ABSTRACT
A growing number of treatments for genitourinary diseases can result in various iatrogenic complications. Multimodality imaging in the post-procedural setting is essential for early and accurate diagnosis to limit morbidity and mortality. We review common and uncommon treatment-induced pathologies affecting the genitourinary system via a case-based approach. We illustrate notable complications affecting the kidneys, ureters, bladder, and urethra induced by percutaneous procedures, external beam radiation, immunotherapy, laparoscopic/robotic pelvic surgery, and intravesicular BCG. Finally, we provide guidance on optimal imaging techniques for diagnosis and highlight the role of image-guided interventions for mitigation of complications.
ABSTRACT
Cervical cancer is a common gynecological malignancy worldwide. Cervical cancer is staged based on the International Federation of Gynecology and Obstetrics (FIGO) classification system, which was revised in 2018 to incorporate radiologic and pathologic data. Imaging plays an important role in pretreatment assessment including initial staging and treatment response assessment of cervical cancer. Accurate determination of tumor size, local extension, and nodal and distant metastases is important for treatment selection and for prognostication. Although local recurrence can be diagnosed by physical examination, imaging plays a critical role in detection and follow-up of local and distant recurrence and subsequent treatment selection. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
Subject(s)
Societies, Medical , Uterine Cervical Neoplasms , Humans , Female , Uterine Cervical Neoplasms/diagnostic imaging , Uterine Cervical Neoplasms/pathology , United States , Neoplasm Invasiveness , Neoplasm Staging , Evidence-Based MedicineABSTRACT
Cervical cancer is a common gynecological malignancy worldwide. Cervical cancer is staged based on the International Federation of Gynecology and Obstetrics (FIGO) classification system, which was revised in 2018 to incorporate radiologic and pathologic data. Imaging plays an important role in pretreatment assessment including initial staging and treatment response assessment of cervical cancer. Accurate determination of tumor size, local extension, and nodal and distant metastases is important for treatment selection and for prognostication. Although local recurrence can be diagnosed by physical examination, imaging plays a critical role in detection and follow-up of local and distant recurrence and subsequent treatment selection. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
Subject(s)
Humans , Uterine Cervical Neoplasms/diagnostic imaging , Mammography , Neoplasm StagingABSTRACT
SUMMARY: Autologous reconstruction accounts for approximately 20% of all breast reconstruction. In cases of unilateral reconstruction, contralateral breast augmentation using autologous tissue can be performed to improve symmetry and is a viable option for patients interested in having more volume relative to their current size without the use of implants. CT scans have been used for preoperative planning for autologous reconstruction to evaluate available perforators. In this study, we report our experience using CT angiography for preoperative volumetric assessment for autologous contralateral breast augmentation in the setting of unilateral autologous breast reconstruction. Twelve patients underwent autologous augmentation during the study period. The average reconstruction flap weight was 561.2±253.6 grams, while the average augmentation flap weight was 218.0±133.7 grams. No patients experienced flap loss and we demonstrate that the predicted volumes for the augmented and reconstructed breasts were comparable to the actual respective flap volumes. Additionally, post-operative patient-reported outcome measures demonstrate high levels of satisfaction across multiple BREAST-Q subscales. This study demonstrates the utility of using CT angiography to estimate reconstructive volumes to help preoperative planning and achieve predictable postoperative breast volumes. It also supports that contralateral autologous augmentation is a good option for patients who would like to avoid implants and are interested in a small to moderate increase in size.
