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  • Review Article
  • OPEN ACCESS

The Synergistic Role of Intraoperative Ultrasound and Contrast-Enhanced Ultrasound in Brain Tumor Surgery: A Review of Technical Advances and Clinical Applications

  • Ying He1,*,
  • Danni Zhu1,
  • Yuwei Zeng1,
  • Jienv Lou1 and
  • Dan Mao1
 Author information 

Abstract

Brain tumors represent a common class of life-threatening neoplastic conditions. The core objective of neurosurgery is to achieve maximal safe resection of the tumor while preserving the patient's neurological function. Intraoperative ultrasound (IOUS) assists surgeons in achieving complete lesion removal, helping to avoid insufficient resection or excessive excision of normal areas, thereby reducing surgical morbidity. Contrast-enhanced ultrasound (CEUS) imaging mode, through harmonic imaging, enables more precise localization of lesions and intracranial structures. This review focuses on two main aspects: 1. The evolution of intraoperative ultrasound in brain tumor surgery, beginning with two-dimensional ultrasound and integrating other techniques including ultrasound elastography, color Doppler flow imaging (CDFI), microvisual flow imaging (MFI), contrast-enhanced ultrasound (CEUS), artificial intelligence, and so on. It specifically emphasizes the application of contrast-enhanced ultrasound in cranial tumor surgery; 2. The applications in cranial tumor surgery and prognostic evaluation, encompassing precise resection guided by IOUS and CEUS, identification of residual tumor, visualization and protection of vascular structures, hemodynamic monitoring of functional areas, and differential diagnosis between tumor boundaries and the surrounding peritumoral edema zone. This review systematically presents the principles, clinical applications, and synergistic value of IOUS and CEUS in brain tumor surgery, summarizes the diagnostic performance of various ultrasound modalities, and addresses current limitations and future directions, offering neurosurgeons a theoretical and practical framework for optimizing intraoperative ultrasound guidance.

Keywords

intraoperative ultrasound, contrast-enhanced ultrasound, brain tumor, precision resection, multimodal imaging

Introduction

Brain tumors are prevalent and life-threatening, with approximately 308,000 new cases and 251,000 deaths worldwide in 2020. Their infiltrative growth and indistinct boundaries pose significant surgical challenges.1,2 The paramount objective of neurosurgery lies in achieving maximal safe resection while preserving neurological function.

Intraoperative ultrasound (ioUS) has played a pivotal role in real-time precise localization of intracranial lesions since its introduction to neurosurgery in the 1980s, facilitated by rapid advancements in ultrasonography. It enables surgeons to achieve complete lesion resection while avoiding incomplete removal or excessive excision of normal areas, thereby reducing iatrogenic injury.2 Recent integration of technologies such as elastography, color Doppler flow imaging, microvascular flow imaging, and artificial intelligence has expanded ioUS capabilities beyond anatomical visualization to include tissue stiffness evaluation and hemodynamic assessment.3

Despite advantages like procedural simplicity, cost-effectiveness, and radiation-free operation, conventional ioUS exhibits limitations in: Residual tumor detection (particularly with isoechoic lesions), Vascular structure discrimination, Demarcation of tumor boundaries from surrounding edema.2 Additionally, brain shift—caused by intracranial pressure changes or focal resection—compromises anatomical landmark identification and lesion localization during surgery.4

The contrast-enhanced ultrasound (CEUS) imaging mode significantly enhances the sensitivity of ultrasound in detecting low-velocity blood flow through harmonic imaging, enabling more precise localization of lesions and intracranial structures. It provides comprehensive visualization of the entire vascular network, offering anatomical information, tumor blood perfusion characteristics, and adjacent vessel details, thereby assisting surgeons in intraoperative tumor boundary assessment and tumor grading.5-7 The application of ultrasound in neurosurgery continues to advance, and currently, multiple ultrasound imaging techniques—including two-dimensional grayscale ultrasound, ultrasound elastography, color Doppler flow imaging, microvascular flow imaging, contrast-enhanced ultrasound, artificial intelligence, and navigated ultrasound—can be used in real time during surgery, making the resection of brain tumors more precise, thorough, safe, and effective.7,8

In summary, despite significant advances of IOUS and CEUS in brain tumor surgery, most existing studies focus on validating single techniques, with limited systematic synthesis of multimodal synergies. Accordingly, this review aims to: (1) present the principles and applications of IOUS and CEUS in brain tumor surgery; (2) summarize the diagnostic performance of different ultrasound modalities for boundary delineation, residual detection, vascular preservation, and edema differentiation; and (3) identify current limitations and future directions, offering a theoretical and practical framework for intraoperative image‑guided precision neurosurgery.

