Diagnostic performance of PET/CT and PET/MR in the management of ovarian carcinoma-a literature review

Application of medical imaging in ovarian cancer: a bibliometric analysis from 2000 to 2022

Background

Ovarian cancer (OC) is the most lethal tumor within the female reproductive system. Medical imaging plays a significant role in diagnosis and monitoring OC. This study aims to use bibliometric analysis to explore the current research hotspots and collaborative networks in the application of medical imaging in OC from 2000 to 2022.

Methods

A systematica search for medical imaging in OC was conducted on the Web of Science Core Collection on August 9, 2023. All reviews and articles published from January 2000 to December 2022 were downloaded, and an analysis of countries, institutions, journals, keywords, and collaborative networks was perfomed using CiteSpace and VOSviewer.

Results

A total of 5,958 publications were obtained, demonstrating a clear upward trend in annual publications over the study peroid. The USA led in productivity with 1,373 publications, and Harvard University emerged as the most prominent institution with 202 publications. Timmerman D was the most prolific contributor with 100 publications, and Gynecological Oncology led in the number of publications with 296. The top three keywords were "ovarian cancer" (1,256), "ultrasound" (725), and "diagnosis" (712). In addition, "pelvic masses" had the highest burst strength (25.5), followed by "magnetic resonance imaging (MRI)" (21.47). Recent emergent keywords such as "apoptosis", "nanoparticles", "features", "accuracy", and "human epididymal protein 4 (HE 4)" reflect research trends in this field and may become research hotspots in the future.

Conclusion

This study provides a comprehensive summary of the key contributions of OC imaging to field's development over the past 23 years. Presently, primary areas of OC imaging research include MRI, targeted therapy of OC, novel biomarker (HE 4), and artificial intelligence. These areas are expected to influence future research endeavors in this field.

The OCDA-Net: a 3D convolutional neural network-based system for classification and staging of ovarian cancer patients using [18F]FDG PET/CT examinations

OBJECTIVE

To create the 3D convolutional neural network (CNN)-based system that can use whole-body [18F]FDG PET for recurrence/post-therapy surveillance in ovarian cancer (OC).

METHODS

In this study, 1224 image sets from OC patients who underwent whole-body [18F]FDG PET/CT at Kowsar Hospital between April 2019 and May 2022 were investigated. For recurrence/post-therapy surveillance, diagnostic classification as cancerous, and non-cancerous and staging as stage III, and stage IV were determined by pathological diagnosis and specialists' interpretation. New deep neural network algorithms, the OCDAc-Net, and the OCDAs-Net were developed for diagnostic classification and staging of OC patients using [18F]FDG PET/CT images. Examinations were divided into independent training (75%), validation (10%), and testing (15%) subsets.

RESULTS

This study included 37 women (mean age 56.3 years; age range 36-83 years). Data augmentation techniques were applied to the images in two phases. There were 1224 image sets for diagnostic classification and staging. For the test set, 170 image sets were considered for diagnostic classification and staging. The OCDAc-Net areas under the receiver operating characteristic curve (AUCs) and overall accuracy for diagnostic classification were 0.990 and 0.92, respectively. The OCDAs-Net achieved areas under the receiver operating characteristic curve (AUCs) of 0.995 and overall accuracy of 0.94 for staging.

CONCLUSIONS

The proposed 3D CNN-based models provide potential tools for recurrence/post-therapy surveillance in OC. The OCDAc-Net and the OCDAs-Net model provide a new prognostic analysis method that can utilize PET images without pathological findings for diagnostic classification and staging.

Diagnostic performance of noninvasive imaging using computed tomography, magnetic resonance imaging, and positron emission tomography for the detection of ovarian cancer: a meta-analysis

OBJECTIVE

The aim of this meta-analysis was to compare the diagnostic value of noninvasive imaging methods computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) in the detection of ovarian cancer (OC).

METHODS

PubMed, Embase, and Ovid were comprehensively searched from the date of inception to 31st, March, 2022. Pooled sensitivity, specificity, positive likelihood ratio (+ LR), negative likelihood ratio (- LR), diagnostic odds ratio (DOR), and area under the curve (AUC) of summary receiver operating characteristic (SROC) with their respective 95% confidence intervals (CIs) were calculated.

