Current Update on PET/MRI in Gynecological Malignancies—A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient’s survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.


Introduction
Gynecological malignancies are a common etiology of mortality and morbidity in women [1]. In 2022, they are estimated to be responsible for 115,130 new cases and 32,830 deaths in the United States [2]. Most of these cancers are staged using the International Federation of Gynecology and Obstetrics (FIGO) system based on clinical examination and diagnostic imaging, along with procedures such as colposcopy, cystoscopy, and rectosigmoidoscopy. For the past two decades, positron emission tomography (PET)/computed tomography (CT) has been the cornerstone for tumor staging, treatment, and recurrence. Magnetic resonance imaging (MRI) was evolving in parallel in evaluating tumor stage with its inherent soft tissue contrast, reduced radiation exposure, and high spatial resolution. MRI is employed in patients where radiation and tissue resolution are the major considerationsAt a later time, integrated PET/MRI gained popularity after 2011 and has become the research of interest. Since then, its clinical benefit has been well-studied in brain malignancies. However, it is still on the quest to confirm its importance in the rest of the cancers. MRI has the propensity to complement metabolic tumor evaluation obtained through PET imaging. The synchronous acquisition of anatomic layout on MRI and functional data on PET can enhance soft tissue assessment and characterization [3]. In addition, the tissue density on diffusion weighted imaging facilitates the local tumor invasion and distant metastatic spread. In this article, we elaborate on the basic technical outline, utility, advantages, and limitations of PET/MRI in gynecological malignancies.

Technical Background
A streamlined and competent workflow is necessary for the well-established recognition of PET/MRI in routine practice. The provider must be aware of the imaging modality and its lucrative benefits in specific disease populations. It must be followed by appropriate scheduling and proper communication between PET/MRI technologists and radiopharmacists. Once the imaging is scheduled, the pertinent protocol should be selected by Over the past two decades, PET/CT has been the standard for evaluating oncologic conditions. In most institutions, the CT component is performed using a low-dose CT scan without contrast administration. However, such practice may result in poor tumor delineation, particularly in the case of pelvic malignancies. PET/MRI provides excellent tumor evaluation and metabolic information from the PET component. The currently available PET/MRI units have a 3-T magnet paired with PET detectors that can coexist and function with the MRI's strong magnetic fields ( Table 2). There are three major types of PET/MRI scanners: (i) Trimodal, (ii) Sequential, and (iii) Integrated systems. The trimodal system involves separate image acquisition through PET/CT and MRI scanners and software-based registration of acquired images. It allows the standard CT-based attenuation correction of the PET images. However, the limitations include potential misregistration due to patient transportation requirements and involuntary patient motion between the separate image acquisitions and the increased scanner space to accommodate the PET/CT and MRI. The sequential system can be described as the different PET and MRI acquisitions in the same room that contains a table that moves in a single track across the two scanners. Its advantage over the trimodal system is that it does not require the patient to be transported to an entirely different room.

Imaging
Although the previous FIGO classifications did not include the imaging criteria for tumor staging, the 2018 classification has permitted the utility of imaging, which enabled better tumor assessment and staging [5,9,10]. The FIGO staging was based on clinical evaluation due to a limited access to imaging in low-income countries with high cervical cancer prevalence [11]. However, clinical staging is suboptimal for certain tumor characteristics such as size, parametrial invasion, and lymph node involvement. In patients with early-stage cervical cancer (IA and part of IB1), the microinvasion is only detectable using tissue evaluation [12]. The rest of the tumor stages, including local extension, can be assessed using reliable imaging modalities such as CT, MRI, and PET/CT, which have higher sensitivity and comparable specificity to the clinical evaluation [13,14]. The National Comprehensive Cancer Network 2022 Practice Guidelines in Oncology recommended CT or PET/CT for tumor surveillance and follow-up, and MRI for the local assessment of the stage ≥ IB1 [11,15]. Staging is essential to predict survival, and surgical planning is considered standard management for early-stage (≤IIA) cervical cancers [16]. Nguyen et al. compared PET/CT and PET/MRI and found that both modalities could identify all the primary and metastatic lesions and could strongly correlate standardized uptake value (SUV) (p = 0.03) [15] (Figure 1). characteristics such as size, parametrial invasion, and lymph node involvement. In patients with early-stage cervical cancer (IA and part of IB1), the microinvasion is only detectable using tissue evaluation [12]. The rest of the tumor stages, including local extension, can be assessed using reliable imaging modalities such as CT, MRI, and PET/CT, which have higher sensitivity and comparable specificity to the clinical evaluation [13,14]. The National Comprehensive Cancer Network 2022 Practice Guidelines in Oncology recommended CT or PET/CT for tumor surveillance and follow-up, and MRI for the local assessment of the stage ≥ IB1 [11,15]. Staging is essential to predict survival, and surgical planning is considered standard management for early-stage (≤IIA) cervical cancers [16]. Nguyen et al. compared PET/CT and PET/MRI and found that both modalities could identify all the primary and metastatic lesions and could strongly correlate standardized uptake value (SUV) (p = 0.03) [15] (Figure 1). In general, diffusion weighted imaging (DWI) is considered sensitive to assessing parametrial involvement. It has high false-positive rates if the patients have large tumor sizes or a superimposed infections. Imaging must be highly specific to demonstrate the local tumor invasion since the curative surgery can be performed based on the parametrial invasion [16]. Moreover, identifying stromal, ovarian, or corpus invasion is crucial as they are risk factors for lymphovascular space invasion (LVSI) and para-aortic lymph nodal metastases [17,18].