I. Evolving Ultrasound Technology in Brain Tumor Surgery: Synergistic Complementarity of IOUS and CEUS

1. Intraoperative Ultrasound (ioUS)

Since its introduction into neurosurgery in the 1980s, intraoperative ultrasound has undergone a developmental trajectory from low-frequency, low-resolution imaging toward high-frequency, high-resolution imaging. In the early stages of ultrasound technology development, two-dimensional grayscale ultrasound predominated; during this period, image quality was suboptimal, resolution was relatively low, and artifacts were prominent.4,5 This technology was primarily employed for deep lesion localization and puncture guidance; however, due to limitations in image quality, it struggled to clearly delineate detailed tumor characteristics.

With continuous advancements in probe technology, the application of high-frequency linear array probes (e.g.,7-15 MHz) significantly enhanced spatial resolution, facilitating more precise observation of brain tissue architecture, tumor boundaries, morphology, internal echogenicity patterns, and their relationships with surrounding structures.2 This proved particularly valuable for intraoperative localization of infiltrative tumors such as gliomas.6 During intraoperative ultrasound procedures, two-dimensional ultrasound is first utilized, followed by the integration of other ultrasound techniques to acquire more comprehensive multimodal information encompassing anatomical and functional imaging characteristics.5

In recent years, the integration of technologies such as elastography and Doppler flow imaging has further expanded the capabilities of ioUS, enabling it to provide not only anatomical information but also insights into tissue stiffness and hemodynamic status.3,9 Ultrasound elastography, as an emerging non-invasive imaging technique, facilitates tumor identification through quantitative or semi-quantitative assessment of tissue stiffness differences.10-12 Currently, elastography techniques commonly employed in brain tumor surgery include strain elastography and shear wave elastography.13,14 The former, a quasi-static strain imaging modality, generates tissue strain by applying stress to the region of interest, allowing assessment of tissue softness or hardness based on ultrasound echo signals; the latter, a dynamic elastography technique, utilizes color-coded mapping for differentiation and offers superior reproducibility and contrast compared with strain elastography.

In the field of cranial ultrasound research and application, Chauvet et al.15 demonstrated in their 2016 study that differences in stiffness exist between low-grade and high-grade gliomas, as well as between low-grade gliomas and normal brain tissue. In the study by Wang et al. 16, shear wave elastography was employed alone during brain tumor surgery, with postoperative magnetic resonance imaging serving as the gold standard for assessing residual tumor detection accuracy. The study found that SWE yielded a Kappa value of 0.714 with MRI, comparable to the 0.717 achieved by two-dimensional ultrasound, suggesting comparable performance in identifying residual tumor. Cepeda et al.17 applied strain elastography to 102 patients with brain tumors, calculating mean tissue elasticity values through semi-quantitative analysis. They identified significant differences in elasticity values among tumors of different pathological types (P < 0.001). A substantial body of research,14,15,1718 indicates that elastography provides valuable supplementary information for surgeons during cranial tumor procedures.

Color Doppler flow imaging (CDFI) utilizes Doppler technology to visualize blood flow direction and measure flow velocity. In the context of brain tumor surgery, it primarily encompasses color Doppler ultrasound and power Doppler ultrasound.19,20 In imaging results, red typically indicates blood flow moving toward the transducer, whereas blue denotes flow moving away from the transducer.5 The optimal timing for this technique is after craniotomy but before dural incision. This technology provides comprehensive information regarding tumor vascularity,3 including the relationship between major vessels and the tumor, tumor vessel caliber, tumor feeding arteries, and tumor-draining veins. Such information assists surgeons in more precisely determining surgical location and depth while avoiding injury to critical vessels. However, color Doppler is notably susceptible to scanning angle effects,4,19 and image quality degrades with deeper target locations. Large sampling windows may introduce artifacts; while it demonstrates advantages in visualizing larger vessels, its capacity for microvascular visualization is limited.21 In contrast, power Doppler 2 is unaffected by flow angle and direction, offering greater sensitivity in detecting small-caliber and deep-seated vessels. Nevertheless, power Doppler does not provide information on flow direction. Previous studies have demonstrated that Doppler ultrasound assessment of critical tumor and peritumoral vessels reduces intraoperative vascular injury and decreases postoperative complications.3,19

Microvascular flow imaging (MFI) and Superb Microvascular Imaging (SMI), as emerging Doppler imaging technique,3,21-25 effectively suppresses tissue motion artifacts, offers high resolution, and preserves microvascular blood flow signals. Its capability in displaying low-velocity blood flow surpasses that of conventional color and power Doppler. The terminological distinction primarily reflects vendor-specific nomenclature rather than fundamental technical differences.3,26 However, reports on its application in cranial surgery remain relatively scarce.

