnosis of TC patients, the AUC of IC level in plain DSCT was 0.771, with a cut‐off value of 1.250 (97.06% sensitivity and 41.89% specificity), and the AUC of venous phase NIC was 0.738, with a cut‐off value of 0.825 (100% sensitivity and 43.24% specificity). Conclusion The IC level obtained from DSCT scanning could assist in the differential diagnosis of malignant and benign thyroid nodules and evaluation of biological behaviors.

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“…I n this issue of the Archives of Endocrinology and Metabolism (AE&M), the use of 3T Magnetic Resonance Spectroscopy (MRS) for the evaluation of patients with thyroid nodules (TNs) is addressed in a very interesting prospective study by Aghaghazvini and cols (1).…”

mentioning

confidence: 99%