The evolving role of MRI in the detection of extrathyroidal extension of papillary thyroid carcinoma: a systematic review and meta-analysis

Abstract

Background

Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer, and the presence of extrathyroidal extension (ETE) significantly impacts treatment decisions and prognosis. Accurate preoperative detection of ETE remains challenging, highlighting the need to evaluate advanced imaging techniques.This systematic review and meta-analysis aimed to investigate the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting extrathyroidal extension (ETE) among patients diagnosed with papillary thyroid carcinoma (PTC).

Method

We conducted a comprehensive search of global databases including PubMed, Web of Science, EMBASE, and the Cochrane Library, spanning from inception to November 03, 2024. We included studies that utilized preoperative MRI to evaluate the presence of ETE. Quality assessment was carried out using the Joanna Briggs Institute (JBI) standard checklists. Data analysis was performed using Comprehensive Meta-Analysis (CMA) software version 3. The study protocol was registered in PROSPERO (CRD42024499536).

Result

Six studies were included in our final quantitative analysis. The included studies were classified into two groups; the first group focused on evaluating the accuracy of MRI in detecting ETE, while the second group assessed the apparent diffusion coefficient (ADC). The accuracy of MRI for overall ETE, minimal ETE (mETE), and gross ETE (gETE) was 81.0% (95% CI: 76.9%-85.6%), 72.9% (95% CI: 66.2%-78.6%), and 83.3% (95% CI: 75.2%-89.1%), respectively. MRI demonstrated a statistically significant difference in detecting gETE compared to mETE (OR = 1.85, 95% CI: 1.01–3.37, P-value = 0.045). Our analysis showed that the ADC of the lesion for b-value 500 is lower in patients with ETE compared to those without ETE (SMD = 0.95, 95% CI: 0.28–1.62, P-value = 0.005).

Conclusion

Our findings demonstrate that MRI has substantial accuracy in detecting ETE in PTC, especially for gross ETE. This suggests MRI could be a valuable tool in preoperative planning, helping to guide surgical decision-making by more precisely identifying patients at higher risk. However, the limited number of studies underscores the need for further research to confirm MRI’s role in routine clinical practice and to refine imaging protocols for more accurate differentiation between minimal and gross ETE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-024-13288-1.

Background

Papillary thyroid carcinoma (PTC) is a prominent type of thyroid cancer, constituting more than 80% of all cases [1, 2]. PTC is widely recognized for its favorable prognosis and low mortality rate. However, there has been an increasing trend in the incidence of PTC in recent years [3, 4].

Age, gender, histological variety, lymph node metastasis, tumor size, and extrathyroidal extension (ETE) are known as the prognostic factors for PTC that can influence patient outcomes [4–6]. ETE is one of the important prognostic factors for PTC that is defined as the invasion of the primary tumor into surrounding anatomical structures and extension beyond the thyroid capsule [7, 8].

The eighth edition of the American Joint Commission on Cancer (AJCC) staging manual classifies ETE into gross (gETE) and minimal (mETE), emphasizing its significance in determining the stage of PTC [9, 10]. Gross ETE is characterized by a substantial invasion of the tumor beyond the thyroid capsule, involving adjacent tissues and anatomical structures. In contrast, microscopic extrathyroidal extension (mETE) is not visibly apparent but is identifiable upon microscopic examination [10]. The presence of ETE in patients diagnosed with thyroid carcinoma is associated with tumor recurrence and poor prognosis, thus influencing clinical decision-making [11, 12]. As highlighted in the latest edition of the AJCC staging manual, in contrast to mETE, gETE is an important factor for tumor staging in PTC and is included during the staging process [8, 10].