RESULTS

Sixty-one articles including 4284 patients met the inclusion criteria of this study. Pooled estimates of sensitivity, specificity, and AUC of SROC with respective 95% CIs of CT on patient level were 0.83 (0.73, 0.90), 0.69 (0.54, 0.81), and 0.84 (0.80, 0.87). The overall sensitivity, specificity, SROC value with respective 95% CIs of MRI were 0.95 (0.91, 0.97),0.81 (0.76, 0.85), and 0.90 (0.87, 0.92) on patient level. Pooled estimates of sensitivity, specificity, SROC value of PET/CT on patient level were 0.92 (0.88, 0.94), 0.88 (0.83, 0.92), and 0.96 (0.94, 0.97).

CONCLUSION

Noninvasive imaging modalities including CT, MRI, PET (PET/CT, PET/MRI) yielded favorable diagnostic performance in the detection of OC. Hybrid implement of different tools (PET/MRI) is more accurate for identifying metastatic OC.

International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology

PREAMBLE

The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The merged International Society for Magnetic Resonance in Medicine (ISMRM) is an international, nonprofit, scientific association whose purpose is to promote communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics and to develop and provide channels and facilities for continuing education in the field.The ISMRM was founded in 1994 through the merger of the Society of Magnetic Resonance in Medicine and the Society of Magnetic Resonance Imaging. SNMMI, ISMRM, and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine and/or magnetic resonance imaging. The SNMMI, ISMRM, and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and/or magnetic resonance imaging and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each practice guideline, representing a policy statement by the SNMMI/EANM/ISMRM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI, ISMRM, and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging and magnetic resonance imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized. These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, the SNMMI, the ISMRM, and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines. The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment. Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.

Low-grade serous ovarian cancer: expert consensus report on the state of the science

Compared with high-grade serous carcinoma, low-grade serous carcinoma of the ovary or peritoneum is a less frequent epithelial ovarian cancer type that is poorly sensitive to chemotherapy and affects younger women, many of whom endure years of ineffective treatments and poor quality of life. The pathogenesis of this disease and its management remain incompletely understood. However, recent advances in the molecular characterization of the disease and identification of novel targeted therapies with activity in low-grade serous carcinoma offer the promise of improved outcomes. To update clinicians regarding recent scientific and clinical trial advancements and discuss unanswered questions related to low-grade serous carcinoma diagnosis and treatment, a panel of experts convened for a workshop in October 2022 to develop a consensus document addressing pathology, translational research, epidemiology and risk, clinical management, and ongoing research. In addition, the patient perspective was discussed. The recommendations developed by this expert panel-presented in this consensus document-will guide practitioners in all settings regarding the clinical management of women with low-grade serous carcinoma and discuss future opportunities to improve research and patient care.

Added Value of FDG PET/MRI in Gynecologic Oncology: A Pictorial Review

Fluorine 18-fluorodeoxyglucose (FDG) PET and MRI independently play a valuable role in the management of patients with gynecologic malignancies, particularly endometrial and cervical cancer. The PET/MRI hybrid imaging technique combines the metabolic information obtained from PET with the excellent soft-tissue resolution and anatomic details provided by MRI in a single examination. MRI is the modality of choice for assessment of local tumor extent in the pelvis, whereas PET is used to assess for local-regional spread and distant metastases. The authors discuss the added value of FDG PET/MRI in imaging gynecologic malignancies of the pelvis, with a focus on the role of FDG PET/MRI in diagnosis, staging, assessing treatment response, and characterizing complications. PET/MRI allows better localization and demarcation of the extent of disease, characterization of lesions and involvement of adjacent organs and lymph nodes, and improved differentiation of benign from malignant tissues, as well as detection of the presence of distant metastasis. It also has the advantages of decreased radiation dose and a higher signal-to-noise ratio of a prolonged PET examination of the pelvis contemporaneous with MRI. The authors provide a brief technical overview of PET/MRI, highlight how simultaneously performed PET/MRI can improve stand-alone MRI and PET/CT in gynecologic malignancies, provide an image-rich review to illustrate practical and clinically relevant applications of this imaging technique, and review common pitfalls encountered in clinical practice. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

