Enhanced Diagnostic Imaging: Arrival-Time Parametric Imaging in Contrast-Enhanced Ultrasound for Multi-Organ Assessment

Introduction

Ultrasound has emerged as the most widely used medical imaging technique globally, offering rapid and real-time examination of various organs and tissues. It is known for its convenience, non-invasiveness, and cost-effectiveness. In recent years, advancements in instruments and technologies have transformed ultrasound from a traditional auxiliary diagnostic tool to a primary method that combines accurate diagnosis and treatment. It has become a crucial and preferred imaging technique, surpassing its previous role of merely complementing computed tomography (CT) or magnetic resonance imaging (MRI) examinations.

Among the various new ultrasound technologies, contrast-enhanced ultrasonography (CEUS) was first introduced in Europe in 1991 [1]. CEUS utilizes ultrasound contrast agents that are injected intravenously during conventional ultrasound procedures. The microbubbles present in ultrasound contrast agents selectively remain within the blood vessels, thereby enhancing the signal of blood flow in patients, particularly for the evaluating of microvessels and large vessels. By facilitating real-time and dynamic observation of microvascular perfusion in the target tissue, ultrasound contrast agents can be eliminated through the lungs via microcirculation, which aids in differential diagnosis [2]. The 2 most frequently used ultrasound contrast agents are SonoVue and Sonazoid. Perfusion imaging is used to assess the qualitative and quantitative characteristics of ultrasound contrast agents by observing the wash-in and wash-out patterns in the tissues of interest. This technique assists in differentiating between benign and malignant lesions. Currently, CEUS is recognized as an independent diagnostic imaging method with significant clinical value, and it is widely utilized across various medical fields. Its advantages include being relatively inexpensive and easy to operate. In recent years, in addition to its established applications in the liver and breast, CEUS has been used as an auxiliary imaging technique for assessing brain death, for the preoperative localization of lymphaticovenous anastomosis in patients with limb edema, and for enhancing the success rate of punctures and reducing complications in the diagnosis of peripheral lung lesions [3–5].

The inflow phase process of traditional CEUS is rapid, yet the limited color display hampers the ability of the human eye to discern the arterial phase perfusion characteristics of small nodules, potentially leading to the omission of critical diagnostic information. This technology heavily relies on the subjective judgment of the operator, which constrains its diagnostic performance. Arrival-time parametric imaging (At-PI) is a CEUS imaging technique that improves the visualization of vascular structures through the integration of temporal information. This method assigns different colors in the image based on the arrival time of ultrasound contrast agent microbubbles, effectively representing the dynamic perfusion of blood flow in the area of interest. In contrast, At-PI provides qualitative and quantitative parameters that assist sonographers in identifying perfusion characteristics that are challenging to differentiate visually. This capability reduces variability among different operators in CEUS mode analysis, thereby enhancing the objectivity and confidence in diagnoses. This technology is also referred to as arrival time parametric imaging (CEUS-PAT), color parametric imaging, and arrival time imaging (ATI) [6–8]. The color scale used in perfusion imaging analysis reflects the timing of the contrast agent’s arrival at a specific location or organ. As time progresses, the colors transition from purple to blue, where purple indicates early arrival, and blue signifies late arrival. The intervals between each color are established based on the timing of the contrast agent’s arrival (Figure 1).

At-PI offers a noninvasive imaging visualization method applicable in various areas, including the analysis of lesion vascular architecture patterns, differentiation between benign and malignant tissues, tissue characterization, and efficacy evaluation. Compared with other examination methods, such as MRI, At-PI is more cost-effective and requires less operational complexity. It presents several advantages, including fewer contraindications, ease of operation, and reduced operator variability. Furthermore, CEUS represents a blood pool phenomenon, utilizing a contrast agent that acts as a true blood pool agent without diffusion [9]. Consequently, the research applications of At-PI hold significant clinical relevance. This paper provides a review of current research on hepatic and non-hepatic CEUS perfusion imaging using At-PI.

This is retrospective review based on searched literature data related to the issue derived from the online databases Medline, Cinhal, and Scopus (in English), using the following keywords: CEUS, arrival-time parametric imaging, and contrast-enhanced ultrasound.

The timeline of At-PI application is illustrated in Figure 2.