In 2017, Mami et al.21 first applied MFI in cranial surgery, describing the MFI characteristics of various brain tumors and proposing that MFI could be used to differentiate tumors from peritumoral tissues. In 2023, the same team 26 applied MFI in 20 patients diagnosed with brain tumors. Their findings revealed that when MFI was performed alone, it was difficult to clearly visualize blood flow in numerous small vessels; however, after the administration of contrast agent, repeated MFI examinations achieved clear visualization. Consequently, they concluded that contrast agent injection enhances the imaging performance of MFI, enabling clear depiction of tumor microvascular architecture, and that analysis of vessel density and contrast agent arrival time allows assessment of tumor blood supply characteristics.

In 2024, Cai et al.22 demonstrated that superb microvascular imaging (SMI) significantly outperformed grayscale ultrasound in improving the delineation of high-grade glioma (HGG) boundaries (P = 0.033). This study directly compared the clinical value of CDFI and SMI, confirming the advantages of SMI as an advanced technology over CDFI. In 2025, Dixon et al.27 employed SMI to acquire tumor microvascular images and conducted both qualitative and quantitative analyses, concluding that HGG exhibits greater vascular complexity and disorganization, thereby establishing SMI as a novel intraoperative real-time tool for glioma grading.

Currently, MFI still presents several limitations, including restricted visualization of deep-seated lesions and a lack of standardized quantitative parameters.4 Future applications in cranial surgery are expected to involve its combination with functional techniques such as CEUS to provide surgeons with more comprehensive information.

Navigated intraoperative ultrasound (nioUS) integrates ultrasound probes with neuronavigation systems to achieve real-time imaging during surgery, which can be compared with preoperative magnetic resonance imaging (MRI). This approach effectively addresses the localization challenges posed by brain shift that affect conventional ultrasound. This technology combines the real-time convenience of ultrasound with the spatial localization advantages of navigation.28,29 In 2025, a study by Cepeda et al.30 incorporated data from six international centers, encompassing 197 glioma patients, demonstrating that navigated intraoperative ultrasound enabled image co-registration with preoperative MRI. Concurrently, the team employed the YOLO11 architecture31on,1732 intraoperative ultrasound images, achieving outstanding performance with a mean average precision (mAP)@50 of 0.95 and mAP@50-95 of 0.65, at a processing speed of 34 frames per second. Neurosurgeons confirmed that the system integrated seamlessly into the surgical workflow, providing real-time, accurate prediction and delineation of tumor regions. These findings validate the clinical feasibility of artificial intelligence-assisted intraoperative ultrasound. Vahdani et al.32 proposed a novel deep learning architecture named U-ConvNext, specifically designed for intraoperative ultrasound segmentation of low-grade gliomas. This study was the first to introduce uncertainty quantification into intraoperative ultrasound segmentation, providing a reliability assessment for AI-assisted decision-making and holding significant clinical translational value. Zeineldin et al.33 developed NeuroIGN, an open-source, multimodal, explainable AI neuronavigation system that seamlessly fuses preoperative MRI with real-time intraoperative ultrasound, offering intuitive decision support for intraoperative navigation. The advancement of navigated intraoperative ultrasound and artificial intelligence signifies the transition of intraoperative ultrasound from an auxiliary localization tool to a multifunctional intraoperative navigation platform. It is anticipated that in the near future, this technology will become a cost-effective and precise intraoperative guidance tool in precision neurosurgery.

Despite the promising performance of YOLO1131, U-ConvNext32, and NeuroIGN33 in intraoperative ultrasound image analysis, several barriers hinder their clinical adoption, namely the scarcity of large-scale, standardized, multi-center annotated datasets, limited cross-device and cross-scenario generalizability, and high computational requirements for real-time processing.4,31

2. Contrast-Enhanced Ultrasound (CEUS)

Contrast-enhanced ultrasound (CEUS) involves intravenous administration of ultrasound contrast agents (primarily gas-filled phospholipid microbubbles, such as those containing sulfur hexafluoride, and perflutren lipid microspheres ), which significantly enhances blood contrast and enables dynamic visualization of tumor microvascular kinetics.7,34 These microbubbles exhibit excellent biocompatibility, remain confined to the vascular space without extravasation, undergo no metabolism in vivo, and are eliminated via the pulmonary circulation, offering a high safety profile with no nephrotoxicity or hepatotoxicity.4,35 Absolute contraindications include known hypersensitivity to sulfur hexafluoride or perflutren components. Caution is advised in patients with severe cardiopulmonary disease or the presence of right‑to‑left shunts, as microbubbles may enter the systemic circulation.35 The underlying principle is that microbubbles undergo nonlinear oscillation under ultrasound exposure, generating harmonic signals that facilitate high-contrast, high-resolution imaging under low mechanical index conditions.34 Consequently, CEUS provides clear visualization of intravascular blood flow distribution unaffected by scanning angle, enables real-time dynamic display of comprehensive vascular information within brain tumor tissues—including anatomical details, tumor blood perfusion characteristics, and adjacent vessel information—thereby assisting surgeons in intraoperative tumor boundary assessment and tumor grading.5,35

