{"paper_id":"39139016-91b3-4a9d-8908-a1c611d798ae","body_text":"Wang et al. Insights into Imaging          (2022) 13:141  \nhttps://doi.org/10.1186/s13244-022-01274-9\nCRITICAL REVIEW\nAdvances in the clinical application \nof ultrasound elastography in uterine imaging\nXia‑li Wang1,2, Shu Lin1,3,4* and Guo‑rong Lyu1,2*   \nAbstract \nChanges in tissue stiffness by physiological or pathological factors in tissue structure are identified earlier than their \nclinical features. Pathological processes such as uterine fibrosis, adenomyosis, endometrial lesions, infertility, and \npremature birth can manifest as tissue elasticity changes. In clinical settings, elastography techniques based on ultra‑\nsonography, optical coherence tomography, and magnetic resonance imaging are widely used for noninvasive meas‑\nurement of mechanical properties in patients, providing valuable tool and information for diagnosis and treatment. \nUltrasound elastography (USE) plays a critical role in obstetrics and gynecology clinical work because of its simplicity, \nnon‑invasiveness, and repeatability. This article reviews the recent progress of USE in uterine tumor diagnosis (espe‑\ncially early diagnosis and treatment effect evaluation), prediction of preterm birth, and intrauterine insemination. We \nbelieve that USE, especially shear wave elastography, may serve as a potential means to assess tissue stiffness, thereby \nimproving the diagnosis and treatment of adenomyosis, fibroids, endometrial lesions, cervical cancer, and precise \nmanagement of preterm birth and intrauterine insemination monitoring.\nKeywords: Elastography, Ultrasonography, Uterus, Shear wave elastography, Stiffness\n© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which \npermits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the \noriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or \nother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line \nto the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory \nregulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this \nlicence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.\nKey points\n• The SWE is more suitable for obstetrics and gyneco -\nlogical applications.\n• USE can assess treatment responses in uterine \nfibroids and adenomyosis.\n• Measuring JZ through SWE could be beneficial for \nidentifying adenomyosis.\n• A risk prediction model using SWE for pre-term \ndelivery is possible.\n• Increased utilization of USE may facilitate an earlier \ncervical cancer diagnosis.\nBackground\nThe female reproductive system is a complex multi-organ \nsystem with multiple closely regulated functional pro -\ncesses [1]. Therefore, uterine stiffness is one of the impor-\ntant mechanical parameters and physical properties of \nuterine tissue and is closely related to the biological char-\nacteristics of the uterus [2]. Different cycles of uterine tis-\nsue, such as proliferative or secretory, or gestational and \nnon-pregnant, have different degrees of stiffness [3]. In \naddition, some pathological processes may manifest as \nchanges in the elasticity of uterine tissue [4]. For exam -\nple, compared with normal myometrium, uterine fibroids \nare characterized by altered mechanical homeostasis and \nincreased stiffness due to excess extracellular matrix [5]. \nAdenomyosis is usually diagnosed as myometrial glan -\ndular and interstitial heterotopia. Histopathology shows \nhyperplasia and hypertrophy of surrounding smooth \nmuscle cells with hyper-fascicular trabecular pattern and \nincreased extensive fibrosis and micro-vascularization [6, \n7]. Benign lesions such as endometrial hyperplasia, pol -\nyps, and endometrial atrophy originate from endometrial \nOpen Access\nInsights into Imaging\n*Correspondence:  shulin1956@126.com; lgr_feus@sina.com\n1 Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical \nUniversity, No. 34 North Zhongshan Road, Quanzhou 362000, Fujian Province, \nChina\n3 Centre of Neurological and Metabolic Research, The Second Affiliated \nHospital of Fujian Medical University, No. 34 North Zhongshan Road, \nQuanzhou 362000, Fujian Province, China\nFull list of author information is available at the end of the article\n\nPage 2 of 15Wang et al. Insights into Imaging          (2022) 13:141 \nsoft tissue and endometrial gland hyperplasia, contain -\ning a small amount of fibrous interstitial components, \nhave soft stiffness, and are accompanied by an increased \nproportion of nucleosomes. Therefore, malignant trans -\nformation may be associated with increased stiffness [8]. \nGiven that, studying the stiffness of tumor tissue gives a \ndeep insight into its characteristics and behavior (Fig. 1a).\nFurthermore, these physiological changes lead to bio -\nmechanical modifications in uterine tissue [9]. Changes \nin the collagen content and structure of uterine tis -\nsue during pregnancy lead to uterine tissue physiologi -\ncal remodeling and tissue elasticity [10]. The collagen \nand elastic fiber structure of the cervix undergoes rapid \nand dramatic changes to fulfill its different physiological \nroles for competence during pregnancy and compliance \nduring birth [11]. Moreover, elastography changes due \nto pregnancy complications or abnormal delivery have \ncontributed to cervical softening disorders (Fig.  1b) [12]. \nTherefore, assessing cervical elasticity to predict prema -\nture delivery and labor induction outcomes may influ -\nence the choice of clinical treatment.\nThe endometrium undergoes a receptive period dur -\ning the menstrual cycle where blastocysts can invade.\nThis period is defined as the “window of implantation” \nand is of limited duration [13]. Precise determination of \nthe window of implantation can significantly improve the \nefficacy of assisted reproductive technology (ART) [14]. It \nis well established that endometrial elastography reflects \nbiochemical and molecular changes in the endometrium \nthroughout the menstrual cycle [15]. Concurrently, \ntransvaginal ultrasound is widely used and offers a good \nopportunity for rapid and accurate assessment of the \nendometrium. However, the clinical relevance of ultra -\nsonographic markers remains uncertain and further \nstudies are needed to conclude [16]. Herein, we sought to \nreview the potential ability of USE to predict pregnancy \nrates following intrauterine insemination (IUI) cycles.