ABSTRACT
PURPOSE: Neoadjuvant chemotherapy is often administered for high-grade serous ovarian carcinoma (HGSC) prior to cytoreductive surgery. We evaluated treatment response by CT (simplified peritoneal carcinomatosis index [S-PCI]), pathology (chemotherapy response score [CRS]), laboratory markers (serum CA-125), and surgical outcomes, to identify predictors of disease-free survival. METHODS: For this retrospective, HIPAA-compliant, IRB-approved study, we identified 396 women with HGSC receiving neoadjuvant chemotherapy between 2010 and 2019. Two hundred and ninety-nine patients were excluded (surgery not performed; imaging/pathology unavailable). Pre- and post-treatment abdominopelvic CTs were assigned CT S-PCI scores 0-24 (higher score indicating more tumor). Specimens were assigned CRS of 1-3 (minimal to complete response). Clinical data were obtained via chart review. Univariate, multivariate, and survival analyses were performed. RESULTS: Ninety-seven women were studied, with mean age of 65 years ± 10. Interreader agreement was good to excellent for CT S-PCI scores (ICC 0.64-0.77). Despite a significant decrease in CT S-PCI scores after treatment (p < 0.001), mean decrease in CT S-PCI did not differ significantly among CRS categories (p = 0.20) or between patients who were optimally versus suboptimally debulked (p = 0.29). In a survival analysis, lower CRS (more viable tumor) was associated with shorter time to progression (p < 0.001). A joint Cox proportional-hazard models showed that only residual pathologic disease (CRS 1/2) (HR 4.19; p < 0.001) and change in CA-125 (HR 1.79; p = 0.01) predicted progression. CONCLUSION: HGSC response to neoadjuvant therapy by CT S-PCI did not predict pathologic CRS score, optimal debulking, or progression, revealing discordance between imaging, pathologic, biochemical, and surgical assessments of tumor response.
Subject(s)
Disease Progression , Neoadjuvant Therapy , Ovarian Neoplasms , Tomography, X-Ray Computed , Humans , Female , Ovarian Neoplasms/diagnostic imaging , Ovarian Neoplasms/pathology , Ovarian Neoplasms/therapy , Ovarian Neoplasms/drug therapy , Retrospective Studies , Aged , Tomography, X-Ray Computed/methods , Middle Aged , Cystadenocarcinoma, Serous/diagnostic imaging , Cystadenocarcinoma, Serous/pathology , Cystadenocarcinoma, Serous/drug therapy , Chemotherapy, Adjuvant , Neoplasm Grading , Cytoreduction Surgical Procedures , CA-125 Antigen/blood , Treatment OutcomeABSTRACT
PURPOSE: Gold-silica nanoshell therapy [AuroShells with subsequent focal laser therapy (AuroLase)] is an emerging targeted treatment modality for prostate cancer. We reviewed pre- and post-treatment unenhanced CT imaging to assess for retained gold-silica nanoshells in the abdomen and pelvis. METHODS: This single-institution retrospective study identified patients in the AuroLase pilot who underwent pre- and post-treatment unenhanced abdominopelvic CT. The attenuation, before and after gold-silica nanoshell administration, of the liver, spleen, pancreas, kidneys, prostate, blood pool, paraspinal musculature, and abnormal lymph nodes were manually measured by two readers. After inter-reader agreement was calculated using intraclass correlation (ICC), a permutation test was used to assess pre- and post-therapy attenuation differences. RESULTS: Four patients met the inclusion criteria. Mean age was 72.3 ± 5.9 years. Median time interval between pre-treatment CT and treatment, and between treatment and post-treatment CT, was 232 days and 236.5 days, respectively. The two readers' attenuation measurements had very high agreement (ICC = 0.99, p < 0.001). The highest differences in organ attenuation between pre- and post-therapy scans were seen in all four patients in the liver and spleen (liver increased by an average of 28.9 HU, p = 0.010; spleen increased by an average of 63.7 HU, p = 0.012). A single measured lymph node increased by an average of 58.9 HU. In the remainder of the measured sites, the change in attenuation from pre- to post-therapy scans ranged from -0.1 to 3.8 HU (p > 0.05). CONCLUSION: Increased attenuation of liver and spleen at CT can be an expected finding in patients who have received gold-silica nanoshell therapy.
Subject(s)
Gold , Nanoshells , Prostatic Neoplasms , Tomography, X-Ray Computed , Male , Humans , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/therapy , Aged , Tomography, X-Ray Computed/methods , Retrospective Studies , Silicon Dioxide , Pilot Projects , Abdomen/diagnostic imaging , Laser Therapy/methodsABSTRACT
In 2021, the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee developed a risk stratification system and lexicon for assessing adnexal lesions using MRI. Like the BI-RADS classification, O-RADS MRI provides a standardized language for communication between radiologists and clinicians. It is essential for radiologists to be familiar with the O-RADS algorithmic approach to avoid misclassifications. Training, like that offered by International Ovarian Tumor Analysis (IOTA), is essential to ensure accurate and consistent application of the O-RADS MRI system. Tools such as the O-RADS MRI calculator aim to ensure an algorithmic approach. This review highlights the key teaching points, pearls, and pitfalls when using the O-RADS MRI risk stratification system.Critical relevance statement This article highlights the pearls and pitfalls of using the O-RADS MRI scoring system in clinical practice.Key points⢠Solid tissue is described as displaying post- contrast enhancement.⢠Endosalpingeal folds, fimbriated end of the tube, smooth wall, or septa are not solid tissue.⢠Low-risk TIC has no shoulder or plateau. An intermediate-risk TIC has a shoulder and plateau, though the shoulder is less steep compared to outer myometrium.