In clinical practice, administration and dosage typically consist of an intravenous bolus injection of 1.2–2.4 mL of contrast agent, followed by a 5–10 mL saline flush. Repeat administrations (usually 2–3 times) are safe.5,35 For perfusion analysis, continuous infusion is recommended.7 The timing of CEUS imaging should be performed at three key time points: (1) after dural opening (baseline), (2) during resection (residual tumor detection), and (3) after resection (final check). Each acquisition should last 60–120 seconds to capture the arterial phase (10–30 s), parenchymal phase (30–60 s), and venous phase (60–120 s).4,35 A low mechanical index (<0.2) should be used to preserve microbubble integrity.35

The application of CEUS in cranial settings dates back to 1993, when Bogdahn first utilized it for cerebral vascular examination.36 To date, CEUS has achieved significant advancements in cranial surgery, diagnostics, and therapeutics,37 with applications including glioma grading,38 brain tumor surgery,3 diagnosis and evaluation of cerebrovascular diseases,39,40 and even microbubble-mediated enhancement of targeted therapeutic efficacy.41,42 In brain tumor surgery, CEUS has been employed to differentiate residual lesions, protect vascular structures, and distinguish tumor boundaries from peritumoral edema.2

The study by Wang et al.16 demonstrated that CEUS exhibited the highest diagnostic concordance with MRI, outperforming B-mode, microvascular flow imaging, and shear wave elastography, strongly supporting CEUS as the preferred technique for intraoperative assessment of residual lesions. CEUS enhancement patterns correlate with tumor pathology and angiogenic characteristics. Cheng et al.38 confirmed that high-grade gliomas (HGG) typically display rapid, heterogeneous “ring-like” enhancement—with non-enhancing central necrotic areas and highly enhancing peripheral viable tumor tissue—reflecting the pathological features of dense microvasculature at the tumor periphery and central ischemia-necrosis. Low-grade gliomas (LGG) manifest as slow, homogeneous, or mild enhancement, with some tumors exhibiting no enhancement due to low microvascular density, suggesting that CEUS may have limitations in LGG identification, necessitating multimodal imaging approaches. Meningiomas, as highly vascular tumors, commonly exhibit homogeneous marked enhancement on CEUS, with sharp tumor–brain interfaces.5 CEUS features of metastatic tumors are influenced by the vascular characteristics of their primaries, with most hypervascular metastases demonstrating rapid marked enhancement and relatively well-defined margins.43

Notably, although the intact blood–brain barrier (BBB) typically restricts the entry of macromolecules into brain parenchyma, malignant brain tumor regions often exhibit BBB disruption, allowing microbubbles to accumulate within tumor vasculature and enhance visualization, whereas normal brain tissue with intact BBB remains non-enhancing, creating a natural contrast.35 Furthermore, microbubbles can serve as therapeutic vehicles; upon ultrasound triggering, they can transiently open the BBB, facilitating targeted delivery of chemotherapeutic agents, antibodies, and immunomodulators, thereby enabling theranostic integration.35,41,42 Thus, CEUS not only addresses the limitations of conventional ioUS in perfusion quantification and boundary identification but also expands its potential for precision therapeutic applications.

Summary

Conventional ultrasound offers multiple advantages in brain tumor surgery, including ease of operation, low cost, and excellent repeatability. However, it exhibits significant limitations in identifying residual tumors, delineating vascular structures, distinguishing tumor boundaries from peritumoral edema, and assessing the completeness of postoperative resection, particularly when tumor echogenicity differences are subtle, which may lead to missed residual lesions.6 Furthermore, conventional grayscale ultrasound cannot accurately assess tumor microcirculatory perfusion status, creating an information gap for intraoperative ultrasound‑guided precise resection.4,7 CEUS precisely fills this gap. By intravenously administering pure blood‑pool microbubble contrast agents, CEUS enables dynamic visualization of tumor microvascular perfusion patterns.7,35 Compared to the “no or delayed low enhancement”observed in normal brain tissue and edematous zones, highly vascularized tumor tissues exhibit characteristic“early rapid enhancement"35,38. This significant functional contrast establishes CEUS as an ideal tool for delineating tumor infiltrative margins, forming direct complementarity with the structural imaging provided by IOUS.35(Table.1)

II. Clinical Synergy of IOUS and CEUS

(Table.2)

1. Applications of IOUS and CEUS in Different Brain Tumor Subgroups

Brain tumor subgroups, including pediatric brain tumor, brain metastases, and skull base lesions, demonstrate divergent pathological and anatomical characteristics, necessitating tailored intraoperative ultrasound (IOUS) and contrast-enhanced ultrasound (CEUS) strategies to optimize resection accuracy and functional preservation.

