Keywords
Pelvic Masses, Magnetic Resonance Imaging (MRI), Diagnostic Accuracy, Anatomic Localization, Gadolinium Contrast, Clinical Decision-Making
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Shelar S, Dhande R, Parihar PS et al. A prospective observational study on magnetic resonance imaging (MRI) based evaluation of pelvic masses in females in tertiary care hospital in central India [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:582 (https://doi.org/10.12688/f1000research.148091.1)
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Study Protocol
A prospective observational study on magnetic resonance imaging (MRI) based evaluation of pelvic masses in females in tertiary care hospital in central India
[version 1; peer review: awaiting peer review]
PUBLISHED 05 Jun 2024
OPEN PEER REVIEW
REVIEWER STATUS
This article is included in the Datta Meghe Institute of Higher Education and Research collection.
Abstract
Corresponding author:
Sheetal Shelar
Competing interests:
No competing interests were disclosed.
Grant information:
The author(s) declared that no grants were involved in supporting this work.
Copyright:
© 2024 Shelar S et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Shelar S, Dhande R, Parihar PS et al. A prospective observational study on magnetic resonance imaging (MRI) based evaluation of pelvic masses in females in tertiary care hospital in central India [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:582 (https://doi.org/10.12688/f1000research.148091.1)
First published: 05 Jun 2024, 13:582 (https://doi.org/10.12688/f1000research.148091.1)
Latest published: 05 Jun 2024, 13:582 (https://doi.org/10.12688/f1000research.148091.1)
Introduction
Pelvic masses in females pose a diagnostic challenge due to their diverse etiologies, ranging from benign cysts to malignant tumors. The accurate characterization of pelvic masses is essential for guiding appropriate clinical management and optimizing patient outcomes. Magnetic Resonance Imaging (MRI) has emerged as a valuable diagnostic tool in this context, offering superior soft tissue contrast and detailed anatomical visualization. The prevalence of pelvic masses in females is a significant health concern globally. In India, where pelvic masses are a common gynecological issue, studies estimate a prevalence of approximately 12% among females.1 These masses often present with non-specific symptoms, including lower back pain, making it crucial to employ advanced imaging modalities for accurate detection and characterization.
Pelvic masses can arise from various structures, including the ovaries, uterus, fallopian tubes, and surrounding tissues. Distinguishing between benign and malignant masses is imperative for appropriate treatment planning. Traditional diagnostic methods, such as ultrasonography, may have limitations in providing a detailed characterization, necessitating the need for advanced imaging techniques like MRI.2 MRI offers several advantages in the evaluation of pelvic masses. It provides multi-planar imaging capabilities, enabling detailed assessments of the size, shape, and location of pelvic lesions. T1 and T2 weighted sequences, along with contrast-enhanced imaging, allow for the differentiation of tissue types and the characterization of lesions based on their enhancement patterns.3
Aim
The primary aim of this study is to utilize pelvic MRI for the detection, characterization, and differentiation of pelvic masses in females, with a focus on accurately diagnosing whether the masses are benign or malignant and estimating local spread in cases of malignancy.
Objectives
1. To assess diagnostic accuracy: Evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy of pelvic MRI in detecting pelvic masses in females with clinical suspicion.
2. To determine anatomic origin and pelvic compartment: Identify the anatomic origin of pelvic masses and determine the pelvic compartment in which they are located.
3. To classify masses as benign or malignant: Analyze the shape, size, and composition of pelvic masses using MRI to classify them as benign or malignant.
4. To estimate local spread in malignant masses: In cases where pelvic masses are diagnosed as malignant, estimate the extent of local spread within the adjacent pelvic cavity.
5. To evaluate the impact of gadolinium contrast: Assess the added value of gadolinium contrast administration in enhancing the diagnostic capability of pelvic MRI for characterizing pelvic masses.
6. To determine the prevalence of pelvic masses: Calculate the prevalence of pelvic masses in females undergoing MRI for clinical suspicion, providing insights into the frequency of these conditions in the study population.
7. To ensure ethical considerations and informed consent: Confirm adherence to ethical guidelines by obtaining both verbal and written informed consent from patients before MRI procedures.
8. To optimize imaging protocols: Refine the imaging protocols for pelvic MRI, considering the optimal combination of T1 and T2 weighted sequences, as well as the selective use of fat saturation imaging.
9. To provide comprehensive lesion characterization: Evaluate the shape, size, number, and origin of pelvic masses, including gynecological and extra-gynecological origins, and assess the presence of internal septations, vegetations, and fibrous tissue.
