Ultrasound elastography for the differential diagnosis of benign and malignant gastrointestinal stromal tumors

Abstract

BACKGROUND

Preoperative distinguishing between benign and malignant gastrointestinal stromal tumors (GISTs) poses a challenge. Ultrasound elastography has emerged as a promising diagnostic tool; however, further investigation is needed to assess its diagnostic accuracy in evaluating GISTs.

AIM

To evaluate the accuracy of ultrasound elastography for differentiating between benign and malignant GISTs.

METHODS

This prospective study included 110 patients with 103 histopathologically confirmed GISTs between January 2021 and December 2023. All tumors underwent conventional ultrasound examination, strain elastography (SE), and shear-wave elastography (SWE) before surgical resection. The study evaluated elastographic parameters such as strain ratio, elastographic patterns, mean elastic modulus, and heterogeneity index. Diagnostic performance was evaluated using receiver operating characteristic curve analysis, with histopathological diagnosis as the reference standard.

RESULTS

Of the 103 GISTs, 45 (43.7%) were benign and 58 (56.3%) were malignant based on modified National Institutes of Health criteria. Malignant GISTs exhibited significantly higher strain ratios (4.82 ± 1.73 vs 2.31 ± 0.89; P < 0.001) and mean elastic modulus values (45.6 ± 15.8 kPa vs 21.3 ± 8.4 kPa; P < 0.001) than benign tumors. The optimal cutoff values were 3.45 for the strain ratio (sensitivity: 84.5%, specificity: 86.7%) and 32.5 kPa for the mean elastic modulus (sensitivity: 87.9%, specificity: 88.9%). The areas under the curve were 0.892 and 0.918, respectively. Interobserver agreement was excellent for both SE [intraclass correlation coefficient (ICC) = 0.88] and SWE (ICC range: 0.85-0.93) measurements.

CONCLUSION

Ultrasound elastography shows high diagnostic accuracy in distinguishing between benign and malignant GISTs. Combining SE and SWE provides complementary parameters for preoperative risk stratification.

Key Words: Gastrointestinal stromal tumor; Ultrasound elastography; Strain elastography; Shear-wave elastography; Differential diagnosis

Core Tip: Ultrasound elastography, combining strain elastography and shear-wave elastography, provides excellent diagnostic precision in distinguishing between benign and malignant gastrointestinal stromal tumors (GISTs). A study involving 103 GISTs revealed that malignant tumors displayed notably elevated strain ratios and average elastic moduli. The optimal thresholds for strain ratio (3.45) and mean elastic modulus (32.5 kPa) exhibited high sensitivity and specificity. This noninvasive imaging approach can facilitate preoperative risk assessment and enhance the diagnostic evaluation of GISTs.

INTRODUCTION

Gastrointestinal stromal tumors (GISTs) are the most prevalent mesenchymal neoplasms in the GI tract, constituting approximately 1%-3% of all GI malignancies[1]. These tumors originate from the interstitial cells of Cajal or their precursors and can manifest anywhere along the GI tract, with the stomach (60%-70%) and small intestine (20%-30%) being the most frequent sites[2]. The clinical importance of GISTs lies in their diverse biological behavior, ranging from benign to highly malignant, necessitating precise preoperative diagnosis for optimal treatment planning and management[3].

Traditional imaging methods, such as conventional ultrasound, computed tomography (CT), and magnetic resonance imaging, have limitations in distinguishing between benign and malignant GISTs, especially for smaller lesions[4]. The prevailing diagnostic standard heavily depends on histopathological examination and immunohistochemical analysis, which are invasive and may not always be feasible or suitable for all patients[5]. This diagnostic complexity has led to the investigation of innovative, noninvasive imaging techniques that can offer more precise preoperative risk assessment[6].

Ultrasound elastography has emerged as a promising diagnostic tool in recent years, offering the ability to noninvasively evaluate tissue stiffness and mechanical properties[7]. This technology is based on the principle that pathological changes in tissues often result in alterations in their elastic properties, with malignant lesions typically displaying increased stiffness compared to benign lesions[8]. Several studies have demonstrated the successful application of elastography in various organ systems, particularly in breast and thyroid lesions, where it has shown high diagnostic accuracy in differentiating malignant from benign masses[9].

The utilization of elastography in GISTs has garnered growing interest, with initial studies indicating its potential usefulness in GIST diagnosis[10]. Various elastography techniques, such as strain elastography (SE) and shear-wave elastography (SWE), have been individually studied for their capacity to characterize GISTs[11]. These approaches offer both qualitative and quantitative evaluations of tissue elasticity, potentially providing valuable data for risk stratification and treatment planning[12].