The successful integration of PET and MRI enabled tumor evaluation and staging in a "one-stop" approach. In a study by Steiner et al., PET/MRI has proven to have a benefit over MRI with an Area Under Curve (AUC) of 0.85 vs. 0.74 for vaginal invasion and 0.89 vs. 0.73 for parametrial invasion [16]. Similar findings were observed in the study by Sarabhai et al., who reported that PET/MRI and MRI are similar in characterizing the Tstage of the tumor (85% vs. 87%) [19]. Wang et al. reported that PET/MRI has a sensitivity, specificity, and negative predictive value (NPV) of 78.5%, 64.9%, and 74.5%, respectively, compared to MRI [20]. PET/MRI characterizes the parametrial invasion with a sensitivity and specificity of 90% and 94% [20]. Kitajima et al. reported a diagnostic accuracy of 83% compared to MRI alone in a study comprising 30 patients [21].
All the studies above were based on morphological observations on PET/MRI. Instead, Wang et al. quantified the gray level values to evaluate the parametrial invasion. They reported that high gray values corresponded to the higher FIGO stages (p < 0.05); hence, this quantification technique is practical to implement in clinical practice [20]. Wang et al. described the sensitivity, specificity, and NPV of combined PET/MRI+ gray values as 87%, 84%, and 86%, respectively, compared to MRI or PET/MRI alone, in assessing parametrial invasion (p < 0.05) [20].
The tumor cells drain from the cervix, through the lymphatic vessels, into parametrial lymph nodes, pelvic sidewall nodes, external and internal iliac nodes, and para-aortic In general, diffusion weighted imaging (DWI) is considered sensitive to assessing parametrial involvement. It has high false-positive rates if the patients have large tumor sizes or a superimposed infections. Imaging must be highly specific to demonstrate the local tumor invasion since the curative surgery can be performed based on the parametrial invasion [16]. Moreover, identifying stromal, ovarian, or corpus invasion is crucial as they are risk factors for lymphovascular space invasion (LVSI) and para-aortic lymph nodal metastases [17,18].
The successful integration of PET and MRI enabled tumor evaluation and staging in a "one-stop" approach. In a study by Steiner et al., PET/MRI has proven to have a benefit over MRI with an Area Under Curve (AUC) of 0.85 vs. 0.74 for vaginal invasion and 0.89 vs. 0.73 for parametrial invasion [16]. Similar findings were observed in the study by Sarabhai et al., who reported that PET/MRI and MRI are similar in characterizing the T-stage of the tumor (85% vs. 87%) [19]. Wang et al. reported that PET/MRI has a sensitivity, specificity, and negative predictive value (NPV) of 78.5%, 64.9%, and 74.5%, respectively, compared to MRI [20]. PET/MRI characterizes the parametrial invasion with a sensitivity and specificity of 90% and 94% [20]. Kitajima et al. reported a diagnostic accuracy of 83% compared to MRI alone in a study comprising 30 patients [21].