ABSTRACT
Epithelial ovarian neoplasms (EON) constitute the majority of ovarian cancers. Among EON, high-grade serous carcinoma (HGSC) is the most common and most likely to present at an advanced stage. Radiologists should recognize the imaging features associated with HGSC, particularly at ultrasound and MR imaging. Computed tomography is used for staging and to direct care pathways. Peritoneal carcinomatosis is common and does not preclude surgical resection. Other less common malignant EON have varied appearances, but share a common correlation between the amount of vascularized solid tissue and the likelihood of malignancy.
Subject(s)
Carcinoma , Ovarian Neoplasms , Female , Humans , Ovarian Neoplasms/diagnostic imaging , Ovarian Neoplasms/metabolism , Ovarian Neoplasms/pathologyABSTRACT
Several recent guidelines have been published to improve accuracy and consistency of adnexal mass imaging interpretation and to guide management. Guidance from the American College of Radiology (ACR) Appropriateness Criteria establishes preferred adnexal imaging modalities and follow-up. Moreover, the ACR Ovarian-Adnexal Reporting Data System establishes a comprehensive, unified set of evidence-based guidelines for classification of adnexal masses by both ultrasound and MR imaging, communicating risk of malignancy to further guide management.
Subject(s)
Adnexal Diseases , Ovarian Neoplasms , Female , Humans , Adnexal Diseases/diagnostic imaging , Ultrasonography/methods , Adnexa Uteri/diagnostic imaging , Magnetic Resonance Imaging/methods , Ovary , Ovarian Neoplasms/diagnostic imagingABSTRACT
Transgender and gender diverse (TGD) people experience health disparities, and many avoid necessary medical care because of fears of discrimination or mistreatment. Disparate care is further compounded by limited understanding of gender-affirming hormone therapy (GAHT) and gender-affirming surgery among the medical community. Specific to radiology, TGD patients report more negative imaging experiences than negative general health encounters, highlighting the need for guidance and best practices for inclusive imaging care. A patient's imaging journey provides numerous opportunities for improvement. Inclusive practice in a radiology department starts with ordering and scheduling the examination, facilitated by staff education on appropriate use of a patient's chosen name, gender identity, and pronouns. Contemporary electronic health record systems have the capacity for recording detailed sexual orientation and gender identity data, but staff must be trained to solicit and use this information. A welcoming environment can help TGD patients to feel safe during the imaging experience and may include institutional nondiscrimination policies, gender-neutral signage, and all-gender single-user dressing rooms and bathrooms. Image acquisition should be performed using trauma-informed and patient-centered care. Finally, radiologists should be aware of reporting considerations for TGD patients, such as avoiding the use of gender in reports when it is not medically relevant and using precise, respectful language for findings related to GAHT and gender-affirming surgical procedures. As a field, radiology has a range of opportunities for improving care delivery for TGD patients, and the authors summarize recommended best practices. See the invited commentary by Stowell in this issue. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.
Subject(s)
Transgender Persons , Humans , Female , Male , Gender Identity , Diagnostic Imaging , Patient-Centered Care , Organizational PolicyABSTRACT
Acute pelvic pain is a common presenting symptom in women, but the etiology is often not readily apparent. The differential diagnosis varies greatly for pre versus postmenopausal and pregnant versus nonpregnant women. In addition to physical examination and laboratory evaluation, imaging plays an important role in narrowing the differential diagnosis. Pelvic ultrasound (US) is the first-line imaging modality, but occasionally pelvic magnetic resonance imaging (MRI) is used for problem-solving in the acute setting. The aim of this article is to educate radiologists on the appearance of acute adnexal pathologies that can be definitively diagnosed at MRI.