Application of At-PI in the Liver

TUMORS:

The initial application of At-PI in liver tumors primarily concentrated on investigating the vascular architecture model. In 2007, researchers in Japan developed At-PI models for 17 rabbit liver malignancies, marking a pioneering effort in the visualization of blood vessels with a minimum internal diameter of approximately 100 to 200 μm [6]. Through the analysis of the number of blood vessels and the ratio of total lumen to visual field area of the tumor vessels, a significant correlation was identified between the number of blood vessels in the tumor and the arrival time of the angiographic agents. This study provided foundational insights into the 7 cases of vascular tumors examined using At-PI, highlighting the presence of severe fibrosis and necrosis associated with tumor growth. However, the research did not offer a comprehensive pathological explanation for the early arrival time of angiographic agents in highly vascularized tumors. Despite the small sample size in constructing At-PI models of animal liver tumors, the introduction of this novel technology in the field of ultrasound has addressed the limitations of traditional real-time perfusion imaging in depicting the vascular curvature characteristics within tumors. This advancement has facilitated the visualization of blood vessels with small inner diameters, enabled the quantification of vessel counts, and allowed for the comparison of contrast agent arrival times across different groups categorized by vessel number. The visual inner diameter of blood vessels in the At-PI of rabbit liver can be as small as 100 to 200 μm. It is essential to investigate the minimum visual inner diameter of blood vessels in other animal livers as well as in human livers. Furthermore, determining whether At-PI can visualize thinner blood vessels and assessing any differences in the degree of vessel diameter visualization between animal and human livers are critical areas for further research. The study on At-PI of liver benign tumors specifically focused on 5 cases of focal nodular hyperplasia with a diameter of less than 3 cm [10]. Despite the involvement of experienced experts, the diagnostic accuracy of micro-flow imaging was only 60% (3/5), while At-PI achieved a remarkable 100% accuracy (5/5). Notably, even a case of focal nodular hyperplasia with a diameter as small as 14 mm and an enhancement time as short as 1.7 s exhibited the characteristic “spoke-wheel pattern” in enhancement direction and timing in the At-PI image. The implementation of At-PI resulted in a significant improvement in diagnostic accuracy by 40%, highlighting its critical role in identifying vascular architectural patterns. However, some scholars have found that, compared with conventional CEUS and At-PI, micro-flow imaging can more effectively depict specific characteristics of blood flow and provide superior diagnostic performance in distinguishing atypical hepatocellular carcinoma (HCC) from focal nodular hyperplasia, particularly when used by ultrasound professionals. This finding is again inconsistent with previous research results [11]. Evaluating small lesions and the rapid transient monochromatic enhancement of contrast agents within a short timeframe poses significant challenges in assessing tumor vascular structures in the human eye, using CEUS. Further research is required to ascertain whether the benefits of At-PI in the curved vascular construction mode for small lesions, as observed in this study, are applicable to organs beyond the liver.

Japanese researchers investigated the relationship between At-PI and histological differentiation in HCC, marking the first instance of At-PI imaging being utilized in human liver tumors [12]. The study compared the quantitative parameter β value (1/TA, TA is peak time) of At-PI among HCC with high [w], medium [m], and low [p] differentiation, as well as normal liver tissue. The β value of wHCC was found to be similar to that of the surrounding normal liver parenchyma, whereas low-differentiation HCC exhibited an increased β value. These quantitative parameters of At-PI effectively reflected the varying degrees of differentiation in HCC. The research provided a comprehensive pathological explanation for these findings: highly differentiated structures displayed underdeveloped abnormal arteries, while low differentiation HCC invaded either the supplying artery or the outflow vessel, resulting in an uneven distribution of blood flow and a loss of normal portal vein structure, ultimately leading to a decrease in the β value [13]. Subsequent studies conducted on At-PI and the time-intensity curve imaging of the same HCC with varying degrees of differentiation [14] and concluded that the color variations observed in At-PI were closely associated with the degree of differentiation in HCC and the time-intensity curve slope. While this study corroborated pathological findings in 2 patients with HCC, regarding color differences, it emphasized the existence of multiple differentiation degrees within the same HCC. The current research on At-PI is limited, raising the question of whether similar findings can be replicated with a larger sample size. By expanding the parameters and increasing the sample size, future studies can further explore the relationship between At-PI imaging and the time-intensity curve slope in differentiating degrees of HCC. Both of the aforementioned studies focus on the selection of regions of interest (ROI). The first study demonstrates that At-PI is used to illustrate color differences, with the quantitative parameter TA being directly measured at the selected color to obtain the β value, thereby avoiding necrosis. The impact of the zone on the results is quantitatively assessed, which minimizes the influence of the operator’s subjective factors. In contrast, the second study measured the time-intensity curve slope of the colorless area separately when selecting ROI in cases of HCC, rather than encompassing the entire region, resulting in an indirectly measured quantitative parameter. The essence of both approaches is that the operator initially identifies the colored area and subsequently conducts quantitative parameter measurements on the selected region, effectively addressing the issue of inaccurate results stemming from improper ROI selection. This parameter analysis allows for an objective evaluation of the tumor’s vascular distribution. Researchers conducting At-PI studies have addressed this concern while examining tumor tissue differentiation, yielding valuable insights for future investigations. The color distribution in At-PI images not only enhances the understanding of tumor differentiation but also provides advantages in the selection of ROIs.