Pediatric low-grade gliomas (LGGs) represent the most common brain tumors in children. However, their echogenicity differences from normal brain tissue are often indistinct, posing challenges for intraoperative boundary identification. Mattei et al.44 demonstrated that both B-mode and contrast-enhanced ultrasound (CEUS) facilitate the delineation of LGG boundaries and the characterization of tumor vascularity, thereby enhancing the safety of radical resection. A study encompassing 45 pediatric supratentorial lesions reported that intraoperative ultrasound (IOUS) ensures reliable real-time imaging during surgery for space-occupying brain lesions.45 Preoperative IOUS enabled accurate lesion localization; in deeply seated lesions, the addition of CEUS improved the visualization of tumor vascular patterns and assisted in surgical route planning. Notably, approximately 30% of cases prompted a change in surgical strategy due to the intraoperative detection of residual tumor. A further study in 2024 confirmed that navigated IOUS achieves a sensitivity of 100% and a specificity of 84.6% for the detection of residual tumor, demonstrating reliable accuracy compared with intraoperative magnetic resonance imaging (iMRI).29

Brain metastases represent the most common intracranial tumors in adults, and the surgical goal is to achieve gross total resection (GTR) to improve survival outcomes. Cheng et al.43 observed that on conventional ultrasound, metastatic tumors frequently presented with well-defined margins (32/46, 69.6%), hypervascularity (35/46, 76.1%), and severe peritumoral edema (33/46, 71.7%). During contrast-enhanced ultrasound (CEUS), brain metastases (BMS) typically exhibit a "rapid, heterogeneous, high-enhancement" pattern with delayed washout, and CEUS can assist in delineating tumor boundaries. A 2025 study further quantified the value of intraoperative ultrasound (IOUS).46 In this study, 80% of IOUS-guided cases achieved a GTR of >96%, which was significantly higher than that of the conventional neuronavigation group (42.86%, P = 0.008). IOUS significantly increased the odds of achieving GTR (OR = 5.33, P= 0.011). A larger tumor volume reduced the likelihood of GTR (OR = 0.469, P = 0.025).

Skull base tumors pose a major surgical challenge due to their proximity to critical vessels and nerves, making intraoperative identification and preservation of vascular structures paramount. Prada et al.5 applied navigated contrast-enhanced ultrasound (CEUS) in 18 patients with skull base tumors (including 10 meningiomas,3 craniopharyngiomas,2 giant pituitary adenomas,1 posterior fossa epidermoid cyst, and 2 dermoid cysts). This technique enabled en bloc visualization of both high- and low-flow vessels, clearly delineating the three-dimensional spatial relationship between the tumor and major vessels, thereby facilitating the avoidance of perforating arteries and reducing the risk of vascular injury.

2. Real-Time Image-Guided Precise Resection: Complementarity of Conventional IOUS and CEUS

Achieving maximal safe resection is a critical goal for improving patient outcomes in brain tumor surgery. Intraoperative ultrasound (IOUS), as a real-time, radiation-free, and cost-effective imaging modality, has been widely employed to assist intraoperative localization and boundary delineation of brain tumors.2 Contrast-enhanced ultrasound (CEUS) not only enhances the contrast between tumors and normal brain tissue but also provides information on tumor angiogenesis, thereby supporting more precise resection decisions.2 On CEUS, tumors typically exhibit early rapid enhancement and late rapid washout, whereas surrounding edematous brain tissue, characterized by an intact blood–brain barrier and low microvascular density, often shows no enhancement or delayed low enhancement.16 This difference in perfusion enables CEUS to accurately delineate tumor boundaries, with its accuracy in assessing residual lesions demonstrating high concordance with postoperative MRI (Kappa = 0.892).16

In clinical practice, conventional IOUS and CEUS form a strong complementary relationship: IOUS provides real-time anatomical localization and surgical pathway planning, while CEUS provides information on tumor blood supply and perfusion boundaries. Their combined application enables multidimensional tumor assessment. The study by Wang et al.16 demonstrated that the gross total resection rate under CEUS guidance reached 82%, significantly higher than that of the conventional IOUS group (48%). Furthermore, CEUS allows intraoperative real-time assessment of tumor angiogenic activity and pathological grading through quantitative parameters (peak intensity, time to peak) and their correlation with microvessel density (MVD).47,38 For high-grade gliomas, the ring-enhancing region visualized by CEUS accurately delineates the boundary of viable tumor tissue, guiding surgeons to achieve maximal resection while preserving critical functional areas.5,47