Subject(s)
Adnexa Uteri , Magnetic Resonance Imaging , Pregnancy , Humans , Female , Magnetic Resonance Imaging/methods , Ultrasonography , Pelvic Pain , Diagnosis, DifferentialSubject(s)
Adnexal Diseases , Magnetic Resonance Imaging , Female , Humans , Magnetic Resonance Imaging/methods , Adnexa UteriABSTRACT
The Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) and MRI risk stratification systems were developed by an international group of experts in adnexal imaging to aid radiologists in assessing adnexal lesions. The goal of imaging is to appropriately triage patients with adnexal lesions. US is the first-line imaging modality for assessment, whereas MRI can be used as a problem-solving tool. Both US and MRI can accurately characterize benign lesions such as simple cysts, endometriomas, hemorrhagic cysts, and dermoid cysts, avoiding unnecessary or inappropriate surgery. In patients with a lesion that does not meet criteria for one of these benign diagnoses, MRI can further characterize the lesion with an improved specificity for cancer and the ability to provide a probable histologic subtype in the presence of certain MRI features. This allows personalized treatment, including avoiding overly extensive surgery or allowing fertility-sparing procedures for suspected benign, borderline, or low-grade tumors. When MRI findings indicate a risk of an invasive cancer, patients can be expeditiously referred to a gynecologic oncologic surgeon. This narrative review provides expert opinion on the utility of multiparametric MRI when using the O-RADS US and MRI management systems.
Subject(s)
Adnexal Diseases , Cysts , Ovarian Neoplasms , Humans , Female , Adnexal Diseases/diagnostic imaging , Data Systems , Ultrasonography/methods , Magnetic Resonance Imaging/methods , Ovarian Neoplasms/diagnostic imagingABSTRACT
Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, diffusion-weighted imaging, and multiphase contrast-enhanced imaging is the mainstay for imaging assessment of endometrial cancer. Identification of important prognostic factors at MRI improves both treatment selection and posttreatment follow-up. MRI also plays a crucial role for fertility-preserving strategies and in patients who are not surgical candidates by helping guide therapy and identify procedural complications. This review is a product of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease-Focused Panel and reflects a multidisciplinary international collaborative effort to summarize updated information highlighting the role of MRI for endometrial cancer depiction and delineation, treatment planning, and follow-up. The article includes information regarding dedicated MRI protocols, tips for MRI reporting, imaging pitfalls, and strategies for image quality optimization. The roles of MRI-guided radiation therapy, hybrid PET/MRI, and advanced MRI techniques that are applicable to endometrial cancer imaging are also discussed. Online supplemental material is available for this article. ©RSNA, 2022.
Subject(s)
Endometrial Neoplasms , Genital Neoplasms, Female , Humans , Female , Neoplasm Staging , Endometrial Neoplasms/diagnosis , Endometrial Neoplasms/pathology , Endometrial Neoplasms/surgery , Magnetic Resonance Imaging/methods , Diffusion Magnetic Resonance Imaging/methods , Genital Neoplasms, Female/pathologyABSTRACT
BACKGROUND: Traumatic Brain Injury (TBI) is a common condition with potentially severe long-term complications, the prediction of which remains challenging. Machine learning (ML) methods have been used previously to help physicians predict long-term outcomes of TBI so that appropriate treatment plans can be adopted. However, many ML techniques are "black box": it is difficult for humans to understand the decisions made by the model, with post-hoc explanations only identifying isolated relevant factors rather than combinations of factors. Moreover, such models often rely on many variables, some of which might not be available at the time of hospitalization. METHODS: In this study, we apply an interpretable neural network model based on tropical geometry to predict unfavorable outcomes at six months from hospitalization in TBI patients, based on information available at the time of admission. RESULTS: The proposed method is compared to established machine learning methods-XGBoost, Random Forest, and SVM-achieving comparable performance in terms of area under the receiver operating characteristic curve (AUC)-0.799 for the proposed method vs. 0.810 for the best black box model. Moreover, the proposed method allows for the extraction of simple, human-understandable rules that explain the model's predictions and can be used as general guidelines by clinicians to inform treatment decisions. CONCLUSIONS: The classification results for the proposed model are comparable with those of traditional ML methods. However, our model is interpretable, and it allows the extraction of intelligible rules. These rules can be used to determine relevant factors in assessing TBI outcomes and can be used in situations when not all necessary factors are known to inform the full model's decision.