All the studies above were based on morphological observations on PET/MRI. Instead, Wang et al. quantified the gray level values to evaluate the parametrial invasion. They reported that high gray values corresponded to the higher FIGO stages (p < 0.05); hence, this quantification technique is practical to implement in clinical practice [20]. Wang et al. described the sensitivity, specificity, and NPV of combined PET/MRI+ gray values as 87%, 84%, and 86%, respectively, compared to MRI or PET/MRI alone, in assessing parametrial invasion (p < 0.05) [20].
The tumor cells drain from the cervix, through the lymphatic vessels, into parametrial lymph nodes, pelvic sidewall nodes, external and internal iliac nodes, and para-aortic nodes [22]. Around 10-30% of patients with cervical cancer demonstrate pelvic lymph node metastases (LNM) during an early stage. This reduces the 5-year survival rate from 94.1% (negative LNM) to 64.1% (positive LNM) [23]. Accurate lymph nodal assessment is essential for developing the individualized treatment algorithm, enhancing the prognosis, and reducing mortality. According to FIGO 2018 classification, micro-or macro-metastases to the lymph nodes are staged as IIIC regardless of tumor size or extent [24]. CT and MRI are less sensitive and specific in detecting metastatic lymph nodes, as they cannot differentiate metastatic from non-metastatic lymph nodes [25,26]. The combined PET/CT was studied, which showed high sensitivity (91% vs. 37.3%) and diagnostic accuracy (98% vs. 95%) compared to MRI (p < 0.034), and hence is recommended by the National Comprehensive Cancer Network clinical guidelines [26,27]. However, the PET is limited by identifying small lymph nodal metastases of size < 5 mm [28]. Later, PET/MRI was found to have improved diagnostic confidence over PET/CT with the advantage of a reduced radiation dose [29] (Figure 2). PET/MRI has a sensitivity, specificity, and diagnostic accuracy of 91%, 94%, and 93% in detecting nodal metastases [15]. Compared to PET/CT, PET/MRI identifies nodal metastases with a sensitivity, specificity, and accuracy of 92.3%, 88.2%, and 90%, respectively [21]. node metastases (LNM) during an early stage. This reduces the 5-year survival rate from 94.1% (negative LNM) to 64.1% (positive LNM) [23]. Accurate lymph nodal assessment is essential for developing the individualized treatment algorithm, enhancing the prognosis, and reducing mortality. According to FIGO 2018 classification, micro-or macro-metastases to the lymph nodes are staged as IIIC regardless of tumor size or extent [24]. CT and MRI are less sensitive and specific in detecting metastatic lymph nodes, as they cannot differentiate metastatic from non-metastatic lymph nodes [25,26]. The combined PET/CT was studied, which showed high sensitivity (91% vs. 37.3%) and diagnostic accuracy (98% vs. 95%) compared to MRI (p < 0.034), and hence is recommended by the National Comprehensive Cancer Network clinical guidelines [26,27]. However, the PET is limited by identifying small lymph nodal metastases of size < 5 mm [28]. Later, PET/MRI was found to have improved diagnostic confidence over PET/CT with the advantage of a reduced radiation dose [29] (Figure 2). PET/MRI has a sensitivity, specificity, and diagnostic accuracy of 91%, 94%, and 93% in detecting nodal metastases [15]. Compared to PET/CT, PET/MRI identifies nodal metastases with a sensitivity, specificity, and accuracy of 92.3%, 88.2%, and 90%, respectively [21]. Cervical cancer is one of the tumors that demonstrate heterogeneity to hypoxia. Narva et al. studied the association between hypoxia and increased resistance to chemotherapy and radiotherapy in patients with SCC of the cervix [30,31]. In addition, the cancerous cells adapt to the hypoxic microenvironment, leading to genetic instability, DNA damage, and mutagenesis. This results in a rapid tumor invasion to the adjacent and distant organs. 18 Fluorine-labeled 2-(2-nitro-1-H-imidazol-1-y)-N-(2,2,3,3,3-pentafluoropropyl)-acetamide ( 18 F-EF5) is a hypoxia radiotracer that can be used in PET imaging. Increased uptake of 18 F-EF5 is strongly associated with poor prognosis compared to (18)Ffluorodeoxyglucose ( 18 F-FDG) uptake. Narva et al. reported that an increased 18 F-EF5 uptake on 18 F-EF5-PET/MRI correlates with hypoxia intensity, which is proportional to the tumor stage [30].