\nUltrasound elastography has also been widely used to \ndiagnose various organs disorder such as the liver, breast, \nthyroid, and blood vessels [17]. This promising technique \nhas played an important role in obstetrics and gynecology \ndue to its simplicity, non-invasiveness, and reproducibil -\nity [18]. This article reviews the recent advances in USE \napplication for diagnosing myometrium, endometrial and \ncervical tumors, especially the evaluation of early diag -\nnosis and treatment. In pregnancy, our review focuses on \nimproving the efficiency of predicting preterm birth and \nidentifying a potential approach to precisely manage neo-\nnatal respiratory complications. In addition, the use of \nUSE to monitor IUI can also be discussed concurrently.\nPrinciples of ultrasound elastography in uterine \ndiseases\nUltrasound is the most commonly used imaging diag -\nnostic tool in obstetrics and gynecology; however, ultra -\nsound imaging also has some disadvantages, such as \nlow contrast between abnormal tissue and surrounding \ntissue. Relying on operator subjectivity and subsequent \nFig. 1 Potential involvement of stiffness in uterus disorders. A is for non‑gestation period while B is for gestational period. The stiffness of \nuterus fibroids, EC, cervical cancers, infertility, and disorders in the cervix during pregnancy increases than normal tissues (Red font), as well \nas endometrium polyps decrease (blue font). AEH and adenomyosis are still uncertain (green font). AEH atypical endometrial hyperplasia, EC \nendometrium cancer\n\nPage 3 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \ninability to distinguish the mechanical properties of tis -\nsues with the same ultrasonic echogenicity is also a \ndisadvantage of ultrasound imaging [19]. Notably, elas -\ntography techniques can display elastic tissue changes \ndue to specific pathological or physiological processes \n[20]. All elasticity measurement and imaging methods \ntypically introduce a mechanical excitation and monitor \nthe resulting tissue response. The different techniques \ncurrently available USE techniques can be divided into \nstrain imaging and shear wave imaging (SWI) accord -\ning to the measured quantity [21]. The workflow of USE \ncan be simplified as follows: First mechanical excitation \nis applied to the target tissue, and then, the displacement \nor shear wave generated by the target tissue is obtained. \nFinally, the different signals are encoded and imaged, or \ncorresponding parameters are measured [22] (Fig.  2). \nStrain and SWI require mechanical excitation, which \ncan be divided into (A) manual compression (by hand or \nusing cardiovascular pulsation or respiratory motion), (B) \nacoustic radiation force pulse (ARFI), and (C) external \nmechanical vibration [23]. Currently, the clinical imaging \ndiagnostic methods mainly include strain elastography \n(SE), transient elastography (TE), ARFI imaging (ARFI \nimaging), shear wave speed measurement, and imaging \nusing acoustic radiation force impulse excitation [24].\nStrain imaging should measure the “stress” applied to \norganizational structure relative to the resulting “strain” \nor deformation. SE and ARFI imaging belong to this \ncategory, and SE is the most widely used mode in obstet -\nrics and gynecology. In SE, stimulation methods include \nmanual tissue compression by the operator using an \nultrasonic transducer or generated internally by physi -\nological movements, such as the cardiovascular or res -\npiratory systems. Transparent color overlay on B-mode \nimages is used for visualization, and strain-based elastog -\nraphy is generated to transform tissue strain information \ninto two-dimensional grayscale or pseudo-color images, \nwhich become strain profiles [25]. It is worth noting that \nthe color scale may vary by ultrasound provider. The \nstrain ratio (SR), which is the ratio of strain measured in \na target lesion region of interest (ROI) to strain measured \nin adjacent (usually normal) reference tissue ROI, indicat-\ning that the SR is higher and the target lesion compresses \nmuch more difficult, and then, the stiffness is greater, and \nvice versa. However, artificial or physiological pressures \ncannot be quantified, requiring operator skills and expe -\nrience for promising results.\nSWI utilizes dynamic pressure to generate shear waves \nin parallel or vertical dimensions. Shear wave velocity \ncan qualitatively and quantitatively estimate tissue elas -\nticity [26]. The process can be summarized as follows: 1) \nThe focused acoustic radiation force pushes the short-\nduration pulse; 2) the shear wave is generated within the \norgan of interest; 3) the speed of the shear wave propa -\ngation is measured away from the push position; and 4) \nthe reported information can be averaged within an ROI \nFig. 2 Flow chart of ultrasound elastography\n\nPage 4 of 15Wang et al. Insights into Imaging          (2022) 13:141 \n(a point measurement) or as an image (shear wave elas -\ntography) and values are reported as shear wave veloc -\nity (Cs) or converted to the elastic modulus. The output \nobtained from each elastography technique corresponds \nto the measured physical quantity, as shown in Fig. 3.\nShear wave elastography (SWE) is the most widely \nused SWI in obstetrics and gynecology among different \nkinds of SWI [27]. The uterus is an active pelvic organ. \nTherefore, it is challenging to control the artificial pres -\nsure consistently to ensure repeatability when using SE. \nMeanwhile, SE has the limitation of difficulty in imaging \ndeep pathological tissues, so this technology is mostly \nused to detect direct contact organs, such as the elastic -\nity detection of superficial organs. The SWE can theoreti-\ncally detect depths up to 8 cm without operator pressure \nand has quantitative properties, making it more suitable \nfor obstetrics and gynecology applications.