Moreover, the complementary application of conventional IOUS and CEUS enables real-time navigation during intracranial tumor resection and can be further integrated with artificial intelligence. Combined with preoperative magnetic resonance imaging (MRI) data, this approach helps mitigate intraoperative brain shift and enhances surgical precision.28,29 Artificial intelligence-assisted image interpretation, capable of automatically delineating tumor boundaries,32,33 is advancing neurosurgical procedures toward greater precision and safety.

3. Identification of Residual Tumor Tissue

Timely identification of residual lesions during tumor resection is crucial for improving the gross total resection rate. Studies have shown that in newly diagnosed IDH-wildtype glioblastoma, extensive resection of non-enhancing tumors is associated with better survival outcomes, with smaller postoperative residual volumes correlating with reduced mortality risk.48 Although conventional grayscale ultrasound provides real-time structural information, its ability to detect small residual lesions is limited, particularly when echogenicity differences are subtle, which may lead to missed residual tumors.2

Leveraging its high sensitivity to microcirculatory perfusion, CEUS enables immediate postoperative assessment of whether abnormal enhancement areas exist at the resection cavity margins—such areas often indicate the presence of residual tumor tissue. Because ultrasound contrast agent microbubbles remain confined to the vascular lumen without extravasating into normal brain parenchyma (due to an intact blood–brain barrier), the abnormal enhancement signals visualized by CEUS typically reflect regions of blood–brain barrier disruption, i.e., areas of tumor infiltration.2,35 In contrast, necrotic tissue, postoperative changes, and surrounding edematous brain tissue show no enhancement or delayed low enhancement.35 This unique characteristic gives CEUS a distinct advantage in distinguishing postoperative reactive changes from true residual tumors.

The study by Wang et al.16 directly compared the efficacy of two-dimensional ultrasound mode, microvascular flow imaging (MFI), CEUS, and shear wave elastography (SWE) in assessing the extent of brain tumor resection. The results showed that CEUS exhibited the highest diagnostic concordance with MRI (Kappa = 0.892) and outperformed other ultrasound techniques in detecting residual lesions. The study concluded that CEUS is the preferred technique for intraoperative assessment of residual tumors.

Superb microvascular imaging (SMI) also plays a role in residual tumor identification. The study by Ishikawa et al.26 combined contrast-enhanced SMI (ceSMI) with CEUS and found that analyzing vessel density and contrast agent arrival time enabled a more comprehensive assessment of tumor blood supply status, aiding in the identification of residual lesions.(Table.3).

4. Vascular Structure Identification and Hemodynamic Monitoring of Functional Areas: From Structural Preservation to Functional Conservation

In brain tumor surgery, real-time intraoperative assessment of the anatomical relationships of tumor feeding arteries, draining veins, and adjacent perforating vessels, as well as the planning of safe resection pathways and intraoperative bleeding control, significantly impacts surgical prognosis. Color Doppler flow imaging (CDFI), as a fundamental blood flow imaging technique, can visualize the direction and velocity of blood flow in larger vessels, assisting surgeons in identifying major feeding arteries and draining veins.19 However, CDFI has low sensitivity to low-velocity blood flow and exhibits strong angle dependence, limiting its ability to visualize microvascular structures and thereby restricting its application in fine vascular identification.4 The advent of superb microvascular imaging (SMI) has addressed the limitations of CDFI, enabling clear visualization of microvessels as small as 0.1–0.2 mm in diameter, and has been effectively applied in high-grade glioma surgery.3,22 Intraoperative contrast-enhanced ultrasound (CEUS) further enhances vascular identification. By dynamically displaying tumor blood perfusion through microbubble contrast agents, CEUS can clearly differentiate feeding arteries, draining veins, and normal perforating vessels, playing a crucial role in intraoperative vascular localization for hypervascular tumors such as meningiomas.5,47

Future synergistic use of CDFI, SMI, and CEUS will deliver comprehensive vascular anatomy from macro‑ to micro‑scales. Together with AI‑assisted vessel identification and localization,32,33 this strategy will provide dual protection for achieving maximal safe resection.