Radiotherapy is the cornerstone in the management of patients with cervical cancer. Around 25% of cervical cancer cases recur, and 24% among those are observed in alreadytreated patients, which points to the importance of identifying the radio-resistant tumor areas that may be managed with radiation dose escalation. A new PET tracer 68 Ga-NODAGA-E[c(RGDyK)]2 ([ 68 Ga] (Ga-RGD)) identifies the αvβ3, an integrin that is found Cervical cancer is one of the tumors that demonstrate heterogeneity to hypoxia. Narva et al. studied the association between hypoxia and increased resistance to chemotherapy and radiotherapy in patients with SCC of the cervix [30,31]. In addition, the cancerous cells adapt to the hypoxic microenvironment, leading to genetic instability, DNA damage, and mutagenesis. This results in a rapid tumor invasion to the adjacent and distant organs. 18 Fluorine-labeled 2-(2-nitro-1-H-imidazol-1-y)-N-(2,2,3,3,3-pentafluoropropyl)-acetamide ( 18 F-EF5) is a hypoxia radiotracer that can be used in PET imaging. Increased uptake of 18 F-EF5 is strongly associated with poor prognosis compared to (18)F-fluorodeoxyglucose ( 18 F-FDG) uptake. Narva et al. reported that an increased 18 F-EF5 uptake on 18 F-EF5-PET/MRI correlates with hypoxia intensity, which is proportional to the tumor stage [30].
Radiotherapy is the cornerstone in the management of patients with cervical cancer. Around 25% of cervical cancer cases recur, and 24% among those are observed in already-treated patients, which points to the importance of identifying the radio-resistant tumor areas that may be managed with radiation dose escalation. A new PET tracer 68 Ga-NODAGA-E[c(RGDyK)]2 ([ 68 Ga] (Ga-RGD)) identifies the α v β 3 , an integrin that is found on the newly formed vasculature. Pelvic insufficiency fractures (PIF) are a late complication of radiotherapy, and Sapienza et al. studied the incidence of PIF in patients who underwent radiotherapy for various gynecologic cancers [32]. They found that 10-18% of patients are affected by PIF, with the sacrum as the most common fracture site [32]. Azumi et al. noticed PIF in 20% of patients with cervical cancer treated with radiotherapy [33]. They also demonstrated that PET/MRI discovers PIF earlier than PET/CT (p <0.05), with the added advantage of reduced radiation exposure [33]. The earliest sign of PIF is medullary edema, which can be observed as T1 hypointense and T2 hyperintense on MRI as early as 18 days after the symptom onset [33].
The maximum standardized uptake value (SUV max ) derived from [ 18 F] FDG-PET and diffusion metrics such as the apparent diffusion coefficient (ADC) from the MRI are studied as the prognostic indicators in patients with cervical cancer [31,[34][35][36][37][38][39][40]. Many studies reported that SUVmax and ADC minimum (ADC min ) values of cervical cancer are inversely related. Olsen et al. also described reduced ADC value in intense SUV max [41]. In addition, the SUVmax was seen to vary based on the histology and degree of differentiation of cervical cancer, and this feature aided in the prognostication [42]. SCC of the cervix is found to have higher SUV max values than the non-squamous tumors (p = 0.153), and poorly differentiated ones have higher SUVmax than do the well-differentiated tumors (p = 0.0474) [42]. The underlying reason for the difference in SUVmax is secondary to the degree of Glucose Transporter (Glut) expression that aids in FDG uptake; however, it still needs to be validated through further studies [43,44].