\nUltrasound elastography and different uterine \ndiseases\nUltrasound elastography, especially shear wave elastogra-\nphy, has emerged to assess tissue stiffness in recent years, \nthereby improving the diagnosis and treatment of clinical \nuterine fibroids, endometriomas, cervical tumors, etc.\nNormal myometrium, uterine fibroids, \nand adenomyosis\nAccording to the physical characteristics of uterine \nfibroids, the stiffness of uterine fibroids should be greater \nthan the surrounding myometrium. This result is also \nsupported by the current ultrasound elastography study \nof uterine fibroids (Fig.  4), with SWE showing images \nmeasuring uterine fibrosis [28–30]. However, elastogra -\nphy stiffness is controversial in assessing adenomyosis. \n(Table 1 reviews the literature on USE in diagnosing nor -\nmal myometrium, uterine fibroids, and adenomyosis.) \nFrank et  al. obtained elastography data from 206 uteri \nwith SE and maximum SR (ROI lesions/ROI healthy tis -\nsue). They demonstrated that the maximum SR values \nfor uterus fibroids were 2.65 [2.12; 3.34] and 0.44 [0.36; \n0.46] for adenomyosis. The SR of uterine fibroids was \ngreater than 1, and the SR of adenomyosis was less than \n1, indicating that uterine fibroids were stiffer than nor -\nmal tissue, and adenomyosis was softer. They further sug-\ngested that SE can help differentiate uterine fibrosis from \nadenomyosis [31]. However, Liu et  al. also used SE to \nevaluate the stiffness of adenomyosis and uterine fibrosis, \nand the results showed that the stiffness of adenomyosis \nlesions was significantly higher than the normal uterus \n(p < 0.0001) and even higher than that of fibroid lesions \n(p = 0.006). This study further found that lesion stiffness \nwas positively correlated with fibrosis degree, negatively \ncorrelated with E-cadherin and progesterone receptor \nexpression levels, and positively correlated with dysmen -\norrhea severity and the number of menses. SE can guide \nthe choice of the best treatment modality for patients \n[32]. The results on adenomyosis stiffness in these two \nstudies were opposite, probably because SE was affected \nby probe pressure, ROI selection was subjective, and AM \nlesions generally did not have obvious border shifts on \nultrasound or SE.\nAnother controversial point is whether USE can dif -\nferentiate adenomyosis from uterine fibroids. Zhang \net al. applied SWE to evaluate uterine adenomyosis and \nFig. 3 The excitation and output methods for different ultrasound elastography modalities. ARFI acoustic radiation force impulse\n\nPage 5 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \nuterine fibrosis. They reported a Cs of 4.861.9  m/s in \nnormal myometrium, 4.962.5  m/s in adenomyosis, and \n5.662.5  m/s in fibrosis, with no significant difference in \nCs between adenomyosis and fibrosis (p = 0.40) [31]. \nPongpunprut et  al. also demonstrated that SWE could \ndifferentiate adenomyosis from the normal uterus, but \nthere was no significant difference in Cs between adeno -\nmyosis and fibroids groups [33]. Görgülü et al. reported \nthat both SE and SWE were used to differentiate leio -\nmyomas from adenomyosis, and both SE and SWE were \nstatistically different (p < 0.001) [34]. It was proposed that \nthere are contradictory results because of the limited \nnumber of studies hitherto performed with SE or SWE, \nand studies with larger patient groups are required.\nAlthough controversial, both SE and SWE have been \nshown to differentiate between normal muscle layers, \nadenomyosis, and uterine fibroids, so SE may help assess \nresponse to therapy. Xie et  al. investigated the effect of \nGnRH agonist (GnRHa) on adenomyosis by SE. They \nfound increased elasticity in adenomyosis after GnRHa \ntreatment, associated with spontaneous pregnancy in \ninfertile patients [35]. Using SWE to study the response \nof uterine fibrosis patients to uterine artery embolization \n(UAE), Samanci et  al. found significantly lower uterine \nfibrosis values after uterine artery embolization than in \nnormal tissue. SWE can be used as a follow-up tool for \nuterine fibrosis after UAE [36].\nAdenomyosis severely affects the quality of life of \npatients [37]. However, the stiffness changes in adeno -\nmyosis are unclear. Recently, the uterine junctional zone \n(JZ) has been defined as the inner 1/3 of the myometrium \nbetween the endometrium and the myometrium. Its \nstructural and functional disturbance has been reported \nto be involved in the occurrence and development of \nadenomyosis [38]. In 2021, a consensus was reached on \na revised definition of the Morphological Uterine Ultra -\nsound Assessment (MUSA) features of adenomyosis, \nwhich considered irregular union bands as an indirect \nfeature of adenomyosis [39]. Since adenomyotic lesions \nnear the JZ may have more advanced fibrosis than newer \nlesions at the mid-uterine wall, different measurement \nlocations have different Cs values [40]. Therefore, we \nhypothesized that measuring the Cs of JZ could improve \nthe accuracy of SWE in identifying adenomyosis. Fig -\nure 5 shows the procedure of JZ displayed and measured \nby SWE.\nIn summary, USE can be used as an alternative diag -\nnostic tool to differentiate between normal myometrium \nand uterine fibroids, and normal myometrium and aden -\nomyosis, suggesting a potential role for USE in assessing \ntreatment response. Whether USE can distinguish uter -\nine fibroids from adenomyosis is still controversial.