Recently preoperative ultrasonography (US) has been widely used for the evaluation of ETE in PTC patients [13]. While the US is a valuable tool for detecting and assessing ETE in PTC, there are some limitations to its accuracy. US is an operator-dependent imaging study, and its accuracy can vary from user to user. The specificity of the US in diagnosing ETE is low, especially when using a non-restrictive definition, despite good sensitivity [14]. The sensitivity of ETE detection using ultrasound based on the result of recent meta-analysis was 76% (95%CI = 74–78%) and the specificity of ETE detection was 51% (95%CI = 49–54%)(13). The reported sensitivity of sonographic assessment for ETE varied from 65.2% to 85.3%. And its specificity varied from 68.9% to 81.8% [15]. Several studies have suggested that magnetic resonance imaging (MRI) has favorable accuracy in diagnosing ETE (ranged from 79.1% to 83.2%) [16–18]. Large tumors or extensive ETE have been proposed for examination with MRI, particularly if there is an invasion of nearby tissues including the esophagus, trachea, and major arteries [16, 19, 20].

The apparent diffusion coefficient (ADC) value is a quantitative measure derived from diffusion-weighted imaging (DWI) that reflects the diffusion of water molecules within tissue. The apparent diffusion coefficient (ADC) is calculated at different b-values, which represent the strength and timing of the applied diffusion gradients, controlling the sensitivity to the molecular diffusion of water in tissues. In the clinical context ADC values are particularly relevant for evaluating tumor aggressiveness and invasiveness in different tumors like Breast Lesions, hepatic and prostate cancer [21–23].

In this meta-analysis, our objective was to systematically assess the potential role of MRI as a diagnostic tool in detecting ETE in patients with PTC. Additionally, we aimed to compare the accuracy of MRI in identifying gETE versus mETE in PTC patients and evaluate the potential of ADC as a predictor for ETE.

Method

Reporting

This current meta-analysis and systematic review followed the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [24]. Our study was registered in PROSPERO under the registration number CRD42024499536.

Search strategy

The literature search was conducted using advanced search functions across online electronic databases, including PubMed, Embase, Web of Science, and the Cochrane Library, covering the period from inception to November 03, 2024. The search strategy utilized variations of the following keywords: “thyroid”, “extrathyroidal extension”, “magnetic resonance imaging”, and “MRI”. No restrictions were placed on the publication date. Additionally, gray literature sources including google scholar and relevant publication references were screened for eligible studies. The detailed search strategy is provided in the supplementary file 1. In this meta-analysis, we utilized bibliographic network analysis to explore the interconnections among search terms in the studied field (Fig. 1).

Fig. 1.

bibliographic network analysis

Eligibility criteria

Studies that met the following criteria were included: 1) prospective, retrospective, randomized controlled trial, or case–control study types 2) evaluated the application of MR imaging in the detection of ETE in patients with PTC 3) publication in English.

Studies that meet any of the following criteria were excluded (1): review articles, letters, comments, editorials, case reports, case series, non-original articles, posters or laboratory-animal research (2), studies with insufficient data collection and overlapping clinical data.

Study selection

Two independent researchers initially assessed the records’ eligibility based on title and abstracts. Subsequently, the full text of the selected studies underwent a thorough evaluation by the same reviewers. Any disagreements were resolved by the corresponding author and consensus was ensured in the selection process.

Data extraction

Using a predesigned Excel spreadsheet, two researchers performed data extraction from the included studies. Study details including first author, year, study period, study design, details of MRI system, number of patients with ETE, number of patients without ETE, mean age of patients, mean ADC for b- value of 500 s/mm2 in patients with ETE, mean ADC for b- value of 500 s/mm2 in patients without ETE, optimal ADC for b- value of 500 s/mm2, accuracy of MRI, sensitivity and specificity of MRI was extracted from each included study. Data on the accuracy of MRI and US from each included study were extracted and analyzed to assess the relative performance of each method in detecting ETE.

Quality assessment

The methodological quality of the included studies was evaluated using the Joanna Briggs Institute checklist (JBI) that generally assesses aspects including study design, participant selection, data collection, statistical analysis, and the overall quality of reporting [25]. The outcome of the quality assessment is categorized as either high (quality score above 7), moderate (quality score between 4 and 7), and low (quality score below 4), reflecting the level of bias identified in the study.