5. Differential Diagnosis of Tumor Boundaries and Peritumoral Edema Zones

Accurate differentiation between tumor parenchyma and surrounding vasogenic edema represents a key challenge in brain tumor surgery. Tumor cells often infiltrate surrounding brain tissue along white matter tracts, forming transitional zones mixed with edema, which conventional grayscale ultrasound struggles to distinguish—both tumor tissue and edematous brain tissue may appear hyperechoic, and surgical manipulation and bleeding can further increase the echogenicity of peritumoral tissue, making it difficult to differentiate from tumor invasion using conventional ultrasound.2,4 This can lead neurosurgeons to either under-resect (leaving residual infiltrating tumor) or over-resect (removing normal functional brain tissue), thereby affecting patient prognosis.48

CEUS facilitates the identification of tumor boundaries and peritumoral edema zones by visualizing microvessel density and perfusion patterns.35 The key differentiating features are: tumor tissue exhibits early rapid enhancement and late rapid washout; whereas edematous zones, due to an intact blood–brain barrier and low microvascular density, show no enhancement or delayed low enhancement.16,35 Therefore, combining intraoperative ultrasound with CEUS aids in delineating tumor margins.48 Studies have shown that the intraoperative application of CEUS in glioma surgery enables delineation of tumor boundaries and further differentiation between tumor tissue and brain edema.7 The study by Cheng et al.38 also demonstrated that cranial CEUS can distinguish between tumor and edema and effectively detect postoperative residual brain tumors. The 2017 EFSUMB CEUS guidelines detail the clinical standards for non‑hepatic applications, including urological, vascular, and endocavitary indications. Thanks to its superior blood‑pool imaging and safety, CEUS has also been adopted in neurosurgery to support intraoperative decision‑making.35,49.

Superb microvascular imaging (SMI) also holds significant value in differential diagnosis. The study by Cai et al.22 showed that SMI significantly outperformed grayscale ultrasound in improving the delineation of high-grade glioma boundaries, and the microvascular architecture visualized by SMI can help distinguish the tumor core from surrounding edematous areas. For low-grade gliomas, SMI can reveal sparse microvascular structures within the tumor, whereas edematous zones typically show no distinct blood flow signals.26

Ultrasound elastography provides complementary information from the perspective of tissue stiffness. Tumor tissue, characterized by high cellular density and fibrosis, typically exhibits significantly higher stiffness than edematous brain tissue.13,15 Cepeda et al.17 demonstrated that strain elastography can clearly visualize the stiffness transition zone between tumor and edematous tissue, with significant differences in mean tissue elasticity values among different pathological types (P < 0.001). Shear wave elastography (SWE) enables further quantitative analysis, providing Young’s modulus values and thereby enhancing the objectivity of differential diagnosis.13,15

6. Long-term outcomes: From GTR to survival benefit

Although gross total resection (GTR) is the core metric of intraoperative efficacy, its ultimate value lies in translating into long-term patient survival. Chen et al.50 (2024) demonstrated in a survival analysis of 64 malignant gliomas that the ICEUS group achieved significantly superior overall survival (OS) and progression‑free survival (PFS), with multivariate analysis confirming ICEUS as an independent prognostic factor for both OS and PFS (P < 0.05). A 2026 meta-analysis51further reported that The GTR rate under CEUS guidance was significantly superior to that of the non-CEUS group (OR = 5.37). Given that GTR has been consistently confirmed as the strongest predictor of survival, the survival benefit of CEUS follows a clear mechanistic logic: precise delineation of infiltrative margins → complete tumor burden removal → delayed recurrence → prolonged survival. Moreover, the accurate protection of functional areas provided by CEUS also safeguards patients‘ postoperative quality of life.50,51

III. Research Limitations and Future Directions

1. Limitations of Existing Research

Despite the significant value of IOUS and CEUS in brain tumor surgery, the following limitations still exist:

Sample size and study design. Currently, most studies are single-center, small-sample retrospective case series, lacking multi-center, large-sample, prospective randomized controlled trials. For example, Giammalva et al.3 only included 17 patients, and Cai et al.21 included 57 patients, both with limited sample sizes. This may lead to result bias and affect the accuracy of the findings.

Heterogeneity issues. There are considerable differences among studies in ultrasound equipment, probe frequency, contrast agent type (SonoVue vs. Definity), administration protocols, and imaging parameters, making direct comparisons between studies difficult.

Outcome measure bias. Most studies use gross total resection (GTR) as the primary endpoint, with insufficient reporting of long-term prognostic indicators such as overall survival (OS), progression-free survival (PFS), neurological function preservation, and quality of life.45 Only a few studies (e.g., Chen et al.50, 2024) have directly investigated the association between ICEUS and survival outcomes.