\nEndometrial tumors\nThe USE study in endometrial tumors is still in its \ninfancy, and the literature is limited [41]. Czuczwar \net al. demonstrated that SE could not be used to screen \nintrauterine lesions. However, SE can show the dif -\nferent stiffness of endometrial polyps and submu -\ncosal fibroids when the lesions are already visible on \nFig. 4 SWE used to diagnose of uterus fibroids. A Transvaginal ultrasound showed a hypoechoic lesion in the anterior inferior uterine segment \n(marked with a white arrow). B SWE showed a lighter blue color pseudocapsule that circling around the fibroid (marked with a white arrow). C \nLocating the region of interest at the lesion 2 and shear wave speed (Cs) measured automatically\n\nPage 6 of 15Wang et al. Insights into Imaging          (2022) 13:141 \nTable 1 Overview of the studies on USE in diagnosing UF and UM\nYear Authors Patient numbers and type of \nlesions\nType of elastography Type of study Diagnostic parameters Diagnostic performance or \nresearch results\nAssessment of the normal uterus\n2019 Manchanda et al. \n[58]\nNM = 56 SWE Prospective cohort study E mean The E mean was 25.54 ± 8.56 \n(endometrium), 40.24 ± 8.59 (myo‑\nmetrium), and 18.90 ± 4.22 (cervix). \nThere was no significant difference \nin E mean for women in different \nmenstrual phases (p = .176) or in \ndifferent age groups (p = .376)\n2015 Soliman et al. [57] NM = 32 ARFI Prospective observational study Cs mean The menopausal status did not have \nany significant influence on the Cs \nmeasurements. The Cs means were \n2.05 ± 0.77 m/s (endometrium) \nwhile 2.82 ± 0.77 m/s(myometrium)\nLesions of the uterus\n2022 Pongpunprut \net al. [33]\nNM = 25, UF = 25, AM = 25 SWE Prospective cross‑Sectional Study Cs mean The Cs differed between NM and \nAM (p = 0.019) with the cut‑off point \nat 3.465 m/s and 80% sensitivity, \n80% specificity, and AUC of 0.80 \n(95% CI 0.68–0.93) (p < 0.001). SWE \ncould not differentiate AM from UF \nor UF from NM\n2021 Görgülü et al. [34] UF = 98, AM = 37 NM = 40 SWE, SE and MRI ADC Retrospectively case–control study SR mean, SR max, ADC values, Cs \nmean, and Cs max\nSE, SWE, and MRI ADC could be \nuseful in differentiating UF and AM \n(p < 0.001 for all three), and none \nof these methods were statistically \nsuperior to each other in differenti‑\nating the UF from the AM (p < 0.001)\n2019 Zhang et al. [49] NM = 16, UF = 12, AM = 6 SWE Prospective case–control study Cs mean Cs mean in NM was 4.861.9 m/s, \ncompared with 4.962.5 m/s in AM \nand 5.662.5 m/s in UF (p = 0.34). \nSWV for AM and UF did not differ \nsignificantly (p = 0.40)\n2018 Bildaci et al. [29] AM = 28, NM = 62 vitro ARFI Prospective case–control study Cs mean The Cs mean of AM (4.22 ± 1.62 m/s) \nshowed a significant differ‑\nence compared to that of NM \n(3.22 ± 0.90 m/s) (p < 0.01)\n2018 Stoelinga et al. \n[30]\nNM = 10, UF = 10, AM = 10 SE Prospective diagnostic study Uterine volume for AM and fibroid \nvolume for AF\nThe sensitivity of SE in the diagnosis \nof UF and AM was 82% and 91%, \nand the specificity was 95% and \n97% with high inter‑observer and \ninter‑method agreement\n\nPage 7 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \nTable 1 (continued)\nYear Authors Patient numbers and type of \nlesions\nType of elastography Type of study Diagnostic parameters Diagnostic performance or \nresearch results\n2018 Liu et al. [32] NM = 141, UF = 75, AM = 147 SE Prospective control study SR mean, SR max, SR min The stiffness of AM lesions was \nsignificantly higher than that of UF \n(p < 0.01)\n2016 Frank et al. [31] NM = 143, UF = 41, AM = 22 SE Prospective case–control study SR max: stored as the “lesion index” “Lesion indices” of UF, AM, and NM \nwere 2.65, 0.44, and 1.19, respec‑\ntively, and were significantly differ‑\nent between them (p < 0.001)\nAssessment of treatment\n2020 Samanci et al. [36] UF = 33 SWE Prospective case–control study Cs mean The post‑UAE Cs mean of UF \n(3.34 ± 3.9 kPa) was significantly \nlower than that of the pre‑UAE \n(17.16 ± 4.8 kPa) (p < 0.001). There \nwas excellent agreement between \nthe 2 blinded observers in Cs mean\n2019 Xie et al. [35] AM = 45 SE Prospective case–control study scoring system In 12 cases who were pregnancy \nduring the follow‑up, the mean \nelasticity score was significantly \nhigher for the uterine after therapy \nthan before (3.6 ± 0.3 vs 2.3 ± 0.5, \np = 0.004)\nUSE ultrasound elastography, NM normal myometrium, SE strain elastography, SWE shear wave elastography, E Young’s modulus, Cs shear wave speed, MRI ADC magnetic resonance imaging apparent diffusion coefficient \nvalues, UF uterine fibroids, UAE uterine artery embolization, AUC  area under the curve, ARFI acoustic radiation force imagine, AM adenomyosis, SR mean strain ratio mean, SR max strain ratio maximum, SR min strain ratio \nminimum. References were presented in Supplementary text\n\nPage 8 of 15Wang et al. Insights into Imaging          (2022) 13:141 \nB-mode sonography [42]. Du et al. explored the diag -\nnostic value of transvaginal SWE for endometrial pol -\nyps, endometrial hyperplasia, and endometrial cancer \nand found that the maximum value of Young’ modu -\nlus (E) was 27.28 ± 10.28  kPa in endometrial polyps, \n36.32 ± 15.04 kPa in the endometrial hyperplasia cases, \nand 86.66 ± 42  kPa in the endometrial cancer cases \n(p < 0.05). SWE can be used as an auxiliary method for \ndiagnosing and differential diagnosis of endometrial \ncancer [43]. Ma et  al. further evaluated the diagnos -\ntic value of SWE for endometrial cancer and atypical \nendometrial hyperplasia (AEH). They established a \npredictive logistic regression model to diagnose endo -\nmetrial cancer and AEH, suggesting that SWE can \nfurther diagnose endometrial cancer and AEH [44]. \nHowever, Vora et al. found no statistical difference in \nelasticity between carcinoma and AEH (p  = 0.19) [45]. \nIn a later study, the researchers measured the elastic -\nity ratio of endometrial lesions to the myometrium \n(E/M ratio), arguing that using the myometrium as an \ninternal control would more objectively describe mass \nlesions. The inconsistency in the parameters they used \nmay be the reason for the contradictory results of the \ntwo studies. (Table  2 lists studies of USE in the diagno -\nsis of endometrial lesions.) Notably, there is anisotropy \nin the uterine myometrium, and we believe that the \nindex Cs, rather than E, is more suitable to assess the \nstiffness ratio of the endometrium to the myometrium. \nZhao et  al. reported that the determination of endo -\nmetrial cancer by SWE can determine whether it has \ninvaded the myometrium and the depth of myometrial \ninvasion, which can clinically determine the surgical \nmethod and determine the prognosis [46]. Although \nthere are limited studies, the accuracy of SWE in diag -\nnosing endometrial disease is outstanding. Given its \nusefulness, we speculate that future studies may focus \non the ability of SWE to assess the depth of invasion \nand staging of endometrial cancer. More quantitative \nindicators, combined with clinical symptoms, are help -\nful for diagnosis.