In 2020, Chinese scholars began using At-PI to differentiate between benign and malignant liver tumors [8,15]. First, different operators used At-PI to distinguish focal nodular hyperplasia from atypical HCC, atypical hepatic hemangioma from liver metastasis, and hepatocellular adenoma from wHCC, all demonstrating good cognitive consistency. The inclusion of At-PI parameters significantly enhanced the diagnostic accuracy of novice operators. The subjective interpretation of imaging by operators directly impacted the results. Accumulating experience in learning and utilizing CEUS imaging is essential for scholars in this field. Therefore, reducing the learning curve and attaining diagnostic proficiency comparable to that of experienced physicians is crucial. Second, the integration of At-PI demonstrated superior performance, compared with traditional ultrasonic imaging methods, in differentiating focal nodular hyperplasia from atypical HCC, atypical hepatic hemangioma, and hepatic metastases. In contrast to conventional CEUS, At-PI exhibits higher specificity and sensitivity, with values of 77.3% and 80.0%, respectively. Furthermore, At-PI provides a more objective color-coded map that depicts dynamic perfusion in focal liver lesions, thereby significantly enhancing the sonographer’s capability to detect these lesions. The strong diagnostic capabilities of At-PI present a novel ultrasound imaging approach for distinguishing between benign and malignant liver tumors, thereby offering significant clinical diagnostic value. Third, the At-PI parameters of liver tumors revealed distinct patterns: focal nodular hyperplasia exhibited initial contrast agent arrival at the tumor center, atypical HCC showed uniform arrival, and hemangiomas displayed concentric circles or peripheral nodules upon arrival, while liver metastases demonstrated a uniform and earlier contrast agent arrival, compared with atypical hemangiomas. Hepatic adenomas primarily exhibited centripetal enhancement, whereas wHCC displayed centrifugal enhancement, with hepatic adenomas arriving earlier than wHCC. The qualitative and quantitative At-PI parameters of these tumors not only serve as an additional method to validate CEUS diagnostic outcomes but also supplement ultrasound tumor parameters, thereby providing comprehensive information for clinical use. At-PI significantly enhances the diagnostic accuracy of liver malignant tumors, thereby reducing the likelihood of misdiagnosis. Early detection of malignant tumors is crucial for patients, as it facilitates timely treatment, maximizes the chances of successful intervention, and ultimately reduces mortality rates.

The study on the clinical efficacy of drug treatment for HCC focused on analyzing the qualitative parameter of color mapping and the quantitative parameter of mean time (in seconds) [16,17]. The research observed changes in color mapping color distribution at various time intervals following sorafenib treatment, as well as variations in the mean time of contrast media arrival time to the ROI. Both At-PI parameters indicated a decrease in blood flow velocity after sorafenib treatment. Patients exhibiting a reduced mean time had a higher overall survival rate, and a correlation was identified between mean time and the neutrophil-to-lymphocyte ratio, a sensitive laboratory indicator for cancer progression. Mean time was suggested to be more valuable than neutrophil-to-lymphocyte ratio in evaluating the efficacy of sorafenib. Despite the high cost and potential complications associated with sorafenib, it was found to prolong patient survival and inhibit angiogenesis, thereby demonstrating anti-tumor effects. Hemodynamic studies are crucial for assessing the efficacy of sorafenib [18–20]. Researchers utilizing At-PI observed significant changes in blood flow velocity after just 2 weeks of treatment, suggesting that At-PI may serve as an early efficacy evaluation method following sorafenib treatment for HCC. The application results of At-PI directly reflect the efficacy of the drug, playing a crucial role in adjusting the patient’s treatment plan and minimizing drug complications. By comparing the efficacy of drugs that modify tumor angiogenesis through At-PI ultrasound technology and vascular architecture model imaging, researchers were able to obtain direct images, measurable parameters, and combined laboratory indicators for research purposes. This approach could provide a valuable reference for assessing drug efficacy in other tumor types using At-PI.