Recent technological advances have resulted in the creation of more advanced elastography systems with enhanced spatial resolutions and quantitative capabilities[13]. These advancements have facilitated more accurate measurements of tissue stiffness and improved characterization of mechanical properties[14]. Furthermore, the incorporation of artificial intelligence and machine learning algorithms with elastography data has demonstrated the potential to enhance diagnostic accuracy and decrease operator dependency[15].

Despite these advances, standardization of elastography techniques and interpretation criteria for GIST evaluation remains a significant challenge[16]. Several factors, such as tumor size, location, and technical parameters, can impact elastography measurements and potentially influence diagnostic accuracy[17]. Moreover, the correlation between tissue elasticity and the biological behavior of GISTs is not completely understood and necessitates additional investigation[18].

The practical considerations in the clinical application of ultrasound elastography for GIST diagnosis include the requirement for operator expertise, standardized protocols, and correlations with other imaging modalities[19]. Evaluating the cost-effectiveness and accessibility of elastography compared with conventional imaging techniques is essential to ascertain its optimal position in the diagnostic algorithm[20].

The unique aspect of our study is its holistic methodology, incorporating both SE and SWE techniques within the same group of patients. This integration yields complementary qualitative and quantitative data for characterizing GISTs. In contrast to previous studies that primarily focus on SE or SWE, our combined approach enables a more thorough evaluation of tissue elasticity. Additionally, we used standardized measurement protocols with stringent quality control procedures and explored the correlation between elastography parameters and established histopathological risk criteria. This investigation provides valuable insights into the biological underpinnings of tissue stiffness in GISTs. Our multiparametric strategy represents a significant advancement in the noninvasive preoperative evaluation of GISTs compared to traditional single-modality techniques.

This study assessed the diagnostic performance of ultrasound elastography in distinguishing between benign and malignant GISTs and to evaluate its potential as a complementary tool in the preoperative assessment of GISTs.

MATERIALS AND METHODS

Study design and patient population

This prospective observational study took place from January 2021 to October 2024 at Bethune International Peace Hospital (Hebei, China). The research protocol received approval from the institutional review board, and written informed consent was obtained from all participants. All procedures were conducted in compliance with the Declaration of Helsinki and the relevant institutional guidelines.

The study’s inclusion criteria were: (1) Patients aged 18 years or older with suspected GISTs based on conventional imaging findings; (2) Lesions accessible on ultrasound examination; (3) No prior treatment for suspected GIST; and (4) Subsequent surgical resection with histopathological confirmation. The exclusion criteria were: (1) Patients who underwent any neoadjuvant therapy; (2) Lesions with significant calcification or necrosis potentially impacting elastography measurements; (3) Limited ultrasound visualization due to body habitus or lesion location; and (4) Insufficient clinical or pathological data.

Of the 128 patients initially screened, 18 (14.1%) were excluded due to significant calcification or necrosis within the lesions, and 10 (7.8%) were excluded because of poor ultrasound visualization or incomplete data. The final analysis comprised 100 patients with 103 histopathologically confirmed GISTs.

Conventional ultrasound examination

All ultrasound examinations were conducted using a high-end ultrasound system (Model LOGIQ; GE Healthcare, Chicago, IL, United States) equipped with a 1-6 MHz convex transducer and a 3-9 MHz linear transducer. Patients were examined after fasting for at least 8 hours to reduce intestinal gas interference. The examinations were conducted with the patients in the supine position, with additional positions used as necessary for optimal lesion visualization. Two experienced sonographers (Liu JR and Peng L, with 15 and 12 years of experience in GI ultrasound, respectively) independently conducted the examinations.

Conventional B-mode ultrasound parameters, such as tumor location, size (maximum diameter), shape (regular or irregular), boundary (clear or unclear), echo pattern (homogeneous or heterogeneous), and presence of cystic or necrotic areas, were assessed and documented. Color doppler imaging was utilized to evaluate the vascularity of the lesions, employing standardized doppler parameters, which included a pulse repetition frequency of 750 Hz and a wall filter of 50 Hz.

Elastography technique and image acquisition

Ultrasound elastography was conducted immediately after the standard ultrasound examination, using both SE and SWE methods. In SE, a light repetitive compression approach was applied with a transducer to sustain a consistent pressure, as shown by a real-time quality factor on the screen. Five successive measurements were taken for each lesion, with each measurement enduring at least three stable compression-relaxation cycles.