Data synthesis and analysis

Comprehensive Meta-Analysis (CMA) software version 3 was employed for all statistical analyses. Statistical analysis was conducted on two sets of groups based on the extracted data. The first set of data was utilized to assess the overall accuracy of MRI in detecting ETE, while the second set was used to evaluate ADC in patients with ETE. The comparison of MRI accuracy between gETE and mETE was reported using the odds ratio (OR). Additionally, the standardized mean difference (SMD) was calculated to statistically compare the ADC in patients with and without ETE. All statistical analyses were performed using a random-effects model to accommodate variations in effect sizes across individual studies due to differences in study designs and methodologies. Statistical significance was considered for P-values less than or equal to 0.05. A power analysis was also conducted to detect a true effect if present. Heterogeneity among the studies was evaluated using I² tests, with results being considered heterogeneous when I² surpassed 50% and the P-value was less than 0.1. Due to a limited number of eligible studies, using a funnel plot to assess the publication bias was not possible.

Results

Main result

Initially using specific search phrases, an advanced search resulted in a total of 265 studies. Following the elimination of duplicates, the titles and abstracts of 175 publications were evaluated. A total number of 6 articles fulfilled the inclusion criteria in the final stage (Fig. 2). The key characteristics of these included studies are shown in Table 1 and Table s1 in supplementary file. All studies were published between 2014 and 2022, with 4 studies coming from China [16, 17, 19, 21], 1 from the USA [18], and 1 from South Korea [15]. A total of 629 patients were included in this meta-analysis.

Fig. 2.

Study selection process

Table 1.

Characteristics of included studies

Author, year	Country	Period	Study design	Patient No	MRI System	MRI protocols	Diagnostic performance	Accuracy	Imaging Reader data	Blinding	Total score
Hu 2020 [18]	China	2014–2018	Retrospective	85	1.5 T MR scanners (GE Signa HD 1.5 T MR scanner; GE Healthcare Systems, Milwaukee, WI, USA) with an eight-channel high-resolution receiver synergy head /neck phased-array coil	T1WI, T2WI, DWI, and contrast-enhanced MRI	Sensitivity: 76.6 Specificity: 76.6 PPV: 93.8 NPV: 89.1	85.7	2 independent Radiologists	yes	8
Hu 2022 [17]	China	2014–2018	Retrospective	158	1.5 Tesla MR scanners (GE Signa HD 1.5 TMR scanner; GE Healthcare Systems, Milwaukee, WI, USA, and UIH uMR560 1.5 T MR scanner, United Imaging Healthcare, Shanghai, China) equipped with an eight-channel high-resolution receiver synergy-head /neck phased-array coil	T1WI, T2WI, DWI, and contrast-enhanced MRI	Sensitivity: NA Specificity: NA PPV: NA NPV: NA	79.1	2 independent Radiologists	yes	8
Kim 2014 [16]	South Korea	2011–2014	Retrospective	67	1.5-T Avanto (Siemens, Erlangen, Germany) MR unit using a neck coil	T1WI and T2WI	Sensitivity: 88.7 Specificity: 77.5 PPV 92.1 NPV: 68.5	83.2	2 independent Radiologists	yes	8
Author, year	Country	Period	Study design	Patient No (with ETE / without ETE)	MRI System	mean ADC in patients with ETE	mean ADC in patients without ETE	b-value sec/mm 2	optimal ADC cutoff *10–6	optimal AUC	Total score
Hao 2016 [20]	China	2014–2015	Retrospective	60 (31-/29)	3 T (HD 750; GE Healthcare, Milwaukee, WI) using an eight-channel head and neck neurovascular array coil	1.44 ± 0.30	1.54 ± 0.28	500	1.355	0.647	9
Hu 2021 [26]	China	2015–2017	Retrospective	238 (93/145)	1.5 Tesla MR scanners (147 patients on GE Signa HD; GE Healthcare, Milwaukee, Wisconsin, and 91 patients on UIH uMR560, United imagining Healthcare, Shanghai, China) with an eight-channel high-resolution receiver synergy -head/neck phased-array coil	1.35 ± 0.29	2.32 ± 0.99	500	1.407	0.905	9
Lu 2015 [19]	USA	2011–2012	Prospective	21 (7/14)	3-Tesla GE scanner (General Electric, Milwaukee, WI) using an eight-channel neurovascular phased-array coil	1.53 ± 0.25	2.37 ± 0.67	500	1.85	0. 85	8