10. To contribute to clinical decision-making: Provide valuable information that can contribute to improved clinical decision-making for the management of patients with pelvic masses, leading to more effective and timely interventions.
Methods
Study design
This study will employ a prospective observational design to evaluate the diagnostic accuracy of pelvic MRI in detecting and characterizing pelvic masses in females. The design will allow for the systematic collection of data and analysis of the imaging findings in correlation with clinical, pathological, and surgical outcomes.
Study population
The study population will include female patients who are referred to the Department of Radiodiagnosis at AVBRH, Sawangi, complaining of lower back pain and have clinical suspicion or inconclusive ultrasonographic findings of pelvic masses. All eligible participants meeting the inclusion criteria will be considered for enrollment.
Place of study
The study will be conducted at the Department of Radiodiagnosis, AVBRH (Acharya Vinoba Bhave Rural Hospital), Sawangi. This facility is equipped with state-of-the-art MRI technology, ensuring standardized imaging protocols and data acquisition. AVBRH serves as a tertiary care center, providing a diverse patient population for the study.
Duration of study
The study will be conducted over a two-year period, from 2022 to 2024, allowing for a comprehensive assessment of the selected population and providing a representative sample for analysis.
Bias
1. Selection bias:
• Potential bias: Patients referred with lower back pain may not represent the entire population of females with pelvic masses, leading to an underrepresentation of individuals without lower back pain or those managed in other clinical settings.
• Mitigation strategy: Ensure collaboration with various clinical departments and healthcare settings to capture a diverse patient population. Randomized patient selection and inclusive referral criteria can reduce the impact of selection bias.
2. Referral bias:
• Potential bias: Patients referred for MRI may have a higher likelihood of having more complex or clinically suspicious cases, potentially skewing the study population towards a higher prevalence of pelvic masses.
• Mitigation strategy: Clearly define referral criteria and actively seek referrals from multiple clinical sources to ensure a representative sample. Conduct sensitivity analyses to assess the impact of referral patterns on study outcomes.
3. Volunteer bias:
• Potential bias: Patients who agree to participate may differ from those who decline, introducing bias based on individual motivations, socio-economic status, or health awareness.
• Mitigation strategy: Emphasize the voluntary nature of participation, ensuring that patients understand that their decision will not affect their medical care. Collect demographic data to identify and control for potential differences between participants and non-participants.
4. Information bias:
• Potential bias: Variability in the accuracy and completeness of clinical, imaging, or outcome data could lead to bias in the interpretation of study results.
• Mitigation strategy: Standardize data collection procedures, provide training to data collectors, and conduct regular quality checks. Employ blinded assessments whenever possible to reduce bias in outcome interpretation.
Enrollment
The enrollment process for the study on MRI-Based Evaluation of Pelvic Masses in Females involves a systematic approach to identify, recruit, and engage eligible participants. Patients presenting with lower back pain and clinical suspicion or inconclusive ultrasonographic findings of pelvic masses are identified during routine clinical assessments by healthcare providers from various departments, including gynecologists, general practitioners, and relevant specialists. Upon identification, a dedicated study coordinator conducts eligibility screening to ensure potential participants meet the inclusion and exclusion criteria. Inclusion criteria encompass female patients with lower back pain and clinical suspicion or inconclusive ultrasonographic findings of pelvic masses. Exclusion criteria include a history of abdominal trauma, operative history of malignant pelvic mass, pregnancy, metallic implants, pacemaker/cochlear implant, claustrophobia/psychiatric abnormalities, and uncooperative patients.
The informed consent process is a crucial step in the enrollment process, conducted by the study coordinator. Potential participants are provided with both verbal and written information about the study in English and Marathi. A detailed consent proforma is filled out after obtaining informed consent, emphasizing the voluntary nature of participation and the right to withdraw without impacting medical care. Patient education is an integral part of the enrollment process, where participants are informed about the importance of their role in contributing accurate and complete information for research purposes. The study coordinator or a qualified healthcare professional address any questions or concerns raised by potential participants, ensuring clarity and understanding.