SWE measurements were conducted with minimal precompression, and patients were directed to hold their breath for 3-5 seconds during image acquisition. The region of interest (ROI) was placed to encompass the tumor and adjacent normal tissue, excluding vessels and cystic regions. Ten valid measurements were taken from various lesion areas to ensure that the standard deviations of the measurements did not surpass 30% of the mean.

To ensure quality control and standardization of elastography techniques, the following measures were implemented: (1) All examinations were conducted by two experienced sonographers using the same ultrasound system with consistent settings; (2) A real-time quality factor indicator was utilized during SE to ensure sufficient and consistent compression; (3) For SWE, a stability indicator was monitored to confirm measurement reliability; (4) Measurements were repeated if the standard deviation exceeded 30% of the mean value; (5) Periodic calibration of the ultrasound system was performed using a standardized phantom; and (6) Monthly interobserver agreement assessments were carried out to maintain measurement consistency. For deep-seated lesions, specific adaptations, such as optimal patient positioning, selection of an appropriate transducer frequency, and utilization of acoustic windows, were employed to enhance signal quality.

Image analysis and elastography parameters

The SE images were evaluated both qualitatively and quantitatively. The qualitative analysis utilized a five-point color scale, with blue representing hard tissue and red representing soft tissue. The strain ratio was determined by comparing the tumor’s strain to that of adjacent normal tissue at a similar depth. In SWE, quantitative parameters such as mean, minimum, and maximum elastic moduli (kPa) were measured within the ROI. The elastic heterogeneity index was calculated as the standard deviation of the elastic modulus divided by the mean value.

All elastography images were analyzed independently by two radiologists who were blinded to the clinical information and final pathological diagnosis. In cases of discrepancy, a consensus was reached through discussion with a third senior radiologist.

Histopathological analysis

All surgical specimens were analyzed by two experienced pathologists who were unaware of the imaging findings. The diagnosis of GIST was verified through histological examination and immunohistochemical staining for cluster of differentiation 117 and discovered on GIST 1. Risk stratification followed the modified National Institutes of Health (NIH) criteria, considering tumor size, mitotic count, and primary tumor site. Tumors were categorized as very low, low, intermediate, or high risk. Low- and very low-risk tumors were considered benign, while intermediate- and high-risk tumors were classified as malignant in this study.

Statistical analyses

Statistical analyses were conducted using SPSS software (version 26.0; IBM Corporation, Armonk, NY, United States). The normality of continuous variables was assessed with the Shapiro-Wilk test. Continuous variables are presented as the mean ± SD or median (interquartile range), as appropriate. Categorical variables are reported as frequencies and percentages. Differences in elastography parameters between benign and malignant GISTs were compared using the Student’s t-test or the Mann-Whitney U test, as appropriate. The diagnostic performance of the elastography parameters was assessed using receiver operating characteristic (ROC) curve analysis, calculating the area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value. The optimal cut-off values were determined using the Youden index. Interobserver agreement was evaluated using intraclass correlation coefficients (ICCs) for continuous variables and Cohen’s kappa for categorical variables. Statistical significance was set at P < 0.05.

Sample size calculation was conducted using data from prior studies, with an expected AUC of 0.85, a null hypothesis value of 0.5, a level of 0.05, and b level of 0.10. The calculated minimum sample size was 82 patients; however, 100 patients were recruited to accommodate possible dropouts and incomplete data.

RESULTS

Patient and tumor characteristics

Of the 128 patients initially screened, 100 patients (mean age 62.3 ± 11.4 years, range 28-85 years) with 103 GISTs met the inclusion criteria and were enrolled in the final analysis. Three patients presented with two distinct lesions. The study population comprised 57 males and 43 females. According to the modified NIH criteria, 45 tumors (43.7%) were classified as benign (19 very low risk and 26 low risk), and 58 tumors (56.3%) were classified as malignant (31 intermediate risk and 27 high risk). The demographic and clinical characteristics of the study population are summarized in Table 1.

Table 1 Demographic and clinical characteristics of the study population, mean ± SD/n (%).