The simultaneous acquisition of PET/MRI provides precise spatial correlation and a more appropriate insight into the imaging biomarkers on the voxel level. The inverse correlation between SUV mean , SUV max , and ADC min was also supported by Brandmaier et al. on hybrid PET/MRI. The correlations between SUV mean and ADC min (r = −0.403) and SUV max and ADC min (r = −0.532) were significant in primary cervical tumors [45]. The authors demonstrated a stronger correlation between SUV mean and ADC min (r = 0.773) and SUV max and ADC min (r = −0.747) in the case of recurrent cervical tumors [45]. Grueneisen et al. reported significant SUVmax and ADC min in primary tumors but not the recurrent cervical tumors [46]. Later, Ho et al. described no correlation among SUV max , SUV mean , ADC min , or ADC mean . However, they found that the ratio of ADC min /ADC mean (relative admin) and the ratio of SUV max and SUV mean (relative SUV max ) correlated well with the adenoand adenosquamous carcinoma of the cervix (r = −0.685) and with the well-to moderately differentiated tumors (r = −0.631) [47]. No significant correlation between relative SUVmax and relative ADC min was found in squamous cell carcinoma and poorly differentiated tumors [47]. Surov et al. studied the SUV and ADC parameters and their relation with the KI 67 proliferation index [48]. They found that SUVmax (r = 0.59), SUV mean (r = 0.45), SUV max /ADC min (r = 0.71), SUV max /ADC mean (r = 0.75), and ADC min (r = −0.48) correlated significantly with the KI 67 proliferative index, thereby reflecting the tumor proliferation rate [48]. Additionally, SUV mean (r = 0.71) and SUV max (r = −0.71) strongly correlate with epithelial and stromal areas and locate the metabolically active areas [48]. In addition to SUV and ADC, the other parameters include metabolic tumor volume (MTV) and total lesion glycolysis (TLG). It has been studied that these parameters conventionally correlate with the SCC antigen levels, FIGO staging, tumor size, and depth of stromal invasion [49,50]. Tables 3 and 4 summarize the essential characteristics of PET/MRI studies in cervical and pelvic malignancies.  Retrospective analysis resulting in selection bias; Small sample size; No evaluation between multiple observers. 6 Narva et al. [30] 2021 Prospective 9 To evaluate the correlation between PET/MRI imaging ( 18 F-EF5) and endogenous hypoxia (such as HIF1, CAIX, and GLUT1) tracers.
Small sample size; the chemistry of EF5 is complex, which may limit its broad application. 7 Brandmaier et al. [

Epidemiology
Cancer of the uterine corpus comprises endometrial and myometrial cancers [65,66]. The majority of the tumors are adenocarcinomas from the endometrium and sarcomas from the myometrium. Around 65,950 new cases and 12,550 deaths due to cancer of the uterine corpus are estimated in 2022 by the American Cancer Society [2]. These cancers are often referred to as endometrial cancer, as >90% of the cases demonstrate malignancy in the endometrial lining [65]. It is observed among 7% of cancer patients [66].

Classification
Of all the endometrial carcinoma histologies, endometroid adenocarcinoma accounts for 75% of the endometrial cancers, while mixed, uterine papillary serous, clear cell, carcinosarcoma, mucinous, squamous cell, and undifferentiated comprise 10%, <10%, 4%, 3%, 1%, <1%, and <1%, respectively [66]. Endometrial cancer can be classified as type I (80-90% of cases) and type II (10-20% of cases) carcinomas [67]. Type I is low-grade (grades 1 and 2) endometroid adenocarcinoma arising from complex atypical hyperplasia and is secondary to unopposed estrogen exposure. Type II arises from atrophic endometrium and comprises high-grade endometroid adenocarcinoma (grade 3) and nonendometroid histologies. Type II tumors are clinically aggressive and associated with poor prognosis. FIGO staging of the cancer also plays a vital role in estimating the prognosis. The "new risk groups to guide adjuvant therapy use" were described during the recent conference European Society for Medical Oncology-European Society of Gynecological Oncology-European Society for Radiotherapy and Oncology (ESMO-ESGO-ESTRO) [68]. The consensus stratified stages IA of grades 1-2 and IB endometroid adenocarcinomas of grades 1-2 without LVSI as low and intermediate risk groups. At the same time, Stage ≥ II, grade 3 endometroid adenocarcinomas, with LVSI, or non-endometroid tumors, are categorized under high-intermediate or higher risk groups [69]. The 5-year overall survival (OS) for Stages I, II, III, and IV ranges between 85 and 90%, 75 and 85%, 50 and 56%, and 20 and 25%, respectively [67].