A case of paraovarian tumor of borderline malignancy with decrease of apparent diffusion coefficient value and marked 18F-fluorodeoxyglucose accumulation

Para-ovarian cysts are occasionally encountered in clinical practice; however, malignant tumors derived from them are rare. Due to its rarity, the characteristic imaging findings of para-ovarian tumors with borderline malignancy (PTBM) are largely unknown. Herein, we report a case of PTBM, along with imaging findings. A 37-year-old woman came to our department with a suspected malignant adnexal tumor. Pelvic contrast-enhanced magnetic resonance imaging (MRI) revealed a solid part within the cystic tumor with a decrease in the apparent diffusion coefficient (ADC) value (1.16 × 10-3 mm2/s). We also performed Positron Emission Tomography-MRI and showed a strong accumulation of 18F-fluorodeoxyglucose (FDG) in the solid part (SUVmax = 14.8). In addition, the tumor appeared to develop independently of the ovary. Because tumor was derived from para-ovarian cyst, we suspected PTBM preoperatively and planned fertility sparing treatment. Pathological examination revealed a serous borderline tumor and PTBM was confirmed. PTBM can have unique imaging characteristics, including a low ADC value and high FDG accumulation. When a tumor appears to develop from para-ovarian cysts, borderline malignancy can be suspected, even if imaging findings suggest malignant potential.

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.

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis

BACKGROUND

Accurate identification of ovarian cancer (OC) is of paramount importance in clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the medical imaging recognition. We systematically review articles on the diagnostic performance of AI in OC from medical imaging for the first time.

METHODS

The Medline, Embase, IEEE, PubMed, Web of Science, and the Cochrane library databases were searched for related studies published until August 1, 2022. Inclusion criteria were studies that developed or used AI algorithms in the diagnosis of OC from medical images. The binary diagnostic accuracy data were extracted to derive the outcomes of interest: sensitivity (SE), specificity (SP), and Area Under the Curve (AUC). The study was registered with the PROSPERO, CRD42022324611.

FINDINGS

Thirty-four eligible studies were identified, of which twenty-eight studies were included in the meta-analysis with a pooled SE of 88% (95%CI: 85-90%), SP of 85% (82-88%), and AUC of 0.93 (0.91-0.95). Analysis for different algorithms revealed a pooled SE of 89% (85-92%) and SP of 88% (82-92%) for machine learning; and a pooled SE of 88% (84-91%) and SP of 84% (80-87%) for deep learning. Acceptable diagnostic performance was demonstrated in subgroup analyses stratified by imaging modalities (Ultrasound, Magnetic Resonance Imaging, or Computed Tomography), sample size (≤300 or >300), AI algorithms versus clinicians, year of publication (before or after 2020), geographical distribution (Asia or non Asia), and the different risk of bias levels (≥3 domain low risk or < 3 domain low risk).

INTERPRETATION

AI algorithms exhibited favorable performance for the diagnosis of OC through medical imaging. More rigorous reporting standards that address specific challenges of AI research could improve future studies.

FUNDING

This work was supported by the Natural Science Foundation of China (No. 82073647 to Q-JW and No. 82103914 to T-TG), LiaoNing Revitalization Talents Program (No. XLYC1907102 to Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (No. M0268 to Q-JW and No. M0952 to T-TG).

Neuroendocrine Neoplasms of the Gynecologic Tract

Simple Summary

Neuroendocrine refers to the cells that synthesize and secrete messenger chemicals such as neuropeptides and amines. Neuroendocrine neoplasms (NENs) are aggressive tumors arising from neuroendocrine cells, with an annual incidence of 6.98/100,000 and a prevalence of 170,000 in the United States. Primary gynecologic NENs constitute ≤2% of female reproductive tumors. NENs of the gynecologic tract are associated with high recurrence rates and dismal prognosis, making their treatment challenging. This article focuses on the updated staging classifications, clinicopathological characteristics, imaging, and management of NENs of the gynecological tract.