After obtaining consent, baseline data is collected, including demographic information, medical history, and relevant clinical details. This information contributes to characterizing the study population and aids in the analysis of potential confounding factors. Following successful enrollment, patients are scheduled for pelvic MRI appointments. Prior to the MRI, patients are instructed to fast for at least 6 hours to optimize imaging quality. The imaging procedure involves obtaining T1 and T2 weighted images in axial, sagittal, and coronal planes, and gadolinium contrast is administered as per requirement. Post-MRI, participants are followed up to collect information on clinical outcomes, surgical interventions, or pathological findings related to detected pelvic masses. This follow-up ensures a comprehensive understanding of the patient journey and contributes to correlating imaging findings with clinical outcomes. Collected data is securely stored and analyzed according to the study objectives. Statistical methods are applied to assess the diagnostic accuracy of pelvic MRI and the impact of potential confounding factors. The entire enrollment process adheres to ethical guidelines, with regular oversight by the Institutional Ethics Committee to ensure participant safety and study integrity.
Data collections
The data collection process for the MRI-Based Evaluation of Pelvic Masses in Females is structured to gather comprehensive information encompassing clinical, imaging, and outcome data. This systematic approach ensures a robust analysis of the diagnostic accuracy of pelvic MRI in detecting and characterizing pelvic masses in females. At the outset, baseline information is collected, including demographic data such as age, ethnicity, and socioeconomic status. Additionally, participants' medical history, including relevant pre-existing conditions, medication history, and reproductive history, is documented. Clinical presentation details, such as the nature of lower back pain, its duration, and any associated symptoms, are also recorded.
Ensuring ethical compliance, the informed consent process is meticulously documented, with participants providing written consent and a verification of their understanding regarding voluntary participation and the right to withdraw from the study. Clinical assessment information encompasses referral details, the source of referral, initial clinical suspicions, and findings from inconclusive ultrasonographic examinations. Additionally, observations from physical examinations related to pelvic masses are documented. MRI imaging data collection is detailed, incorporating information on imaging protocols, contrast administration, and characteristics of pelvic masses. This includes the shape, size, and composition of the masses, enhancement patterns, and precise anatomical localization.
Follow-up data collection focuses on tracking clinical outcomes, including details of surgical interventions, pathological findings, and subsequent management decisions. Patient-reported outcomes, such as changes in symptoms, quality of life, or overall well-being, are also documented. To ensure robust data management, collected data is securely stored, coded, and anonymized to maintain participant confidentiality. Regular data backup procedures are implemented to prevent loss and ensure the integrity of the dataset. Quality control measures include ongoing training for data collectors to maintain consistency and accuracy. Blinded assessments, where data collectors are unaware of clinical outcomes, are conducted to minimize bias. Regular audits of data quality are performed to identify and rectify any discrepancies. Statistical analyses involve the calculation of prevalence estimates and diagnostic accuracy measures, including sensitivity, specificity, positive and negative predictive values, and overall accuracy of pelvic MRI. Ethical considerations remain paramount throughout the data collection process, with strict adherence to ethical guidelines and regular monitoring by the Institutional Ethics Committee to ensure participant welfare and uphold the integrity of the study. This comprehensive data collection process aims to provide a thorough foundation for the subsequent analysis of pelvic MRI efficacy in females with pelvic masses.
Sample size calculation top of form
The prevalence of pelvic masses in females in India is approximately 12%. To determine the appropriate sample size for the study, the formula N = ZαPQ/d2 is employed, where Zα represents the standard normal variate (1.96), P is the estimated proportion (0.06%), and d is the estimation of error (10%). Substituting these values, the calculated sample size (N) is (0.12) × (0.88) / (0.10)2, resulting in a sample size of 41 participants for the study. This calculation aims to ensure that the study is adequately powered to draw meaningful conclusions about the prevalence of pelvic masses in the target population.
Statistical method
In the statistical analysis for the MRI-Based Evaluation of Pelvic Masses in Females, a systematic approach is employed to elucidate the diagnostic accuracy and associated factors. Descriptive statistics, including measures like mean, median, standard deviation, and range, are utilized to succinctly summarize demographic characteristics, clinical variables, and imaging features within the study population. This provides a foundational understanding of the patient cohort undergoing pelvic MRI. Prevalence estimation is a critical aspect, where the occurrence of pelvic masses in females undergoing MRI is quantified, providing insights into the frequency of these conditions within the study population. Diagnostic accuracy measures, such as sensitivity, specificity, positive and negative predictive values, and overall accuracy, are calculated to evaluate the effectiveness of pelvic MRI in detecting and characterizing pelvic masses. The construction of 95% confidence intervals around these measures aids in assessing the precision of the findings.