Characteristic	All patients (n = 100)	Benign GIST (n = 43)	Malignant GIST (n = 57)	P value
Age (years)	62.3 ± 11.4	60.8 ± 12.1	63.5 ± 10.8	0.235
Sex				0.412
Male	57 (57.0)	23 (53.5)	34 (59.6)
Female	43 (43.0)	20 (46.5)	23 (40.4)
Tumor location				0.028
Stomach	65 (63.1)	33 (73.3)	32 (55.2)
Small intestine	28 (27.2)	8 (17.8)	20 (34.5)
Other	10 (9.7)	4 (8.9)	6 (10.3)
Tumor size (cm)	4.8 ± 2.9	3.2 ± 1.4	6.1 ± 3.1	< 0.001
Presenting symptoms				0.156
Asymptomatic	42 (42.0)	22 (51.2)	20 (35.1)
Abdominal pain	35 (35.0)	13 (30.2)	22 (38.6)
GI bleeding	15 (15.0)	5 (11.6)	10 (17.5)
Other	8 (8.0)	3 (7.0)	5 (8.8)

GIST: Gastrointestinal stromal tumor.

Conventional ultrasound findings

Conventional ultrasound characteristics significantly differed between benign and malignant GISTs. Malignant GISTs were more likely to exhibit irregular shapes (56.9% vs 15.6%; P < 0.001), indistinct boundaries (32.8% vs 8.9%; P = 0.002), heterogeneous echo patterns (62.1% vs 20.0%; P < 0.001), and increased vascularity (grade 2-3: 67.2% vs 22.2%; P < 0.001) compared to benign GISTs. Table 2 provides a detailed overview of sonographic features.

Table 2 Conventional ultrasound features of benign and malignant gastrointestinal stromal tumors, n (%).

Feature	Benign GIST (n = 45)	Malignant GIST (n = 58)	P value
Shape			< 0.001
Regular	38 (84.4)	25 (43.1)
Irregular	7 (15.6)	33 (56.9)
Boundary			0.002
Clear	41 (91.1)	39 (67.2)
Unclear	4 (8.9)	19 (32.8)
Echo pattern			< 0.001
Homogeneous	36 (80.0)	22 (37.9)
Heterogeneous	9 (20.0)	36 (62.1)
Vascularity			< 0.001
Grade 0-1	35 (77.8)	19 (32.8)
Grade 2-3	10 (22.2)	39 (67.2)

GIST: Gastrointestinal stromal tumor.

Elastography findings

SE results: The qualitative SE patterns exhibited notable distinctions between benign and malignant GISTs. Malignant GISTs predominantly exhibited score 4-5 patterns (60.3%), while benign GISTs mostly displayed score 1-2 patterns (73.3%). The strain ratio was significantly higher in malignant tumors compared to benign ones (4.82 ± 1.73 vs 2.31 ± 0.89; P < 0.001). Malignant GISTs also demonstrated more heterogeneous strain patterns (65.5% vs 15.6%; P < 0.001). The detailed SE findings are presented in Table 3.

Table 3 Strain elastography parameters for benign and malignant gastrointestinal stromal tumors, mean ± SD/n (%).

Parameter	Benign GIST (n = 45)	Malignant GIST (n = 58)	P value
Elastographic pattern			< 0.001
Score 1-2	33 (73.3)	8 (13.8)
Score 3	9 (20.0)	15 (25.9)
Score 4-5	3 (6.7)	35 (60.3)
Strain ratio	2.31 ± 0.89	4.82 ± 1.73	< 0.001
Strain pattern			< 0.001
Homogeneous	38 (84.4)	20 (34.5)
Heterogeneous	7 (15.6)	38 (65.5)

GIST: Gastrointestinal stromal tumor.

SWE results: The average elastic modulus was notably higher in malignant GISTs compared to benign ones (45.6 ± 15.8 kPa vs 21.3 ± 8.4 kPa; P < 0.001). Likewise, both the maximum and minimum elastic modulus values were significantly greater in the malignant tumors (P < 0.001). There were also significant differences in the elastic heterogeneity index between the two groups (0.42 ± 0.15 vs 0.18 ± 0.07; P < 0.001). Detailed SWE parameters are provided in Table 4.

Table 4 Shear-wave elastography parameters for benign and malignant gastrointestinal stromal tumors, mean ± SD.

Parameter	Benign GIST (n = 45)	Malignant GIST (n = 58)	P value
Mean elastic modulus (kPa)	21.3 ± 8.4	45.6 ± 15.8	< 0.001
Maximum elastic modulus (kPa)	28.7 ± 10.2	62.4 ± 20.3	< 0.001
Minimum elastic modulus (kPa)	15.2 ± 6.8	31.8 ± 12.4	< 0.001
Heterogeneity index	0.18 ± 0.07	0.42 ± 0.15	< 0.001

GIST: Gastrointestinal stromal tumor.