MRI magnetic resonance imaging, T1WI T1 weighted image, T2WI T2 weighted image, DWI Diffusion-weighted imaging, PPV Positive predictive value, NPV Negative predictive value, NA not available, ADC apparent diffusion coefficient, ETE extrathyroidal extension

The pooled accuracy of preprocedural MRI for detecting gETE and mETE was 83.3% and 72.9%, respectively. Our findings underscore a statistically significant superiority in MRI accuracy for detecting gETE over mETE (OR = 1.85, 95% CI = 1.01–3.37, P = 0.045).

Figure 3 shows the forest plot illustrating the distribution and effect sizes of the individual studies contributing to the pooled accuracy. Notably, all statistical analyses are presented in Table 2, providing a comprehensive overview of the study outcomes.

Fig. 3.

A) Forest plot of pooled MRI accuracy B) pooled MRI accuracy for mETE C) pooled MRI accuracy for g ETE D) MRI accuracy for gETE vs mETE E) MRI accuracy vs US for overall ETE

Table 2.

Results of analysis

Parameter	Effect size	I2	P-value
MRI accuracy for minimal extrathyroidal extension	72.9% (66.2–78.6)	0.00	0.890
MRI accuracy for gross extrathyroidal extension	83.3% (75.2–89.1)	0.00	0.558
MRI accuracy for overall extrathyroidal extension	81.6% (76.9–85.6)	0.00	0.424
MRI accuracy for gross vs minimal extrathyroidal extension	OR = 1.85 (1.01–3.37)	0.00	0.730
MRI accuracy vs US	OR = 0.875 (0.506–1.513)	31.94	0.230
The Apparent diffusion coefficient in patients with and without extrathyroidal extension	SMD = 0.955 (0.287–1.623)	78.45	0.01

OR odds ratio, SMD standard difference in mean

The pooled accuracy of MRI in detecting ETE was determined to be 81.0% (95% CI = 76.9%−85.6%) based on data from 3 studies (I² = 0.00, P = 0.424). In comparison to ultrasound (US), although MRI exhibited a 12.5% lower likelihood of detecting ETE, this difference did not reach statistical significance (P = 0.633).

A total number of 3 studies (319 patients) compared the ADC in patients with and without ETE [19, 20, 26](Fig. 4). The results of the random effect meta-analysis are shown in Table 1. Our analysis revealed that compared to patients without ETE, the ADC of lesion for a b-value of 500 in patients with ETE ETE is lower (SMD = 0.955, 95% CI: 0.28–1.62), which is statistically significant (P = 0.005). The results of the ADC analysis also demonstrated the presence of heterogeneity (I² = 78.45%, P = 0.01). The optimal threshold for the mean ADC500 value of detecting ETE in the studies ranged from 1.355 × 10–6 mm²/s to 1.85 × 10–6 mm²/s.

Fig. 4.

A) Forest plot for comparison of ADC in patients with and without ETE B) Sensitivity analysis

The power analysis conducted for MRI accuracy in detecting gETE and mETE revealed a high power of final effect size (1-β = 0.98, number of effect sizes = 3, the average number per group = 103) (Fig. 5). The calculated power suggests that our study has a high chance of capturing a significant effect given the current sample size, effect size, and alpha level. Moreover, the result of power analysis for ADC difference in patients with and without ETE revealed a high power of final effect size (1-β = 0.99, number of effect sizes = 3, the average number per group = 106) (Fig. 5) that aligns with recommended thresholds for reliable hypothesis testing and emphasizes the study's ability to detect meaningful differences in ADC in patients with and without ETE.

Fig. 5.