Subject(s)
Brain Injuries, Traumatic , Neural Networks, Computer , Brain Injuries, Traumatic/diagnosis , Brain Injuries, Traumatic/therapy , Humans , Machine Learning , Prognosis , ROC CurveABSTRACT
Gastric neuroendocrine neoplasms are uncommon tumors with variable differentiation and malignant potential. Three main subtypes are recognized: type 1, related to autoimmune atrophic gastritis; type 2, associated with Zollinger-Ellison and MEN1 syndrome; and type 3, sporadic. Although endoscopy alone is often sufficient for diagnosis and management of small, indolent, multifocal type 1 tumors, imaging is essential for evaluation of larger, high-grade, and type 2 and 3 neoplasms. Hypervascular intraluminal gastric masses are typically seen on CT/MRI, with associated perigastric lymphadenopathy and liver metastases in advanced cases. Somatostatin receptor nuclear imaging (such as Ga-68-DOTATATE PET/CT) may also be used for staging and assessing candidacy for peptide receptor radionuclide therapy. Radiotracer uptake is more likely in well-differentiated, lower-grade tumors, and less likely in poorly differentiated tumors, for which F-18-FDG-PET/CT may have additional value. Understanding disease pathophysiology and evolving histologic classifications is particularly useful for radiologists, as these influence tumor behavior, preferred imaging, therapy options, and patient prognosis.
Subject(s)
Neuroendocrine Tumors , Organometallic Compounds , Stomach Neoplasms , Humans , Positron Emission Tomography Computed Tomography/methods , Gallium Radioisotopes , Neuroendocrine Tumors/pathology , RadiologistsABSTRACT
BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitative (v.s. quantitative) fashion, shortcomings which could both be addressed by automated computer-aided systems that are capable of generating real-time reproducible and quantitative information. This study outlines an end-to-end pipeline to calculate the percentage of the liver parenchyma disrupted by trauma, an important component of the American Association for the Surgery of Trauma (AAST) liver injury scale, the primary tool to assess liver trauma severity at CT. METHODS: This framework comprises deep convolutional neural networks that first generate initial masks of both liver parenchyma (including normal and affected liver) and regions affected by trauma using three dimensional contrast-enhanced CT scans. Next, during the post-processing step, human domain knowledge about the location and intensity distribution of liver trauma is integrated into the model to avoid false positive regions. After generating the liver parenchyma and trauma masks, the corresponding volumes are calculated. Liver parenchymal disruption is then computed as the volume of the liver parenchyma that is disrupted by trauma. RESULTS: The proposed model was trained and validated on an internal dataset from the University of Michigan Health System (UMHS) including 77 CT scans (34 with and 43 without liver parenchymal trauma). The Dice/recall/precision coefficients of the proposed segmentation models are 96.13/96.00/96.35% and 51.21/53.20/56.76%, respectively, in segmenting liver parenchyma and liver trauma regions. In volume-based severity analysis, the proposed model yields a linear regression relation of 0.95 in estimating the percentage of liver parenchyma disrupted by trauma. The model shows an accurate performance in avoiding false positives for patients without any liver parenchymal trauma. These results indicate that the model is generalizable on patients with pre-existing liver conditions, including fatty livers and congestive hepatopathy. CONCLUSION: The proposed algorithms are able to accurately segment the liver and the regions affected by trauma. This pipeline demonstrates an accurate performance in estimating the percentage of liver parenchyma that is affected by trauma. Such a system can aid critical care medical personnel by providing a reproducible quantitative assessment of liver trauma as an alternative to the sometimes subjective AAST grading system that is used currently.