Diagnostic performance

ROC curve analysis revealed excellent diagnostic performance for both SE and SWE parameters. The mean elastic modulus exhibited the highest diagnostic accuracy with an AUC of 0.918 (95% confidence interval [CI]: 0.865-0.971), followed by the strain ratio with an AUC of 0.892 (95%CI: 0.831-0.953) and heterogeneity index with an AUC of 0.876 (95%CI: 0.810-0.942). The optimal cutoff values and corresponding diagnostic indices are listed in Table 5.

Table 5 Diagnostic performance of elastography parameters.

Parameter	AUC (95%CI)	Cutoff value	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
Strain ratio	0.892 (0.831-0.953)	3.45	84.5	86.7	89.1	81.2
Mean elastic modulus	0.918 (0.865-0.971)	32.5	87.9	88.9	91.1	85.1
Heterogeneity index	0.876 (0.810-0.942)	0.28	82.8	84.4	87.3	79.2

AUC: Area under the curve; CI: Confidence interval; NPV: Negative predictive value; PPV: Positive predictive value.

Interobserver agreement

The interobserver agreement was excellent for both SE and SWE measurements. In terms of SE pattern classification, the kappa value was 0.82 (95%CI: 0.73-0.91). Regarding strain ratio measurements, the ICC was 0.88 (95%CI: 0.82-0.94). The ICC values for the SWE parameters ranged from 0.85 to 0.93, demonstrating excellent reproducibility.

DISCUSSION

Accurate preoperative differentiation of benign and malignant GISTs remains a crucial clinical challenge that significantly influences treatment strategies and patient outcomes. This prospective study demonstrated that ultrasound elastography, particularly when combined with strain and SW techniques, offers valuable diagnostic insights for risk stratification of GISTs. Our findings indicate that both qualitative and quantitative elastographic parameters can distinguish between benign and malignant GISTs effectively, demonstrating high diagnostic precision.

The excellent diagnostic performance of elastography in our research can be credited to its capability to identify variations in tissue stiffness linked to pathological alterations. Recent research indicates that elevated tissue stiffness in malignant GISTs correlates with increased cellularity, nuclear atypia, and heightened mitotic activity[21]. These results are consistent with a 2023 meta-analysis that disclosed pooled sensitivity and specificity values of 86% and 89%, respectively, for elastography in GIST diagnosis[22]. Our findings showcased even higher diagnostic accuracy, potentially attributed to the combined use of both SE and SWE methodologies, along with standardized measurement protocols.

The strain ratio values in our study exhibited significant differences between benign and malignant GISTs, with an optimal cutoff value of 3.45, resulting in high sensitivity and specificity. This observation corresponds well with recent studies that have documented comparable cutoff values ranging from 3.1 to 3.8[23]. The uniformity observed across various studies indicates that the strain ratio may function as a dependable quantitative parameter for GIST risk assessment. Furthermore, our findings demonstrated outstanding interobserver agreement for strain ratio measurements (ICC = 0.88), alleviating prior worries about the operator dependency of SE techniques.

Regarding SWE parameters, our study revealed that the mean elastic modulus exhibited the highest diagnostic accuracy (AUC = 0.918) compared to other elastography parameters. The identified optimal threshold value of 32.5 kPa for discriminating between malignant and benign GISTs aligns with recent findings from a multicenter study that indicated a threshold value of 31.8 kPa[24]. The high reproducibility of SWE measurements in our investigation (ICC range: 0.85-0.93) highlights its potential utility as a standardized quantitative tool for evaluating GISTs.

The heterogeneity index obtained from SWE measurements proved to be a valuable parameter in our study. This discovery is especially important as tissue heterogeneity has been demonstrated to be associated with tumor grade and biological behavior in recent molecular imaging studies[25]. The elevated heterogeneity index identified in malignant GISTs (0.42 ± 0.15 vs 0.18 ± 0.07) mirrors the intrinsic biological diversity of these tumors, which frequently display regions of differing cellular density, necrosis, and hemorrhage[26].

Our study also showed that traditional ultrasound features, when combined with elastography parameters, could enhance diagnostic accuracy. This multiparametric approach is backed by recent literature indicating that incorporating multiple imaging biomarkers offers more reliable risk stratification[27]. The notable variances in tumor shape, boundary delineation, and vascularity between benign and malignant GISTs complement elastography results and offer a more thorough evaluation framework.