Power analysis for A) difference between ADC in patients with and without ETE. B) difference between MRI accuracy in detecting mETE and gETE

Quality assessment of the studies

A risk of bias assessment was conducted using JBI checklists for diagnostic test accuracy. The results are included in Table 3. Five out of six studies were of a retrospective design. All of the included studies except one by Lu et al. [19] may have had a low risk of selection bias considering the fact that patients underwent MRI when ETE was clinically probable for them. All of the included studies were considered to have high quality.

Table 3.

Risk of bias assessed based on the JBI critical appraisal tools

	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Total score
Hao, 2016 [20]	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	9/10
Lu, 2015 [19]	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	8/10
Hu, 2021 [26]	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	9/10
Hu, 2020 [18]	Yes	No	Yes	Yes	NA	Yes	Yes	Yes	Yes	Yes	8/10
Hu, 2022 [17]	Yes	No	Yes	Yes	NA	Yes	Yes	Yes	Yes	Yes	8/10
Kim, 2014 [16]	Yes	No	Yes	Yes	NA	Yes	Yes	Yes	Yes	Yes	8/10

The JBI checklist for diagnostic test accuracy studies was presented in Supplementary File 1

Discussion

Based on current literatures the incidence of ETE in patients with PTC varies between 14.2% −74.7% [27–30]. It is widely recognized that ETE increases the risk of recurrence and mortality in patients with PTC [31].

The diagnosis of ETE in patients with PTC is important for establishing different surgical approaches, postoperative patient management, guiding adjuvant therapy decisions and impacting prognostic assessments [31, 32].

Based on the latest practice guidelines of the National Comprehensive Cancer Network (NCCN) for thyroid carcinoma a total thyroidectomy for patients with extensive ETE was recommended. The presence of ETE in PTC patients necessitates more extensive surgical intervention compared to patients without ETE. The treatment approach may involve less extensive surgery, depending on the absence of ETE and the individual's risk stratification [33, 34]. The latest guidelines from the American Thyroid Association (ATA) suggest that extensive surgical intervention, such as total thyroidectomy followed by RAI adjuvant therapy, is recommended for cases of PTC with gETE or lymph node involvement. However, these guidelines also consider active surveillance as a suitable alternative when ETE is absent. Despite the growing endorsement of active surveillance for thyroid cancer in the ATA guidelines, there remains significant hesitation among clinicians in the United States. One reason for this hesitancy is the accuracy of detecting tumor progression by imaging studies, which may be limited in their reliability in identifying concerning features. Consequently, it is essential to utilize imaging methods that can effectively identify tumors with high-risk features likely to progress [32].

Although the standard diagnostic method for detecting ETE is biopsy, currently, preprocedural ultrasonography is widely used for the detection of ETE in patients with PTC [13, 35]. Various studies have shown that the accuracy of ultrasound reports describing pathological features is suboptimal not only for mETE but also for gETE. In a recent meta-analysis ultrasound showed a sensitivity of 76.4%, a specificity of 51.2%, and a DOR of 5.317 in detecting ETE [36, 37]. The accuracy of ultrasound may be influenced by factors including the expertise of the sonographer (radiologist, surgeon, or ultrasound technician), the quality of the ultrasound equipment (including probe transducer frequency), and patient-specific factors [36, 38, 39].

In addition to ultrasound, other imaging techniques are employed to evaluate thyroid pathology in the neck. For instance, CT imaging provides reliable, three-dimensional visualization of the neck [40]. Lee et al. reported a sensitivity of 87.8% and a specificity of 48.6% for CT scan in ETE [40]. Currently, the overall utilization of MRI for the thyroid gland is increasing [18]. MRI has both advantages and limitations compared to biopsy for detecting ETE in papillary thyroid carcinoma. As a non-invasive imaging method, MRI provides detailed visualization of soft tissue, aiding in assessing tumor invasion into adjacent structures without the risks associated with biopsy, such as bleeding, Pain/discomfort, or infection. Moreover, MRI offers the advantage of providing detailed soft tissue contrast and an assessment of extrathyroidal extension, which can be useful in preoperative planning. However, its higher cost, and longer procedure time present challenges that must be considered when deciding on diagnostic strategies [41–43].