NON-TUMOR CATEGORY:

The investigation of liver diseases, excluding tumors, utilizing At-PI commenced in patients with severe alcoholism [21]. In 2011, a comparative analysis of the At-PI color ratio was conducted at various time points, incorporating relevant laboratory test results of the patients. In 2 cases, the initial At-PI exhibited a predominance of red, which indicated liver dysfunction, as per laboratory indicators. However, following a period of alcohol abstinence, the color distribution of At-PI and the laboratory indicators showed improvement. This study established a correlation between laboratory tests and At-PI results, using a final resting image to objectively evaluate the patients’ actual alcohol consumption. Historically, some scholars have utilized the B-mode ratio in the United States to diagnose alcoholic liver disease; however, the accuracy of this method has been found to be moderate [22]. At-PI is a noninvasive examination technique that offers rapid imaging, intuitive results, and repeatable assessments, making it particularly suitable for patients with liver dysfunction. This method can directly inform the drinking habits of individuals with alcohol-related issues and assist them in modifying their lifestyle choices in clinical practice, ultimately contributing to the restoration of liver function. This research represents the inaugural application of At-PI in the investigation of lifestyle habits that can contribute to specific diseases, demonstrating significant potential for disease prevention research. However, it is crucial to acknowledge that this study was confined to a case report and did not encompass a large sample size. Future analyses could incorporate additional factors, such as daily alcohol consumption, to facilitate a more comprehensive evaluation.

In recent years, numerous scholars have concentrated on investigating fibrosis in non-tumor liver tissue using At-PI. The quantitative parameters frequently used to evaluate the extent of fibrosis include the red-to-overall ratio (ROR) and the CEUS-PAT ratio. Research has demonstrated that the ROR is correlated with the severity of fibrosis in chronic hepatitis C, although it does not correlate with the level of inflammation [23,24]. The sensitivity and specificity of At-PI in diagnosing fibrosis stage (F) 2 and stage F4 were 0.971 and 0.657, and 0.889 and 0.918, respectively. Complications of portal hypertension, such as paraumbilical veins and splenorenal shunts, can occur when the ROR is ≥60.3%. Additionally, At-PI demonstrates a sensitivity of 87.5% and a specificity of 86.5%, which effectively predicts the presence of esophageal varices [25]. Changes in ROR, which reflect alterations in liver blood flow, have shown promise in diagnosing fibrosis in primary biliary cholangitis. The sensitivity of using At-PI to diagnose F1 (F2) is 0.75 (0.92), while the specificity is 0.82 (0.81). In contrast, the sensitivity of shear wave velocity for diagnosing F1 (F2) is 0.75 (0.60), with a specificity of 0.82 (0.86). Overall, the sensitivity and specificity of the 2 methods are comparable, with At-PI demonstrating greater sensitivity in diagnosing a specific stage [26]. Patients with cirrhosis demonstrate a higher CEUS-PAT ratio than do healthy individuals [23]. Various studies have used At-PI to compare different stages of fibrosis and analyze disease progression. Noninvasive At-PI ultrasound technology and invasive liver biopsy effectively characterize the severity of fibrosis, with the former offering a comprehensive view of the right liver. This information is essential for the clinical diagnosis, treatment, and prognosis of liver fibrosis. At-PI can serve as an alternative to liver biopsy for assessing liver fibrosis. It is non-toxic to the liver and can be used repeatedly, thereby minimizing the physical damage and psychological stress associated with traditional liver biopsy procedures. Future research could explore the use of the ROR, CEUS-PAT ratio, or other At-PI quantitative parameters to investigate fibrosis caused by different etiologies.