\nCervical tumors\nCervical cancer (CC) is only cancer with clinical staging \nin gynecology. According to FIGO, staging is the key to \nselecting treatment methods. SE and SWE have been used \nfor the differential diagnosis of CC and to assess the degree \nof invasion [47]. Fu et  al. studied SWE in CC (n  = 40), \nbenign cervical lesions (n = 40), and 40 healthy volunteers, \nand the results showed that the mean Cs of cervical can -\ncer patients were significantly higher than benign cervical \nlesions and normal cervix (p  < 0.05). The results showed \nthat SWE was more accurate than b-ultrasound in evalu -\nating vaginal fornix and uterine infiltration (p < 0.05) [46]. \nFurthermore, SWE was evaluated for uterine and vaginal \nfornix invasion, and the results showed that SWE was \nmore accurate in assessing vaginal fornix and uterine inva-\nsion than B-mode sonography only (p < 0.05) [48].\nUSE may have an important role in the early evaluation \nof chemotherapy or radiation therapy treatment efficacy \nin CC. Zhang et  al. performed SE examination in 160 \npatients with suspected CC and compared the results \nwith the pathological and clinical stages of CC. Radio -\ntherapy was used for patients confirmed as CC75 in 160 \nsuspected CC patients. The results demonstrated that SE \nhas a certain clinical value in the diagnosis and efficacy \nevaluation of CC, and its sensitivity (94.67%), specificity \n(92.94%), and diagnostic accordance rate (93.75%) [49]. \nIn 2021, Shao et al. conducted a systematic review of the \nUE application in CC and concluded that both SE and \nSWE might have important roles in the differential diag -\nnosis of CC, assessment of the degree of invasion, clinical \nstaging, and early evaluation of treatment effects [50].\nIt is well established that SE provides semiquantita -\ntive results, while SWE provides quantitative results, \nexpressed in m/s or kPa, making it difficult to compare \nSE and SWE when analyzing CC. Technologically, SWE \nis superior to SE due to its ability to evaluate the aniso -\ntropic elasticity and viscosity of cervical lesions, which \nmay help improve diagnostic performance and open \ndoors for new clinical applications [51].\nFig. 5 SWE used to display of uterus junctional zone (JZ). A Transvaginal grayscale ultrasound showed JZ appeared as a fuzzy region. B JZ in SWE \ncan be seen clearly (marked with a white arrow) and distinguished from the surrounding healthy tissue. C The endometrium is delineated, and then, \nthe JZ is delineated by shell function key and the shear wave speed (Cs) of both regions can be obtained simultaneously\n\nPage 9 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \nTable 2 Overview of the studies on USE for endometrium diseases\nUSE ultrasound elastography, EC endometrial carcinoma, AEH atypical endometrial hyperplasia, UF uterine fibroids, E/M ratio the ratio of mean elasticity of the endometrial lesion to myometrial elasticity, SE strain \nelastography, SWE shear wave elastography, SR strain ratio, E Young’s modulus, E max Young’s modulus maximum, E mean Young’s modulus mean, B/A ratio the ratio of mean elasticity of the endometrium to adjacent \nmyometrium, AUC  area under the curve, IUI intrauterine insemination. References were presented in Supplementary text\nYear Authors Patient numbers and type of lesions Type of \nelastography\nType of study Diagnostic parameters Diagnostic performance or research \nresults\nEndometrium tumors\n2022 Vora et al. [45] AEH = 11, EC = 29, Submucosal UF = 13, \nendometrial polyp = 14, Focal AM = 7\nSWE Prospective control study E, E/M ratio The elasticity of five pathologies was \nsignificant difference (p < 0.001). E mean of \nendometrial polyp was lowest (p < 0.01), \nand no significant difference was noted in \nE mean of EC and AEH (p = 0.19)\n2021 Ma et al. [44] benign lesions = 85 and EC including \nAEH = 37\nSWE Prospective case–control study E max, E mean E max and E mean were identified as inde‑\npendent risk factors for EC and AEH\n2021 Du et al. [43] Endometrial polyps = 45, AEH = 29 and \nEC = 66\nSWE Prospective diagnostic study E mean, E max, and E min E max has the highest diagnostic value \nwith the truncation values of 52.45 kPa to \ndistinguish between normal endometrium \nand EC\n2016 Gultekin et al. \n[41]\nAEH = 22, endometrial polyps = 20, and \nNU = 64\nSE Prospective control study B/A ratio AEH and endometrial polyps had signifi‑\ncantly lower B/A ratios than NU (p < 0.01); \nhowever, there is no significant difference \nbetween them (p > 0.05)\n2016 Czuczwar \net al. [42]\nendometrial polyps = 29 and submu‑\ncosal fibroids = 18\nSE Prospective diagnostic study Elastographic color map The accuracy for SE in distinguishing \nendometrial polyps and submucosal \nfibroids was 89.4% and had the highest \nproportion of correct findings(p < 0.001)\nInfertility\n2021 Kabukçu et al. \n[62]\n197 IUI cycles (148 infertility women) SE Prospective diagnostic study SR (endometrium/parametrial tissue) The SR was not different between preg‑\nnant and non‑pregnant groups (p = 0.651). \nSR was not predictive for pregnancy\n2021 Shui et al. [63] 117 of infertility and 35 of pregnancy SWE Prospective diagnostic study SR (endometrial/subendometrial areas) The AUC up to 0.949 for predicting preg‑\nnancy by using age and ultrasonographic \nfactors including uterine peristalsis, uterine \nspiral artery, and SR. The sensitivity was \n0.83, and specificity was 0.96\n2017 Swierkowski‑\nBlanchard \net al. [61]\n100 women for IUI SE Prospective diagnostic study SR The SR was significantly higher (2.4 ± 1.3 \nvs. 1.5 ± 0.7, p < 0.001) in future pregnant \nwomen\n\nPage 10 of 15Wang et al. Insights into Imaging          (2022) 13:141 \nGiven the viral etiology and its sexual transmission, \ncervical intraepithelial neoplasia (CIN) occurs mainly in \nyoung patients of reproductive age, who want to preserve \ntheir fertility [52]. In 2021, Dudia-Simon et  al. revised \nthe literature