The pooled results of our analysis revealed that the accuracy of MRI in detecting overall ETE is 81.6% (76.9%−85.6%) based on existing studies. Also, our study revealed that MRI has better accuracy in detecting gETE than mETE. (OR = 1.85, 95% CI = 1.01–3.37, P-value = 0.045). The majority of studies revealed that mETE has a limited impact on clinical outcomes in PTC patients [44–49]. Sonography is more accurate and sensitive in detecting mETE compared to MRI, while MRI has been more accurate in detecting gETE [16, 17].

Hu et al. reported an accuracy of 79.1% for MRI in detecting ETE [17]. Also, in other studies, the accuracy of MRI in detecting ETE was reported at 85.7% and 83.2% [16, 18].

Due to the results of our analysis, it seems that there is no statistically significant difference in accuracy between MRI and ultrasound in detecting ETE. This could be due to a limited number of included studies. Kim et al. revealed that the US had higher accuracy (92.6% vs 83.2%) higher sensitivity (100% vs. 88.7%) and higher NPV (100% vs. 68.5%) than MRI for detecting ETE in PTC [16]. We only found one study that reported a higher accuracy of MRI in detecting ETE compared to the US (85.7% vs 81.9%) [18]. Furthermore, studies have reported that due to high superior predictability and ease of application, MRI is suggested to be reserved for extensive and overall ETE [16, 19, 50]. MRI is widely recognized as a non-invasive imaging technique with excellent tissue resolution and contrast, with no exposure to ionizing radiation [38, 39]. MRI imaging offers several advantages over the US and CTscan. It is inherently more intuitive and less susceptible to examiner subjectivity. Moreover, MRI enables precise tumor localization preoperatively and provides visualization of anatomical regions inaccessible to the US, such as the mediastinum and Parapharynx. With higher resolution and immunity to the interference of skeletal structures or gas, MRI ensures clear delineation of tumor boundaries and their relationship with adjacent structures like the trachea. This superior soft tissue resolution facilitates accurate lesion staging and definition of peripheral invasion pre-surgery. This becomes particularly apparent in cases involving invasion of the tracheal mucosa by PTC. With recent technological advancements, MRI now offers the capability to precisely assess the extent of PTC invasion into the recurrent laryngeal nerve, providing detailed visualization of its continuity and any abnormal signal intensity surrounding the lesion [17, 51].

In the evaluation of gross extrathyroidal extension (ETE), MRI may offer certain diagnostic advantages over contrast-enhanced CT, despite its greater availability, faster imaging time, and lower cost [43]. MRI provides excellent soft tissue contrast, which can improve visualization of subtle tumor invasion into surrounding structures such as the trachea or recurrent laryngeal nerve [43, 52, 53]. This level of detail is particularly valuable in cases where accurate anatomical delineation directly affects surgical planning or radiotherapy approaches. While CT is a convenient and readily available imaging option, the increased accuracy of MRI in certain cases of ETE may provide important information that can guide more appropriate treatment decisions [17].

One of the derived quantitative measurements available from a specific type of MRI is the ADC, calculated automatically using Diffusion-weighted magnetic resonance imaging (DWI-MRI).

DWI-MRI is a sequence utilized in MR imaging that measures the random Brownian motion of water molecules within a voxel of tissue and has various applications in oncology and body imaging by providing valuable information about alterations in tumor composition, molecular activity, and cellular function [54, 55].

DWI-MRI is utilized as a non-invasive adjunct to FNAB (fine needle aspiration biopsy) and is reported to help differentiate benign and malignant thyroid tumors [56, 57]. ADC serves as a valuable indicator of water movement, offering insights into tumor cellularity and cell membrane integrity. A decrease in ADC suggests restricted water diffusion, possibly due to reduced water flow, while elevated ADC values indicate uninhibited water flow within tissues. As cell proliferation increases, cellular density rises, accompanied by a decrease in available intracellular (ICS) or extracellular space (ECS), ultimately resulting in a reduction in ADC [58, 59]. ADC is computed using various b-values, which signify the magnitude and duration of applied gradients, as well as the time between paired gradients [60]. Therefore, the choice of b values can affect the accuracy of ADC measurements. Hu et al. revealed that b-value 500 has the highest AUC compared to b-value 300 and 800 in differentiating ETE of tumors from normal tissue (AUC = 0.905) [26].