To explore potential variations in diagnostic accuracy, subgroup analyses are conducted across different patient subpopulations, considering factors like age groups and clinical presentations. Statistical tests, such as chi-square or t-tests, are employed to identify significant differences in diagnostic accuracy between subgroups, providing valuable insights into the impact of various patient characteristics on the study outcomes. Correlation analysis is implemented to investigate the associations between imaging characteristics, such as size, shape, and enhancement patterns, and clinical outcomes, including surgical interventions and pathological findings. Correlation coefficients, such as Pearson or Spearman, quantify the strength and direction of these associations, contributing to a nuanced understanding of the relationships within the data.
Regression analysis, particularly logistic regression, is utilized to identify independent predictors of malignancy among pelvic masses. By controlling for potential confounding variables like age and clinical presentation, this analysis provides a more refined assessment of factors influencing diagnostic outcomes. For patients diagnosed with malignant pelvic masses, survival analysis techniques such as Kaplan-Meier curves are employed to estimate survival probabilities over time. Log-rank tests are used to compare survival curves between different subgroups, offering insights into potential prognostic factors. Receiver Operating Characteristic (ROC) curve analysis is instrumental in visualizing the trade-off between sensitivity and specificity at different diagnostic thresholds. The area under the ROC curve (AUC) serves as a summary measure of overall diagnostic performance, facilitating a comprehensive evaluation of the discriminatory ability of pelvic MRI. All statistical analyses are carried out using established statistical software packages such as R studio version 4.3.1 ensuring transparency, reproducibility, and appropriate visualization of results. Sensitivity analyses are conducted to assess the robustness of findings under different scenarios, and the results are reported in a clear and interpretable manner in adherence to reporting guidelines, such as the STARD statement for diagnostic studies. This meticulous statistical approach aims to derive meaningful insights from the collected data and contribute valuable information to the clinical understanding of pelvic masses in females.
Ethical and consent
The Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research (DU) has granted its approval to the study protocol (Reference number: DMIHER (DU)/IEC/2022/32. Date:15-07-2022). Prior to commencing the study, we will obtain written informed consent from all participants, providing them with a comprehensive explanation of the study’s objectives.
Limitations
The study on MRI-Based Evaluation of Pelvic Masses in Females is not without its limitations. One notable concern is the potential for selection bias, as the reliance on patients referred with lower back pain may introduce a skewed representation of individuals with specific characteristics, thereby limiting the generalizability of the findings. Additionally, the predominance of referral sources being gynecologists and general practitioners may lead to a higher prevalence of clinically suspicious cases, potentially impacting the external validity of the study. The voluntary nature of participation introduces the possibility of volunteer bias, with enrolled individuals differing from those who decline based on motivation, health awareness, or other unmeasured factors. The interpretation of MRI findings may be subject to variability between radiologists, introducing potential inter-observer bias. The study’s single-centre setting and limited ethnic and socioeconomic diversity may further constrain the generalizability of the results. Furthermore, the relatively small sample size and the cross-sectional nature of the study may limit statistical power and the ability to establish causal relationships. These limitations underscore the importance of cautious interpretation and acknowledgment of potential biases in understanding the implications of the study’s findings.
Discussion
The proposed study aims to contribute valuable insights into the diagnostic accuracy of pelvic magnetic resonance imaging (MRI) in the evaluation of pelvic masses in females. The primary objective of this study is to assess the diagnostic accuracy of pelvic MRI in detecting and characterizing pelvic masses in females. The utilization of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy will provide a comprehensive evaluation of the imaging modality's performance. Previous studies have highlighted the significance of MRI in the assessment of pelvic masses, demonstrating its superiority over other imaging modalities, especially in cases where ultrasound findings are inconclusive.4 The current proposal aligns with existing literature, aiming to further substantiate the diagnostic capabilities of pelvic MRI.
Determining the anatomic origin and pelvic compartment of pelvic masses is crucial for effective treatment planning. Accurate localization allows for precise surgical interventions and contributes to better patient outcomes.5 The proposed study's focus on identifying the anatomic origin and pelvic compartment aligns with the recommendations of the International Federation of Gynecology and Obstetrics (FIGO) for standardized reporting of pelvic masses.6 The evaluation of the impact of gadolinium contrast on the diagnostic capability of pelvic MRI is a notable aspect of this study. Contrast-enhanced MRI has demonstrated improved lesion conspicuity and characterization, especially in cases of malignancy.7 Investigating the added value of gadolinium contrast in the proposed study can provide evidence for its utility in enhancing the diagnostic accuracy of pelvic MRI
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how to cite this article
Shelar S, Dhande R, Parihar PS et al. A prospective observational study on magnetic resonance imaging (MRI) based evaluation of pelvic masses in females in tertiary care hospital in central India [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:582 (https://doi.org/10.12688/f1000research.148091.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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