At-PI is more commonly utilized in the evaluation of liver non-tumor diseases characterized by liver hemodynamic alterations. The primary changes observed in At-PI include modifications in color distribution and ROR, particularly in instances of portal vein thrombosis and small hepatic vein occlusion associated with Buga syndrome [27,28]. Notably, regardless of the presence of jaundice in patients with benign recurrent intrahepatic cholestasis, ROR levels were found to be comparable to those of normal individuals [29], indicating that benign recurrent intrahepatic cholestasis does not significantly affect liver hemodynamics. Although this segment of the study included only 3 cases, the results derived from At-PI parameters highlight the potential and accuracy of this technology in assessing hemodynamic equilibrium in non-tumor liver diseases. However, it is crucial to acknowledge that the scope of diseases examined in this study was limited, and future research should encompass a broader range of conditions that influence liver hemodynamic changes.

Non-Hepatic Applications of At-PI

ADRENAL GLANDS:

In 2015, Polish scholars conducted a study using At-PI in the adrenal gland to differentiate between hyperplastic nodules and adenomas (34 cases) [30]. The analysis revealed that AT (the time of arrival) did not significantly differ among all benign adrenal masses. When examining tumor enhancement modes at different times of arrival (peripheral, central, mixed, and no enhancement, the study found that At-PI had a sensitivity of 100% and a specificity of 83% in detecting adenomas, outperforming other diagnostic methods. Despite the study’s focus on benign adrenal diseases and the limited comparison of qualitative parameters, the researchers noted that tumor size or depth did not affect the observation of enhancement modes. This pioneering use of At-PI in the abdominal cavity, beyond the liver, represents a significant advancement. While the study did not compare the imaging visualization quality of At-PI in the adrenal gland or investigate potential differences in results based on operator experience, future research could explore these aspects. Previous studies have shown the efficacy of At-PI in distinguishing benign and malignant liver tumors, raising the question of its applicability in adrenal tumors [8,14,15]. Additionally, further investigation could delve into potential differences in At-PI parameters among adrenal tumors with varying characteristics and whether At-PI can enhance diagnostic efficiency, compared with other ultrasound techniques. These avenues warrant exploration in future studies.

BREAST:

In 2016 and 2020, Asian countries conducted imaging studies on the female breast using At-PI. First, the studies aimed to assess the visibility of breast lesions. In Japan, a comparison was made between 65 cases of breast cancer lesions visualized with At-PI by both beginners and experts. Operators rated the visualization quality of At-PI as the highest level (1.44 points). Beginners noted that At-PI provided significantly better visibility than did other imaging methods, reducing measurement bias and enhancing consistency in lesion diameter assessment [31]. Chinese researchers, in a study involving 184 cases of benign and malignant breast lesions, demonstrated good reproducibility of At-PI between operators and within operators themselves [32]. The advantages of At-PI can significantly enhance the diagnostic accuracy of breast tumors by junior doctors, thereby playing a crucial role in the routine outpatient screening for breast diseases. The high visualization quality and reproducibility of At-PI ultrasound technology are crucial for clinical diagnosis and serve as the basis for future research. Second, while At-PI offers excellent visualization, MRI remains superior in correlating lesion size with pathology [31]. The study suggests that At-PI may not be as effective as MRI in evaluating breast tumor size. Third, the perfusion patterns and color distribution types of benign and malignant breast lesions differ in At-PI imaging mode [32]. The sensitivity and specificity of the 2 quantitative parameters, MDRAI/GI (the maximal diameter ratio of the lesion in contrast-enhanced ultrasound images [CI] and that in gray-scale images [GI]) and ARAI/GI (the area ratio of the lesion in CI and that in GI), based on At-PI, are 84.48% and 88.24%, and 93.10% and 91.18%, respectively. Breast cancer is often characterized by centripetal perfusion and type 1 color distribution, with an analysis linking these findings to the vascular architecture pattern of the lesion. While the correlation between lesion size and pathology measured by At-PI may not be as strong as that of MRI, the study highlights the importance of 2 quantitative parameters – MDRAI/GI and ARAI/GI – in distinguishing between benign and malignant breast lesions. Overall, the use of At-PI for measuring lesions shows promise in clinical settings for identifying tumor properties.