Subject(s)
Deep Learning , Humans , Image Processing, Computer-Assisted/methods , Liver/diagnostic imaging , Neural Networks, Computer , Tomography, X-Ray ComputedABSTRACT
PURPOSE: Our purpose was to evaluate the accuracy of LI-RADS Treatment Response Algorithm (LR-TRA) for assessing the viability of hepatocellular carcinoma (HCC) treated with stereotactic body radiation therapy (SBRT), using explant pathology as the gold standard. METHODS AND MATERIALS: This retrospective study included patients who underwent SBRT for locoregional treatment of HCC between 2008 and 2019 with subsequent liver transplantation. Five radiologists independently assessed all treated lesions by using the LR-TRA. Imaging and posttransplant histopathology were compared. Lesions were categorized as either completely (100%) or incompletely (<100%) necrotic, and performance characteristics and predictive values for the LR-TR viable and nonviable categories were calculated for each reader. Interreader reliability was calculated using the Fleiss kappa test. RESULTS: A total of 40 treated lesions in 26 patients (median age, 63 years [interquartile range, 59.4-65.5]; 23 men) were included. For lesions treated with SBRT, sensitivity for incomplete tumor necrosis across readers ranged between 71% and 86%, specificity between 85% and 96%, and positive predictive value between 86% and 92%, when the LR-TR equivocal category was treated as nonviable, accounting for subject clustering. When the LR-TR equivocal category was treated as viable, sensitivity of complete tumor necrosis for lesions treated with SBRT ranged from 88% to 96%, specificity from 71% to 93%, and negative predictive value from 85% to 96%. Interreader reliability was fair (k = 0.22; 95% confidence interval, 0.13-0.33). Although a loss of arterial phase hyperenhancement (APHE) was highly correlated with pathologically nonviable tumor on explant, almost half of the patients with APHE had pathologically nonviable tumor on explant. CONCLUSIONS: LR-TRA v2018 performs well for predicting complete and incomplete necrosis in HCC treated with SBRT. In contrast to other locoregional therapies, the presence of APHE after SBRT does not always indicate viable tumor and suggests that observation may be an appropriate strategy for these patients.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Radiosurgery , Algorithms , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/pathology , Carcinoma, Hepatocellular/radiotherapy , Contrast Media , Humans , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/pathology , Liver Neoplasms/radiotherapy , Magnetic Resonance Imaging/methods , Male , Middle Aged , Reproducibility of Results , Retrospective Studies , Sensitivity and SpecificityABSTRACT
Primary vaginal cancer is rare, comprising 1% to 2% of gynecologic malignancies and 20% of all malignancies involving the vagina. More frequently, the vagina is involved secondarily by direct invasion from malignancies originating in adjacent organs or by metastases from other pelvic or extrapelvic primary malignancies. Data on the use of imaging in vaginal cancer are sparse. Insights are derived from the study of imaging in cervical cancer and have reasonable generalizability to vaginal cancer due to similar tumor biology. Given the trend toward definitive chemoradiation for both cancers in all but early stage lesions, principles of postchemoradiation tumor response evaluation are largely analogous. Accordingly, many of the recommendations outlined here are informed by principles translated from the literature on cervical cancer. For pretreatment assessment of local tumor burden and in the case of recurrent vaginal cancer, MRI is the preferred imaging modality. PET/CT has demonstrated utility for the detection of nodal metastatic and unexpected distant metastatic disease. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
Subject(s)
Positron Emission Tomography Computed Tomography , Vaginal Neoplasms , Female , Follow-Up Studies , Humans , Magnetic Resonance Imaging , Neoplasm Recurrence, Local , Societies, Medical , United States , Vaginal Neoplasms/diagnostic imagingABSTRACT
BACKGROUND: The 125I-iothalamate clearance and 99mTc diethylenetriamine-pentaacetic acid (99mTc-DTPA) split scan nuclear medicine studies are used among living kidney donor candidates to determine measured glomerular filtration rate (mGFR) and split scan ratio (SSR). The computerized tomography-derived cortical volume ratio (CVR) is a novel measurement of split kidney function and can be combined with predonation estimated GFR (eGFR) or mGFR to predict postdonation kidney function. Whether predonation SSR predicts postdonation kidney function better than predonation CVR and whether predonation mGFR provides additional information beyond predonation eGFR are unknown. METHODS: We performed a single-center retrospective analysis of 204 patients who underwent kidney donation between June 2015 and March 2019. The primary outcome was 1-y postdonation eGFR. Model bases were created from a measure of predonation kidney function (mGFR or eGFR) multiplied by the proportion that each nondonated kidney contributed to predonation kidney function (SSR or CVR). Multivariable elastic net regression with 1000 repetitions was used to determine the mean and 95% confidence interval of R2, root mean square error (RMSE), and proportion overprediction ≥15 mL/min/1.73 m2 between models. RESULTS: In validation cohorts, eGFR-CVR models performed best (R2, 0.547; RMSE, 9.2 mL/min/1.73 m2, proportion overprediction 3.1%), whereas mGFR-SSR models performed worst (R2, 0.360; RMSE, 10.9 mL/min/1.73 m2, proportion overprediction 7.2%) (P < 0.001 for all comparisons). CONCLUSIONS: These findings suggest that predonation CVR may serve as an acceptable alternative to SSR during donor evaluation and furthermore, that a model based on CVR and predonation eGFR may be superior to other methods.