on the role of elastography in CC and CIN, \nfrom diagnosis and staging to predicting the response \nto oncologic treatment. In the meta-analysis, they share \nconsistent opinions with Shao’s review that USE can be \nused to assess normal cervical variants and positive diag -\nnosis of CC, clinical staging, and the prediction of ther -\napeutic response in CC. However, they argue that the \nmethod used to distinguish CC and CIN is not applicable \n[53]. CIN is a precursor of CC and has less pathological \nchanges than CC. There is no unique feature in USE to \ndetect CIN due to image noise, reduced resolution, and \nunclear image edge recognition [54]. Sun et al. introduced \na denoising algorithm for an intelligent bilateral filter, \nwhich has improved image quality when used in applica -\ntions. Combined with human papillomavirus (HPV) test -\ning to diagnose CIN, the results showed that the accuracy, \nsensitivity, and specificity of this new technology were \n95%, 95%, and 98%, respectively [55]. In summary, the \nbilateral filter intelligent denoising algorithm has a good \ndenoising effect on ultrasonic elastography. The USE \nimages processed by the algorithm combined with HPV \ndetection have a better diagnostic effect on CIN.\nInfertility\nDuring the menstrual cycle, major structural changes \noccur in the endometrium. When desquamated, \nthe upper, functional layer of the endometrium is \ncompletely sloughed off, followed by reconstruction \nduring the proliferative phase and then the secretory \nphase [56]. Soliman et al. showed that menopausal sta -\ntus did not significantly affect the Cs measurements by \nARFI [57]. In 2019, Manchanda et al. found that there \nwas also no significant difference in mean endometrial \nelasticity values in women at different physiological \nstages (p  = 0.176) or in different age groups (p  = 0.376) \nwhen using SWE (Fig.  6 shows the elasticity imaging \nand measurement of normal endometrium through \nSWE. Table  1 lists the studies on USE in the assess -\nment of normal endometrium) [58]. In addition, three-\ndimensional multi-frequency magnetic resonance \nelastography (MRE) combined with a multi-frequency \ndual-elastic visco-inversion method was used to meas -\nure the response of viscoelastic materials to vibration. \nThe results showed that the complex shear modulus |G \n*| and the |G *| of the endometrium were higher dur -\ning the proliferative phase (3.34 ± 0.42 kPa) than during \nthe early secretory phase (1.97 ± 0.34  kPa) in healthy \nvolunteers [59]. However, whether these differences \nreflect overall differences in the entire endometrium \nor between functional and basal endometrial layers is \nuncertain. MRE uses the magnitude of the complex \nshear modulus G, which contains both elastic and vis -\ncous components and is calculated from phase-contrast \nmultiphase pulse sequence data, while SWI measures E \nor Cs [60]. Estimations of these values depend on the \nused frequency of excitation, making a comparison of E \nor Cs reported in USE and G in MRE is challenging [60]. \nConsidering that the connective tissue surrounding \nFig. 6 SWE for normal endometrium. SWE showed a relatively uniform blue area in the proliferative endometrium (A) and secretory endometrium \n(B). Image C further showed that the region of interest was selected in endometrium 1 and myometrium 2 and that shear wave speed (Cs) were \nacquired\n\nPage 11 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \nthe extensive functional glands is very loose, this con -\ntributes to the increased softness during the secretory \nphase. MRE is costly and time-consuming; therefore, \na multicenter study with a larger sample size using the \nsame elastography technology and vendor is worth fur -\nther verifying whether SWE has significant differences \nin endometrial elasticity values in women with different \nmenstrual periods.\nThe endometrium lines the uterine cavity, implants the \nembryo, and provides the environment for the embryo to \ndevelop and grow. Swierkowski-Blanchard et al. assessed \nendometrial elasticity (using SR) before IUI and showed \nsignificantly higher SR (with stiffer myometrium) [61]. SE \nprovides a promising and innovative tool for IUI moni -\ntoring. For abnormal elasticity, appropriate strategies \n(another IUI with specific treatments, in  vitro fertiliza -\ntion, etc.) should be assessed to improve fertility out -\ncomes. However, Kabukçu et al. found that endometrial \nSR had no significant effect on pregnancy rate during \ngonadotropin-stimulated artificial insemination cycles. It \nappears that SR does not predict IUI outcomes [62]. Cur-\nrently, the efficiency of ultrasonic detection of endome -\ntrial receptivity is still inconclusive, and we believe that \nsingle parameters are unreliable in predicting pregnancy \noutcomes. Shui et  al. obtained endometrial receptivity-\nrelated factors and used logistic regression to establish \na predictive model for the probability of successful preg -\nnancy. The results showed the nomogram prediction \nmodel with its value of area under the receiver operating \ncurve (AUC) up to 0.949 for predicting pregnancy using \nage and ultrasonographic factors, including uterine peri -\nstalsis, uterine spiral artery, and ultrasound elastographic \nfeatures (overview of the studies on ultrasound elastog -\nraphy in predicting the outcome of IUI is also listed in \nTable 2) [63]. By applying a pregnancy prediction model \nof ultrasonographic factors related to endometrial recep -\ntivity, clinicians can perform quantitative assessment and \nreal-time screening of uterine conditions to provide opti -\nmal guidance, treatment, and management recommenda-\ntions for infertility-related patients.\nUSE does not predict the outcome of IUI when used \nindependently. However, using age and ultrasonographic \nfactors, including SE, uterine motility, uterine spiral \narteries, and ultrasound elastography features, can quan -\ntitatively estimate and predict pregnancy probability for \nclinicians. To date, studies using SWE to evaluate endo -\nmetrial receptivity are lacking. Considering that SWE \nhas the advantages of independent artificial pressure, \nmore objectiveness, and more repeatability, the results of \nusing SWE instead of SE to predict IUC deserve further \nexploration.