Abstract

Gynecological tract neuroendocrine neoplasms (NEN) are rare, aggressive tumors from endocrine cells derived from the neuroectoderm, neural crest, and endoderm. The primary gynecologic NENs constitute 2% of gynecologic malignancies, and the cervix is the most common site of NEN in the gynecologic tract. The updated WHO classification of gynecologic NEN is based on the Ki-67 index, mitotic index, and tumor characteristics such as necrosis, and brings more uniformity in the terminology of NENs like other disease sites. Imaging plays a crucial role in the staging, triaging, restaging, and surveillance of NENs. The expression of the somatostatin receptors on the surface of neuroendocrine cells forms the basis of increasing evaluation with functional imaging modalities using traditional and new tracers, including ⁶⁸Ga-DOTA-Somatostatin Analog-PET/CT. Management of NENs involves a multidisciplinary approach. New targeted therapies could improve the paradigm of care for these rare malignancies. This article focuses on the updated staging classifications, clinicopathological characteristics, imaging, and management of gynecologic NENs of the cervix, ovary, endometrium, vagina, and vulva, emphasizing the relatively common cervical neuroendocrine carcinomas among these entities.

Reproducibility of Standardized Uptake Values Including Volume Metrics Between TOF-PET-MR and TOF-PET-CT

Purpose

To investigate the reproducibility of tracer uptake measurements, including volume metrics, such as metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) obtained by TOF-PET-CT and TOF-PET-MR.

Materials and Methods

Eighty consecutive patients with different oncologic diagnoses underwent TOF-PET-CT (Discovery 690; GE Healthcare) and TOF-PET-MR (SIGNA PET-MR; GE Healthcare) on the same day with single dose−18F-FDG injection. The scan order, PET-CT following or followed by PET-MR, was randomly assigned. A spherical volume of interest (VOI) of 30 mm was placed on the liver in accordance with the PERCIST criteria. For liver, the maximum and mean standard uptake value for body weight (SUV) and lean body mass (SUL) were obtained. For tumor delineation, VOI with a threshold of 40 and 50% of SUVmax was used (VOI40 and VOI50). The SUVmax, SUVmean, SUVpeak, MTV and TLG were calculated. The measurements were compared between the two scanners.

Results

In total, 80 tumor lesions from 35 patients were evaluated. There was no statistical difference observed in liver regions, whereas in tumor lesions, SUVmax, SUV mean, and SUVpeak of PET-MR were significantly underestimated (p < 0.001) in both VOI40 and VOI50. Among volume metrics, there was no statistical difference observed except TLG on VOI50 (p = 0.03). Correlation between PET-CT and PET-MR of each metrics were calculated. There was a moderate correlation of the liver SUV and SUL metrics (r = 0.63–0.78). In tumor lesions, SUVmax and SUVmean had a stronger correlation with underestimation in PET-MR on VOI 40 (SUVmax and SUVmean; r = 0.92 and 0.91 with slope = 0.71 and 0.72, respectively). In the evaluation of MTV and TLG, the stronger correlations were observed both on VOI40 (MTV and TLG; r = 0.75 and 0.92) and VOI50 (MTV and TLG; r = 0.88 and 0.95) between PET-CT and PET-MR.

Conclusion

PET metrics on TOF-PET-MR showed a good correlation with that of TOF-PET-CT. SUVmax and SUVpeak of tumor lesions were underestimated by 16% on PET-MRI. MTV with % threshold can be regarded as identical volumetric markers for both TOF-PET-CT and TOF-PET-MR.

The Development of Nanoparticles for the Detection and Imaging of Ovarian Cancers

Ovarian cancer remains as one of the most lethal gynecological cancers to date, with major challenges associated with screening, diagnosis and treatment of the disease and an urgent need for new technologies that can meet these challenges. Nanomaterials provide new opportunities in diagnosis and therapeutic management of many different types of cancers. In this review, we highlight recent promising developments of nanoparticles designed specifically for the detection or imaging of ovarian cancer that have reached the preclinical stage of development. This includes contrast agents, molecular imaging agents and intraoperative aids that have been designed for integration into standard imaging procedures. While numerous nanoparticle systems have been developed for ovarian cancer detection and imaging, specific design criteria governing nanomaterial targeting, biodistribution and clearance from the peritoneal cavity remain key challenges that need to be overcome before these promising tools can accomplish significant breakthroughs into the clinical setting.