Technical limitations. CEUS has limited ability to identify low-grade gliomas (LGGs) (some exhibit iso-enhancement or no enhancement), SMI has reduced resolution for deep-seated lesions, and SWE lacks standardized stiffness thresholds. These technical shortcomings restrict their application in surgery.4

Operator dependency. The acquisition and interpretation of IOUS and CEUS images are highly dependent on operator experience, with low inter-observer agreement, which limits the widespread adoption of these techniques.4,31

Lack of subgroup analyses. There are few specific studies targeting special subgroups such as pediatric brain tumors, skull base tumors, and brain metastases, making it difficult to develop individualized intraoperative ultrasound application strategies.

Future perspectives

Despite the proven value of IOUS and CEUS in brain tumor surgery, current studies lack sufficient solutions to address specific clinical challenges. Future research should therefore focus on the following priority directions.

Targeted Design of Miniaturized High-Resolution Probes for Deep-Seated Lesions. Benson et al.52 developed a novel intraoperative imaging adjunct—a miniaturized, high‑resolution, trackable ultrasound (US) imaging endoscope. This probe achieves axial and lateral resolutions of 38 µm and 113 µm, respectively. During tumor resection, it can differentiate neoplastic tissue from healthy parenchyma and detect residual tumors that would otherwise be missed under conventional surgical guidance. When the integrated system was tested in a brain phantom, the tumor boundaries identified by navigated MRI and US images demonstrated excellent concordance.

Multi-Modal Strategy Combining CEUS and Elastography for Low-Grade Gliomas (LGGs), Due to the relatively intact blood–brain barrier in LGGs, contrast-enhanced ultrasound (CEUS) often demonstrates iso-enhancement or weak enhancement, making it difficult to delineate tumor infiltrative boundaries using a single modality.38 Shear wave elastography (SWE) can provide complementary information through tissue stiffness parameters. Using a Young's modulus threshold of 13.90 kPa, the sensitivity and specificity for differentiating high-grade gliomas (HGGs) were 88.9% and 86.7%, respectively, with an area under the curve (AUC) of 0.855 (95% confidence interval: 0.741–0.968, P= 0.001). In this study, the Young's modulus values of LGGs and HGGs were.234 ± 11.6 kPa and.121 ± 13.7 kPa, respectively, demonstrating a statistically significant difference (p = 0.005).22 Future efforts may be directed toward establishing a fusion scoring model integrating CEUS perfusion parameters and SWE stiffness parameters to predict the added value of this multimodal approach in delineating LGG boundaries.17

Furthermore, multi-center prospective registry studies should establish standardized data acquisition protocols, unify ultrasound parameters, contrast agent regimens, and outcome measures, and conduct large‑scale prospective cohort studies to validate the clinical value of CEUS/IOUS across different tumor subgroups. Long‑term outcome studies should take overall survival, progression‑free survival, and neurological function preservation as primary endpoints to clarify the independent impact of CEUS‑guided surgery on patients‘ long‑term prognosis. Artificial intelligence assistance should focus on developing explainable deep learning models capable of real‑time intraoperative tumor boundary delineation, residual tumor detection, and perfusion parameter quantification, thereby reducing operator dependency.31,32

IV. Conclusion

Conventional intraoperative ultrasound provides real-time imaging and offers advantages in brain tumor surgery, including ease of operation, low cost, and high repeatability. However, its inherent limitations in tumor boundary delineation, microcirculatory perfusion assessment, and residual tumor detection have driven the development of multimodal ultrasound imaging strategies. Superb microvascular imaging (SMI) and shear wave elastography (SWE) provide complementary information from the perspectives of microvascular architecture and tissue stiffness, respectively. The introduction of ultrasound contrast agents, leveraging their blood pool imaging characteristics, significantly improves the visualization of tumor vascularization, perfusion patterns, and infiltrative margins, thereby facilitating more precise delineation of resection boundaries. The integration of navigated ultrasound and artificial intelligence enables real-time automated interpretation and localization. The multimodal ultrasound system provides surgeons with real-time, precise, and repeatable decision support for accurate tumor localization and resection, identification of residual tumors, vascular structure identification and preservation, and differentiation of tumor boundaries from peritumoral edema.

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Li H, Tan Y. Evolving Excellence in ERCP Quality—Key Updates and Clinical Implementation. J Transl Gastroenterol. Published online: May 11, 2026. doi: 10.14218/JTG.2026.00013.
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Received Revised Accepted Published
June 15, 2026
DOI http://dx.doi.org/10.14218/JTG.2026.00013
  • Journal of Translational Gastroenterology
  • eISSN 2994-8754
  • © 2026 Xia & He Publishing Inc.
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The Synergistic Role of Intraoperative Ultrasound and Contrast-Enhanced Ultrasound in Brain Tumor Surgery: A Review of Technical Advances and Clinical Applications

Ying He, Danni Zhu, Yuwei Zeng, Jienv Lou, Dan Mao
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