\nPredicting preterm delivery\nUSE is an established method for evaluating cervical sof -\ntening, predicting pre-term delivery and outcomes of \nlabor induction [64–75]. In 2019, a meta-analysis includ -\ning 1488 pregnant indicated that cervical USE is useful \nto PTD with a summary sensitivity of 0.84 [95% confi -\ndence interval (CI): 0.68, 0.93], a specificity of 0.82 (95% \nCI: 0.63, 0.93), a diagnostic odds ratio of 25 (95% CI: 7, \n93), and AUC of USE being 0.90 (95% CI: 0.87–0.93) [76]. \nInduction of labor (IOL), a common practice in modern \nobstetrics, involves artificial labor stimulation before its \nspontaneous onset, and nearly one-quarter of all deliver -\nies require IOL [70]. A group of studies concluded that \nSWE provides a promising method for predicting the \nefficacy of IOL. Strobel et al. included 41 full-term preg -\nnancies who decided to accept IOL and SE, and assess -\nments of the Bishop score were performed before and 3 h \nafter IOL. They observed an association between strain \npatterns and SR values   at 3 h after IOL and a successful \nIOL (p = 0.0343 and p = 0.0342, respectively) that the \nresults can well demonstrate after 48  h. This is the first \nstudy to demonstrate that cervical SE after the first appli-\ncation of prostaglandins helps predict the outcome of \nIOL [77]. Another study reported that measurement by \nSE is relatively reproducible with intra-observer repro -\nducibility ICC 0.733 (95% CI 0.553–0.841) and inter-\nobserver reproducibility ICC 0.801 (95% CI 0.666–0.881) \n[78]. A comparison of SWE and Bishop score was done \nin the Lu et al. ’s study (n = 475), and outcome prediction \nmodels using inner cervical E and cervical length had \nincreased AUC compared with models using the Bishop \nscore (0.888 vs. 0.819, p = 0.009) [79]. Models based on \nSWE and cervical length had higher predictive accuracy \nthan models based on the Bishop score.\nIf a single or combined biomarker is found in predict -\ning PTB or IOL, it could reduce hospital costs and limit \ntreatment [66]. Various approaches have been reported \nin the literature to improve the application of USE in \nobstetrics. Studies have shown that SE can qualitatively \ndetect the elasticity of the cervix when using reference \nmaterials, but the application of this technique in cervi -\ncal disease has not been studied [80]. Hamza et al. sought \nto combine lower uterine segment (LUS) thickness and \nSE to predict successful IOL within 24 h and intervals to \nonset of labor. However, LUS thickness and strain values   \nwere not significant for predicting a successful IOL [81]. \nThe tissue structure of the placenta (necrosis, inflam -\nmation, and possibly histological changes) can lead to \npreterm delivery [27]. When measured by SE, placental \nstrain ratio (PSR) was inversely correlated with gesta -\ntional age at birth, which is considered a valid predictor \n\nPage 12 of 15Wang et al. Insights into Imaging          (2022) 13:141 \nof PTD. Albayraket et al. analyzed the placenta and found \nthat PSR has some promise in predicting PTD. This is \nbecause the fat-to-strain placenta ratio can be used to \nindicate PTD [82]. Tolunay et  al. conducted a prospec -\ntive study of threatened preterm labor (TPL) (n = 108) \nand measured PSR values. Multivariate logistic regres -\nsion analysis showed that when the PSR value was 4.04, \nthe sensitivity of short-term delivery time prediction was \n77.78%, and the specificity was 87.04% [83]. SE may con -\ntribute to predict delivery time in TPL high-risk pregnan-\ncies. Therefore, we believe cervical elasticity combined \nwith PSR should be beneficial for developing more effec -\ntive preventive strategies for PTB.\n5–18% of pregnant women are affected by PTD and \nit is the leading cause of neonatal death. This individu -\nalization of risk, both fetus and mother, leads to explicit \nmanagement and treatment under a precision medicine \napproach [84]. Respiratory distress syndrome (RDS) \noccurs in 26 to 30 percent of preterm neonates before \n34 weeks of gestation and 5 to 20 percent after 34 weeks \nof gestation [85]. Mottet et  al. conducted a prospec -\ntive case–control study including fetuses of uncompli -\ncated pregnancies between 24 and 34 weeks of gestation \n(n = 55) and preterm-threatening pregnancies requir -\ning corticosteroids (n = 48). SWE assessed fetal lung \nand liver elastography (LLE), and the results showed \nthat there was no difference in LLE values between the \ntwo groups at “day 0, ” but the LLE values decreased at \n“day 2” in the case group (0.2; 95% confidence interval: \n0.07–0.34; p < 0.001). The repeatability and reproducibil -\nity of the measurement were calculated, and the results \nwere acceptable [86, 87]. SWE could be considered a new \nnon-invasive, reproducible tool for monitoring fetal lung \ndevelopment by assessing mechanical properties during \npregnancy. In summary, we propose establishing a gen -\neralized risk prediction model including cervical elastic -\nity, placental elasticity, and fetal LLE ratio to develop an \nevidence-based PTD risk assessment for clinical practice.\nSummary and future prospect\nUSE diagnosis is a promising diagnostic method, but its \nclinical application is limited due to instrument limita -\ntions and different elastography parameters; for example, \nSE can only provide semiquantitative results, while SWE \ncan provide quantitative results. Given the advantages \nof SWE, the results are relatively operator-independent, \nwhile the shear wave is constant in the presence of a con-\nstant push pulse. We demonstrate that SWE is more suit-\nable for clinical application and obstetricians are trained \nto use a phantom setup and an operating manual is \nachievable.