LYMPH NODES:

The current research on the application of At-PI to lymph nodes is limited to a single report from 2018. In this study, At-PI was used for the differential diagnosis of pathological features in 145 lymph nodes [33]. The imaging technique allowed visualization of perfusion modes (centripetal, centrifugal, fully synchronous), perfusion uniformity (uniform, uneven), presence of perfusion defects, and clarity of boundaries in non-enhanced areas. An innovative addition to the study was the parameter of transit time, representing the travel time between peripheral and central or central to peripheral regions. The study concluded that the most accurate transit time value for distinguishing between benign and malignant lymph nodes was 2.75 s. Notably, transit time was found to be a relative value independent of lymph node diameter, thus mitigating the impact of individual differences, such as cardiac function, on contrast agent arrival time. The sensitivity and specificity of transit time were 78.9% and 64.7%, respectively. It is advised that future studies utilize this objective parameter to reduce potential bias in results. When compared with CEUS, At-PI showed a decrease in diagnostic uncertainty from 19.3% to 15.2% and an increase in diagnostic accuracy from 76.6% to 83.4%. These findings align with previous research demonstrating the improved diagnostic accuracy of At-PI in liver examinations [10], underscoring its potential to enhance disease diagnosis in lymph nodes. Moreover, the study observed changes in perfusion modes of lymph nodes smaller than 2 cm after At-PI, consistent with previous observations in liver lesions smaller than 3 cm. This highlights the utility of At-PI in analyzing perfusion patterns of small lesions across different organs, with <2 cm representing the minimum lesion diameter range explored in At-PI studies so far. Historically, imaging diagnoses of lymph node diseases have offered numerous qualitative parameters, particularly CEUS. The implementation of At-PI in lymph nodes introduces quantitative parameters for clinical diagnosis, enhancing the accuracy of distinguishing between benign and malignant lymph nodes. This advancement provides a stronger foundation for the detection, metastasis, and recurrence of malignant lymph node diseases in patients.

PROSTATE:

The recent application of At-PI in prostate evaluations has primarily focused on assessing postoperative efficacy. By conducting At-PI before and after prostatic artery embolization (PAE) in 18 patients with benign prostatic hyperplasia, and using time-intensity curve analysis, researchers were able to evaluate and monitor the success rate of PAE [34]. The At-PI images clearly depicted color differences before and after PAE. Subsequently, a study utilized this technology along with CEUS to compare and assess the effectiveness of irreversible electroporation in treating 50 cases of prostate cancer [35]. Prostatitis was predominantly red and yellow in a large area, while the ablation zone appeared as green and dark purple, devoid of any nodular color patterns. In cases of prostate cancer and postoperative recurrence, nodular red and yellow areas were observed, and all patients with recurrence were accurately identified using CEUS and At-PI. In comparison to MRI, At-PI demonstrated a sensitivity of 76% and a specificity of 81% for the detection of residual tumors. While MRI uses a contrast agent containing gadolinium, which is associated with certain adverse effects, At-PI uses a contrast agent that is safe and appropriate for use in patients with impaired kidney function and hyperthyroidism. Additionally, At-PI is more cost-effective than MRI. At-PI demonstrated a high diagnostic accuracy for recurrent lesions in prostate cancer; however, the aforementioned studies did not propose specific quantitative parameters associated with At-PI.

GASTROINTESTINAL TRACT:

For the application of At-PI in the gastrointestinal tract, researchers conducted a comparative analysis of the diagnostic accuracy of 24 cases of acute gastrointestinal graft-versus-host disease among different operators [36]. The study revealed that experienced operators achieved a diagnostic accuracy rate of 95%, while inexperienced operators achieved 89%. Both groups demonstrated high diagnostic accuracy levels. Similar to previous studies on At-PI in liver and breast imaging, the application of At-PI in gastrointestinal diseases appears to be operator-dependent. Subsequent research has shown that At-PI can provide direct insights into intestinal perfusion and transmural conditions [37]. Analysis of At-PI parameters can help evaluate intestinal perfusion ratios and identify disruptions in the intestinal barrier. These findings suggest that At-PI can serve as a valuable tool not only for diagnosing parenchymal organ conditions but also for assessing hollow organ diseases. However, further research is needed to validate these findings with larger sample sizes and to explore the application of At-PI in a wider range of intestinal diseases, including benign and malignant conditions.