Imaging
The role of imaging-derived biomarkers in endometrial cancer was discussed at the ESMO-ESGO-ESTRO consensus conference, highlighting the relevance of imaging in surgery planning [68]. Integrated PET/MRI has been studied to identify cancer prognosis through the individual biomarkers (i) SUV and (ii) ADC. The increased SUV on the PET scan indicates the tumor's strong glucose metabolism and represents the tumor's aggressiveness. The ADC value on DWI is obtained based on the diffusion of the water molecules. Its value is reduced in the tumor tissue secondary to high cellularity. Shih et al. described the inverse correlation between SUV max and ADC min and reported that these components are associated with poor pathological prognostic factors [70]. A more recent study by Tsuyoshi et al. reported that SUV cannot differentiate between low-and high-risk endometrial cancers and cannot be relied on to establish the prognosis. The same study demonstrated that lower ADC values (p < 0.05) and a higher SUV-to-ADC ratio (p < 0.005) are associated with an increased risk of cancers. An SUV-to-ADC ratio of 16.9 × 109 predicts tumor aggressiveness with a sensitivity, specificity, and accuracy of 73%, 81%, and 77%, respectively [69].
The depths of myometrial invasion and lymphovascular space invasion (LVSI) aid in the extent of the surgical intervention [71]. With its enhanced soft tissue evaluation, MRI provides information on the importance of myometrial involvement. The PET imaging assesses the LVSI and correlates well with endometrial tumor prognosis. Combined PET/MRI has been shown to possess an excellent positive predictive value to evaluate both myometrium and LVSI [67]. Ironi et al. reported that PET/MRI has a sensitivity, specificity, accuracy, PPV, and NPV of 85%, 92%, 91%, 75%, and 96%, respectively, in detecting LVSI [67]. At the same time, the parameters were 72%, 84%, 77%, 88%, and 64%, respectively, in the evaluation of the myometrial invasion [67]. The conventional entire field of view (fFOV) DWI is usually performed by single-shot echo-planar imaging (ssEPI). To focus on the region of interest (ROI), a reduced FOV (rFOV) ssEPI technique termed as an optimized and constrained undistorted single shot (FOCUS) is described using the spatial radiofrequency pulse signals that are limited to the ROI [72]. A study by Ota et al. reported that the high-resolution rFOV DWI, compared to fFOV DWI, has fewer distorted images, with enhanced image quality and diagnostic performance to evaluate the deep myometrial invasion of endometrial cancer [72]. Table 5 summarizes the essential characteristics of PET-MRI studies in endometrial malignancies.

Signa 3-T PET/MRI scanne
Lower ADC values (p < 0.05) and higher SUV-to-ADC ratio (p < 0.005) are associated with high-risk cancers more than low-risk cancers. In turn, the SUV-to-ADC ratio demonstrated higher diagnostic accuracy and higher AUC values (p < 0.05); The SUV-to-ADC ratio cut-off value of 16.9 × 10 9 has a sensitivity, specificity, and accuracy of 73%, 81%, and 77%, respectively, in predicting high-risk cancer groups.
Small sample size; Mean SUV and ADC values at the center of the lesion were considered. 6 Bezzi et al. [76] 2021

Systematic review and metaanalysis
To study the role of PET/MRI in staging and re-staging of endometrial cancer.
PET/MRI has the highest diagnostic accuracy in detecting the soft-tissue involvement and metastases. SUV to ADC ratio seems to be a more reliable index to describe the aggressiveness of endometrial cancer; PET/MRI detects the post-therapeutic changes of the lesion and even small recurrent lymph node lesions.
Small cohort study; Heterogeneous patient population.

Epidemiology
Ovarian cancer is the fifth leading cause of cancer-related deaths in women and accounts for 2.1% of all cancer-related deaths [78,79]. It is usually diagnosed in women aged ≥63 years and is more common in white than African American women [78]. Approximately 1 in every 78 women is at risk of ovarian cancer [78]. According to 2022 cancer statistics, around 19,880 new cases and 12,810 ovarian cancer deaths are estimated to occur in the United States [7]. This incidence has reduced by 1-2% per year between 1990 and 2010. However, it has increased by 3% annually from 2010 to 2018 [7]. Only 19% of ovarian cancers are discovered at an early localized stage and are associated with a 5-year survival rate of 93% [7]. The rest of the patient population has often delayed presentation due to the silent nature of the disease, which is responsible for a reduced 5-year survival rate in the same population (49%) [7]. Age is another critical factor that affects the survival rate. The survival rate is 61% in women aged <65 compared to 33% in women aged ≥65 [7].