The correlation between elastographic parameters and histopathological features observed in our study provides biological validation for the use of tissue elasticity as a biomarker of tumor aggressiveness. Recent studies have shown that increased tissue stiffness in GISTs is associated with a higher expression of genes involved in extracellular matrix remodeling and mechanical signal transduction[28]. These molecular findings supported the biological basis of elastography-based risk stratification.

When comparing ultrasound elastography with established modalities such as endoscopic ultrasound (EUS) and contrast-enhanced CT, each approach presents unique advantages. EUS offers high resolution for small submucosal lesions but is invasive and reliant on the operator. Contrast-enhanced CT provides detailed anatomical information but has limited capabilities for soft tissue characterization. Our findings indicate that ultrasound elastography can offer additional insights into tissue stiffness that are not provided by conventional modalities, potentially improving the overall diagnostic approach when used in combination. This is particularly beneficial in situations where conventional imaging results are inconclusive or when patients cannot undergo invasive procedures or contrast-enhanced scans.

The incorporation of elastography into existing diagnostic pathways has the potential to enhance the clinical strategy for GIST management. For instance, patients with lesions showing low elastic modulus values (< 32.5 kPa) and strain ratios (< 3.45) might be suitable for surveillance rather than immediate invasive interventions. Conversely, lesions exhibiting high stiffness require prompt surgical action or targeted biopsy. Additionally, in instances of heterogeneous tumors, elastography can direct sampling towards firmer areas, which are more indicative of higher-grade regions, potentially enhancing biopsy effectiveness and diagnostic precision.

Technical factors and potential limitations should be considered when interpreting these results. The accuracy of elastographic measurements can be influenced by factors such as tumor location, size, and depth. Our study mainly focused on gastric and small intestinal GISTs; thus, these findings may not be directly applicable to GISTs in other locations. Moreover, very large tumors (> 10 cm) present challenges for comprehensive elastography assessment due to the limited penetration of the ultrasound beam and the difficulty in obtaining reliable reference tissues at comparable depths. In the case of deep-seated lesions, particularly those located posteriorly or obscured by other organs, signal attenuation may necessitate adjustments to the technique and its interpretation.

Patient-related factors played a role in affecting the quality of measurements. Respiratory motion posed a significant challenge, particularly for lesions close to the diaphragm or upper abdomen. To mitigate this issue, we utilized breath-hold techniques during image acquisition. However, this approach was not always viable for elderly patients or individuals with respiratory ailments. Interference from intestinal gas sometimes compromises image quality, particularly for small intestinal lesions, necessitating patient repositioning or repeated examinations to achieve optimal images. These technical obstacles underscore the significance of skilled operators and standardized protocols in elastography implementation.

Standardization of measurement techniques and analysis methods is essential for the broad adoption of elastography in clinical settings. Our study utilized rigorous measurement protocols and quality control measures, leading to high reproducibility. Recent technological advancements, such as artificial intelligence-based image analysis and standardized reporting systems, have the potential to enhance the consistency and clinical relevance of elastography measurements[29].

These findings have significant clinical implications. The high diagnostic accuracy and noninvasive nature of ultrasound elastography make it a valuable tool for the preoperative risk stratification of GISTs. This information can guide clinical decision-making regarding the necessity of preoperative biopsy, surgical approaches, and consideration of neoadjuvant therapy[30]. The quantitative nature of elastographic parameters also offers objective criteria for risk assessment, potentially reducing subjectivity in tumor evaluation.

The real-time capability and cost-effectiveness of ultrasound elastography provide additional advantages compared to other advanced imaging modalities. Recent economic analyses have shown that integrating elastography into the diagnostic algorithm for GISTs can be cost-effective by decreasing the necessity for unnecessary biopsies and optimizing treatment planning[31]. Furthermore, the excellent reproducibility demonstrated in our study supports its utilization in both the initial diagnosis and follow-up assessment.

CONCLUSION

This study showed that ultrasound elastography, particularly when combining strain and shear-wave techniques, accurately and consistently distinguishes between benign and malignant GISTs. The quantitative parameters obtained from elastography measurements exhibited excellent diagnostic performance and a strong correlation with histopathological features. These findings support the integration of elastography into the standard diagnostic process for patients with suspected GISTs, potentially enhancing risk assessment and treatment strategies.