Limitations

Currently, there is a limited amount of literature on At-PI, with the literature primarily originating from Asian countries, particularly Japan. Japan was the first to use At-PI for liver research, utilizing the Aplio SSA-790A (Toshiba Medical Systems, Tokyo, Japan) in 2007. Prior to 2013, all relevant reports on this technology were exclusively from Japanese liver research. It was not until 2015 that China and Poland began conducting research on the liver and adrenal glands using the Aplio SSA-770A/500 and Aplio XG (both by Toshiba Medical Systems, Tokyo, Japan), respectively, that this technology gained global attention. This development has expanded the recognition of At-PI among scholars worldwide, leading to its application beyond the liver. In 2016, certain experts used At-PI technology on the LOGIQ S8 (GE Healthcare Japan) for breast imaging. By 2018, numerous countries worldwide began using the LOGIC E9 (GE Healthcare) for At-PI research across multiple organs and various disease types. The author postulates that the At-PI application software was initially developed by Toshiba in Japan and integrated into the Aplio series, while other companies have yet to create their own At-PI software. This may explain why Japan is the earliest adopter and has the highest usage of this technology. Ultrasound imaging technology is continuously evolving, and GE Healthcare has since developed and integrated At-PI software into the LOGIC E series. Furthermore, the clinical diagnosis and treatment capabilities in China have significantly improved in recent years, facilitating the adoption of advanced technologies by Chinese ultrasonography practitioners. Consequently, At-PI software has also been developed and implemented in the LOGIC E series in China. Research on PI is progressively increasing, and several European countries commenced their At-PI research nearly simultaneously with China, with most of the application machines being LOGIC E9 (GE Healthcare). Currently, At-PI exclusively utilizes the Aplio series and LOGIC E series, which feature differing color interval time settings and a limited number of effective parameters. This results in a lack of unified standards for the qualitative and quantitative parameters of At-PI. The liver represents the largest proportion of all applied organs, while the application of non-liver organs has lagged by 8 years and is restricted to the adrenal gland, lymph nodes, breast, prostate, and gastrointestinal tract (Table 1). Researchers in this field have also been relatively conservative and limited in their explorations of other organs. For instance, although both the thyroid gland and breast are superficial organs with well-established research on the application of CUES in the thyroid, there are currently no public reports regarding the use of At-PI in thyroid diseases.

Beyond the liver, CEUS applications for gallbladder and kidney diseases are also prevalent among abdominal organs; however, research related to At-PI in these areas remains absent.

The At-PI results presented in the literature reviewed in this article can be subject to bias due to the limited sample size, and their accuracy warrants further verification. For instance, a 2020 CEUS study on focal nodular hyperplasia with a diameter of less than 3 cm reported an accuracy of 90.3%. Although this figure falls short of the 100% accuracy observed in previous At-PI studies [10,11], it is important to note that the sample size for this study was only 31 cases, which is 6 times smaller than that of the At-PI study. This raises the question: If the sample size in the At-PI studies were to be increased significantly, would its accuracy remain satisfactory?

Current international guidelines for CEUS cover hepatic and non-hepatic applications [38,39], but a standardized guideline for perfusion imaging is lacking. At-PI is capable of generating color images depicting the arrival time of contrast agent perfusion in a layered manner, yet it does not capture perfusion intensity or the contrast agent’s extinction process. Consequently, it offers limited perfusion information and often necessitates integration with other imaging modalities and laboratory data for accurate diagnosis or guideline development.

Conclusions and Perspectives

Although At-PI has been investigated in various organs, such as the liver, adrenal gland, breast, lymph node, prostate, and gastrointestinal tract, over the past decade, its application has primarily been limited to clinical research. The transition from clinical research to clinical implementation requires careful consideration of several factors. First, the selection of appropriate parameters for At-PI is crucial as the accuracy of ultrasound diagnosis relies on multiple qualitative and quantitative parameters. This transition process is contingent upon understanding the pathological mechanisms of the disease, the vascular architecture, and the choice of contrast agents. Parameters suitable for diagnosing specific organ diseases may not be applicable to others, highlighting the need for further exploration of At-PI parameters across various organs, diseases, and perspectives. This research focuses on the application of At-PI in identifying benign and malignant thyroid tumors, evaluating the diagnostic accuracy of thyroid microscopic lesions, exploring the correlation between At-PI parameters and the molecular biology of thyroid cancer, and establishing At-PI models for various pathological types of thyroid tumors. Second, At-PI utilizes color-coded imaging based on contrast agent arrival time in tissue. Exploring the possibility of color-coding extinction time and enhancing perfusion information represent potential optimization directions for this technology. Third, moreover, due to individual variations and other factors, expanding sample sizes and fostering multi-center collaborative research are essential to identify more effective parameters for diverse individuals and diseases. This will facilitate the integration of At-PI into clinical practice and encourage global scholars to leverage this technology in conjunction with their specific disease research contexts.