Imaging
Imaging plays a crucial role in the management of ovarian cancer. Ultrasound (US) provides basic information on the presence of an ovarian mass and demonstrates the benign or malignant features. It is a sensitive imaging modality (97%). However, it lacks specificity (71%), which may lead to unnecessary surgical intervention [84,85]. CT is the next imaging modality that provides decisive interpretation regarding tumor staging, treatment response, and recurrence. It also aids in identifying lymph node and organ metastasis with superior sensitivity than US.
As per the European Society of Urogenital Radiology (ESUR), MRI and contrastenhanced MRI are the alternative modalities in patients with indeterminate adnexal lesions in US and CT [86,87]. It has a sensitivity, specificity, and accuracy of 83%, 84%, and 83%, compared to CT or US, in evaluating indeterminate ovarian lesions [88]. These values increase to 95%, 98%, and 97%, respectively, if the ADNEX MR scoring system is used to evaluate the adnexal lesions [89]. The ADNEX MR scoring system is the standard of imaging evaluation, similar to the Breast Imaging Report Data System (BI-RADS). The lymph node or distant organ metastases can be easily identified on 18F-FDG-PET/CT compared to US, CT, or MRI. However, the false-positive reports are higher due to the increased uptake of the FDG by the normal ovaries in the late follicular to early luteal phase [90,91]. In addition, FDG-PET/CT has low diagnostic value in differentiating early low-grade carcinoma and borderline tumor due to the low FDG uptake, which results in a false-negative value [90].
Combined, PET/MRI has proven to be helpful in the characterization of ovarian tumors with a sensitivity, specificity, PPV, and NPV of 94%, 100%, 100%, and 83%, respectively, compared to individual PET/CT and MRI [92] (Figure 3). The fusion PET/MRI is superior to PET/CT due to the excellent soft tissue resolution, which aids in identifying even minute hypermetabolic tumor masses. Similar results were reported by Fiaschetti et al., who described the sensitivity and specificity of MRI, PET/CT, and PET/MRI as 84% and 60%, 74% and 80%, and 94% and 100%, respectively [92]. However, a study by Tsuyoshi et al. reported that PET/MRI has similar efficacy to contrast-enhanced CT or contrast-enhanced MRI in determining the T-stage of the ovarian tumor [93]. The same study described PET/MRI as superior to contrast-enhanced CT in the M-staging and which can be used as an alternative [93].
Cytoreductive surgery is the standard of care for patients with ovarian cancer [86]. In patients where complete debulking is not feasible, neoadjuvant chemotherapy (NAC) and interval debulking surgery are the optimal therapeutic choices. The response of the tumor to NAC is assessed by monitoring the CA-125 levels before and after the NAC [94]. PET/CT has a proven benefit in predicting the treatment response by measuring before and after the NAC [95]. However, the role of PET/MRI has been established to assess the tumor response in cervical cancer, and its capability is questionable in the case of ovarian tumors [93]. Tables 6 and 7 summarize essential characteristics of PET-MRI studies in ovarian and gynecological malignancies. even minute hypermetabolic tumor masses. Similar results were reported by Fiaschetti et al., who described the sensitivity and specificity of MRI, PET/CT, and PET/MRI as 84% and 60%, 74% and 80%, and 94% and 100%, respectively [92]. However, a study by Tsuyoshi et al. reported that PET/MRI has similar efficacy to contrast-enhanced CT or contrastenhanced MRI in determining the T-stage of the ovarian tumor [93]. The same study described PET/MRI as superior to contrast-enhanced CT in the M-staging and which can be used as an alternative [93]. Cytoreductive surgery is the standard of care for patients with ovarian cancer [86]. In patients where complete debulking is not feasible, neoadjuvant chemotherapy (NAC) and interval debulking surgery are the optimal therapeutic choices. The response of the tumor to NAC is assessed by monitoring the CA-125 levels before and after the NAC [94].    Around 80% of patients respond well to debulking surgery and NAC [101]. Unfortunately, 75% of these patients relapse within two years [101]. The recurrence rate also depends on the tumor's initial stage and is 10%, 30%, 70-90%, and 90-95% in patients with Stages I, II, III, and IV ovarian cancer [102]. Early recognition of the recurrence is essential in planning the optimal treatment, and PET/MRI has proven to have an excellent diagnostic performance in recurrence detection. In a meta-analysis by Zheng et al., PET/MRI had a sensitivity and specificity of 96% and 95% in restaging patients suspected of having a pelvic malignancy recurrence, including ovarian tumors [103]. Specific to ovarian malignancies, PET/MRI has comparable sensitivity, specificity, and accuracy to contrast-enhanced CT in determining the recurrence (100%, 100%, and 100%, respectively, vs. 89%, 100%, and 91%, respectively) [93].