The results of our analysis also suggest that ADC₅₀₀ in papillary thyroid carcinoma patients with ETE was significantly lower compared to patients without ETE. ADC has recently is using as a biomarker in different cancer fields including prostate, breast, and rectal cancer [19]. Furthermore, various studies note that DWI and ADC are valuable preoperative tools in the differentiation of malignant and benign thyroid tumors [57, 61, 62]. Studies revealed that ADC has the potential to predict ETE as an aggressive histological feature in PTC [19, 20]. With its advanced technology and robust data quantification capability, MRI surpasses ultrasound in evaluating ETE.

Some limitations should be acknowledged in interpreting the findings of this meta-analysis. As stated, the limited number of included studies made it impossible to use the funnel plots for assessing publication bias. The excluding non-English articles may introduce a language bias, potentially overlooking relevant studies published in other languages. Additionally, technical heterogeneity may arise from the various characteristics of MRI systems used in the included studies. Furthermore, due to the limited number of included studies, we were not able to perform different subgroup analyses to identify the source of heterogeneity in the analyses.

Conclusion

In general, based on the available information, making definitive or highly probable comments regarding the widespread use of different types of preoperative MRI in diagnosing ETE is challenging. Differences in the studies performed, including differences in the accuracy and power of MRI machines, preclude definitive conclusions. However, the significance of ADC in predicting ETE is clear. Considering the advanced features of MR imaging, its superiority over other imaging methods, and the importance of diagnosing ETE before choosing treatment methods for patients with PTC, more extensive studies should be conducted to determine the role of MRI in diagnosing ETE. Based on our findings, we suggest future studies with larger sample sizes to enhance the statistical power of comparisons between MRI and ultrasound for detecting ETE. Additionally, research focusing on refining MRI protocols or combining imaging modalities could improve diagnostic accuracy Moreover, extensive comparative studies should be conducted with a larger sample size and in the form of a comparison between different b-values, to find the best b-value and the best diagnostic ADC cutoff. Our findings demonstrate that MRI has substantial accuracy in detecting ETE in PTC, especially for gross ETE. This suggests that MRI could be a valuable tool in preoperative planning, helping to guide surgical decision-making by more precisely identifying patients at higher risk. While MRI may not be universally necessary in all cases, its potential value in high-risk cases could justify its inclusion in the imaging protocol for preoperative assessment of ETE.

Abbreviations

ADC

Apparent diffusion coefficient

AJCC

American Joint Commission on Cancer

CI

Confidence interval

AUC

Area under curve

CMA

Comprehensive Meta-Analysis

DWI

Diffusion-weighted imaging

ECS

Extracellular space

ETE

Extrathyroidal extension

FNAB

Fine needle aspiration biopsy

gETE

Gross extrathyroidal extension

ICS

Intracellular space

JBI

Joanna Briggs Institute checklist

mETE

Minimal extrathyroidal extension

MRI

Magnetic resonance imaging

NA

Not available

NCCN

National Comprehensive Cancer Network

NPV

Negative predictive value

PPV

Positive predictive value

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PTC

Papillary thyroid carcinoma

SMD

Standardized mean difference

T

Tesla

T1WI

T1 weighted image

T2WI

T2 weighted image

US

Ultrasonography

Authors’ contributions

All authors contributed to the manuscript preparation. M.J. and A.M. contributed to the study's conception and design. Database searching and data collection were performed by E.AS., E.A., and MH.K. Material preparation was performed by MR.J and N.N. Analysis was performed by S.H. and A.M. The first draft of the manuscript was written by M.J. and A.M. and all authors commented on previous versions of the manuscript. The process was supervised by S.H. and A.A. All authors read and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.