\nSWE has important application value in evaluating \ntreatment response in uterine fibroids and adenomyo -\nsis. Whether USE can distinguish uterine fibroids from \nadenomyosis and whether the changes in adenomyosis \nare stiffer or softer than normal myometrial tissue remain \ncontroversial. Since the most generally accepted theory \nis that the disease develops through an alteration or \nabsence of the JZ that causes the endometrial basal mus -\ncle to grow downward and invaginate into the myome -\ntrium, we hypothesized that measuring the SWV of the \nJZ could improve the accuracy of SWE in differentiating \nadenomyosis. This may provide new insights and poten -\ntial therapeutic target strategies for the clinical strategies \nin the management of adenomyosis.\nUSE can significantly improve the diagnostic specificity \nof cervical cancer, and it is also useful for assessing infil -\ntration the depth and stage of cervical cancer. In tumor \ntissues, stiffness is directly related to tumor development, \ninvasion, metastasis, and chemoradiotherapy resist -\nance; therefore, more research can focus on using USE \nto predict cervical cancer chemoradiotherapy treatment \nresponse. Moreover, the clinical importance of assess -\ning the cervix after cervical conization is evident in most \npatients with CIN who are of childbearing age and wish \nto preserve fertility. Since algorithmically processed USE \nimages combined with HPV detection have a better diag -\nnosis of CIN, we presumed that studying the elastic prop-\nerties of the cervix after cervical conization by this new \ntechnique has a great potential to predict future preg -\nnancies. In addition, USE is useful for assessing cervical \nsoftening and then predicting premature delivery out -\ncomes. Most studies were single-center studies, and fur -\nther larger studies are needed. Simultaneous assessment \nof cervical elasticity, placental elasticity, and fetal lung \nmaturity by SWE may predict preterm birth and neonatal \nrespiratory complications for definitive management and \ntreatment in a precision medicine approach.\nFor the foreseeable future, research into endome -\ntrial properties through USE will continue to focus on \nestablishing the relationship between endometrial stiff -\nness and fertility. With the application of SWE and the \nestablishment of models to predict fertilization and preg -\nnancy using age, uterine motility, uterine spiral arteries, \nand SWE characteristics, the clinical application of USE, \nespecially in the field of infertility, will be significantly \nenhanced.\nConclusions\nUterine stiffness is one of the important mechanical \nparameters, and some pathological processes may mani -\nfest as changes in the elasticity of uterine tissue. We \n\nPage 13 of 15\nWang et al. Insights into Imaging          (2022) 13:141 \n \nbelieve that USE, especially shear wave elastography, \nmay serve as a potential means to assess tissue stiffness, \nthereby improving the diagnosis and treatment of adeno -\nmyosis, fibroids, endometrial lesions, cervical cancer, and \nprecise management of preterm birth and intrauterine \ninsemination monitoring.\nAbbreviations\nAEH: Atypical endometrial hyperplasia; AEH: Atypical endometrial hyperplasia; \nAM: Adenomyosis; ARFI: Acoustic radiation force impulse; AUC : Area under the \nreceiver operating curve; B/A ratio: Ratio of mean elasticity of the endome‑\ntrium to adjacent myometrium; CC: Cervical tumor; CI: Confidence interval; \nCIN: Cervical intraepithelial neoplasia; E max: Young’s modulus maximum; E \nmean: Young’s modulus mean; E/M ratio: Elasticity ratio about endometrial \nlesion to myometrium ratio; E/M ratio: Ratio of mean elasticity of the endome‑\ntrial lesion to myometrial elasticity; EC: Endometrial carcinoma; GnRHa: GnRH \nagonists; HPV: Human papillomavirus; IOL: Induction of labor; IUI: Intrauterine \ninsemination; IVF: In vitro fertilization; JZ: Uterus junctional zone; LLE: Lung‑\nto‑liver elastography; LUS: Lower uterine segment; MRE: Magnetic resonance \nelastography; MRI ADC: Magnetic resonance imaging apparent diffusion \ncoefficient values; NM: Normal myometrium; PSR: Placental strain ratio; PTD: \nPredict preterm delivery; RDS: Respiratory distress syndrome; ROI: Region of \ninterest; SE: Strain elastography; SR max: Strain ratio maximum; SR mean: Strain \nratio mean; SR min: Strain ratio minimum; SR: Strain ratio; SWE: Shear wave \nelastography, Cs shear wave speed; SWI: Shear wave imaging; TE: Transient \nelastography; TPL: Threatened preterm labor; UAE: Uterine artery embolization; \nUF: Uterine fibroids; UF: Uterine fibroids; USE: Ultrasound elastography; WG: \nWeeks of gestation.\nSupplementary Information\nThe online version contains supplementary material available at https:// doi. \norg/ 10. 1186/ s13244‑ 022‑ 01274‑9.\nAdditional file 1. References for table 1 and table 2.\nAcknowledgements\nWe thank International Science Editors YPU Biotechnology for the English \nlanguage professional editing of this manuscript.\nAuthor contributions\nXW contributed to collecting data. XW and SL contributed to manuscript \npreparation/editing, literature research, and study design. SL and GL contrib‑\nuted to the final approval. All authors read and approved the final manuscript.\nFunding\nThis work was supported by the Quanzhou City Science & Technology Pro‑\ngram of China (Grant Number 2020N057s) and the Science and Technology \nBureau of Quanzhou (Grant Number 2020CT003).\nAvailability of data and materials\nNot applicable.\nDeclarations\nEthics approval and consent to participate\nNot applicable.\nConsent for publication\nNot applicable.\nCompeting interests\nThe authors declare that they have no competing interests.\nAuthor details\n1 Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical \nUniversity, No. 34 North Zhongshan Road, Quanzhou 362000, Fujian Province, \nChina. 2 Department of Clinical Medicine, Quanzhou Medical College, Quan‑\nzhou 362000, Fujian Province, China. 3 Centre of Neurological and Metabolic \nResearch, The Second Affiliated Hospital of Fujian Medical University, No. 34 \nNorth Zhongshan Road, Quanzhou 362000, Fujian Province, China. 4 Diabetes \nand Metabolism Division, Garvan Institute of Medical Research, 384 Victoria \nStreet, Darlinghurst, Sydney, NSW 2010, Australia. \nReceived: 16 April 2022   Accepted: 20 July 2022\nReferences\n 1. 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