Challenges
Physiologic variations in FDG uptake may mimic disease, resulting in misdiagnosis or inaccurate staging. Conditions such as seromas, abscesses, ovarian hyperstimulation, and fibroids can cause false results. The assessment of lung metastases can be challenging in PET/MRI. Chandarana et al. reported that MRI with simultaneously acquired PET data has high sensitivity in detecting FDG-avid lung nodules (70.3% vs 61.6%, p = 0.002) and nodules with a diameter of at least 0.5 cm (81.8%) [104]. Acquiring PET/MRI requires technologists to have dual training in PET and MRI. Having two technologists present, each with one of these two proficiencies, may solve this problem, but will be costlier. Another issue relates to the lack of reimbursement for PET/MRI services. There are also no specific Current Procedural Terminology (CPT ® ) codes for PET/MRI for reimbursement. As such, this requires submitting individual codes for whole-body PET and MRI.

Clinical Trials and Metanalysis
A list of the currently ongoing clinical trials regarding the diagnostic utility of PET/MRI in gynecological malignancies can be found in Table 8. These trials are recruiting participants as of the time of writing this manuscript and hopefully will provide better larger-scale data regarding the use of PET/MRI in such patients. Few metanalyses studies have also been conducted with encouraging results, as mentioned in Table 9. The accuracy of lesion detection will be summarized by modality using frequencies and percentages. The McNemar test will be utilized to compare the accuracies of PET/MRI and ceCT.
Other diagnostic metrics (sensitivity, specificity, positive predictive value, and negative predictive value), and 95% confidence intervals will be estimated. The effect of patient and tumor characteristics on diagnostic precision will be evaluated using a logistic regression model. Diagnostic accuracy by location will be analyzed using linear regression or generalized linear regression models where applicable. Where applicable, response status will be analyzed using linear regression or generalized linear regression models.
Imaging and genomic data analysis correlation between imaging and genomic data will be analyzed using linear regression or generalized linear regression models where applicable.  The diagnostic accuracy of the Positron Lymphograph will be defined in terms of sensitivity and will consist of a pathology review of labeled, excised specimens compared with lymph node imaging data acquired preoperatively.
To evaluate several standard uptake values (SUV) (18F-FDG avidity), they will assess the ability of SUV to predict malignant disease. The continuous variable of SUV assigned to a given lymph node during Positron Lymphography will be compared with each labeled lymph node's pathologic assessment (benign vs. malignant). The SUV assigned to a given lymph node is performed using imaging software and is not up to the radiologist's discretion.

Future Directions
Recently, it has been reported that ADC value does not accurately reflect the diffusion of water molecules, as it is based on just a Gaussian distribution model [108]. Hence, diffusion kurtosis imaging (DKI) has been developed, which measures the non-Gaussian distribution, thereby reflecting the tissue microstructure [108]. The application of DKI has been well-studied in gliomas, prostate cancers, and hepatic fibrosis [109]. A pilot study by Wang et al. demonstrated that DKI has the ability to differentiate the stage and grade of uterine cervical cancer [110]. In patients with endometrial cancer, Chen et al. and Yue et al. have proven that DKI is more feasible than DWI in distinguishing high from low grade endometrial cancers [111,112]. Among patients with ovarian tumors, although DKI correlates with Ki-67 expression, it did not demonstrate any added advantage over DWI in a study by Li et al. [113]. As the DKI is still a research tool and only few studies support its application, it is at a stage where it can be analyzed in a broader clinical setting.
Machine learning (ML) is another revolutionary concept in the oncological field. It is a subset of artificial intelligence and aids in the diagnosis, treatment, prognosis, and clinical decision making of various cancer types. Multiple ML algorithms have been reviewed in gynecologic oncology. For instance, Lawresnon et al. studied ML in elucidating the cellular origin of HGSC [114]. Authors identified that HGSC has a dual cellular origin from ovarian surface epithelial and fallopian secretory epithelial cells [114]. ML predicts the prognosis and stratifies the high-risk patients diagnosed with cervical or