Gynecologic tumor board: a radiologist’s guide to vulvar and vaginal malignancies

AbstractPrimary vulvar and vaginal cancers are rare female genital tract malignancies which are staged using the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging. These cancers account for approximately 2,700 deaths annually in the USA. The most common histologic subtype of both vulvar and vaginal cancers is squamous cell carcinoma, with an increasing role of the human papillomavirus (HPV) in a significant number of these tumors. Lymph node involvement is the hallmark of FIGO stage 3 vulvar cancer while pelvic sidewall involvement is the hallmark of FIGO stage 3 vaginal cancer. Imaging techniques include computed tomography (CT), positron emission tomography (PET)-CT, magnetic resonance imaging (MRI), and PET-MRI. MRI is the imaging modality of choice for preoperative clinical staging of nodal and metastatic involvement while PET-CT is helpful with assessing response to neoadjuvant treatment and for guiding patient management. Determining the pretreatment extent of disease has become more important due to modern tailored operative approaches and use of neoadjuvant chemoradiation therapy to reduce surgical morbidity. Moreover, imaging is used to determine the full extent of disease for radiation planning and for evaluating treatment response. Understanding the relevant anatomy of the vulva and vaginal regions and the associated lymphatic pathways is helpful to recognize the potential routes of spread and to correctly identify the appropriate FIGO stage. The purpose of this article is to review the clinical features, pathology, and current treatment strategies for vulvar and vaginal malignancies and to identify multimodality diagnostic imaging features of these gynecologic cancers, in conjunction with its respective 2009 FIGO staging system guidelines.

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Correlation of 18F-FDG PET/CT SUVmax with clinical features, D-dimer and LDH in patients with primary intestinal lymphoma

Journal of International Medical Research ◽

10.1177/03000605211029809 ◽

2021 ◽

Vol 49 (7) ◽

pp. 030006052110298

Author(s):

Shuo Zhou ◽

Wenxin Chen ◽

Meifu Lin ◽

Guobao Chen ◽

Cailong Chen ◽

...

Keyword(s):

Fdg Pet ◽

Clinical Staging ◽

Imaging Features ◽

Intestinal Lymphoma ◽

Ki 67 ◽

Positive Correlation ◽

Pet Ct ◽

18F Fdg ◽

Fdg Pet Ct ◽

D Dimer

Objective To investigate the characteristics of fluorine-18-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) maximum standardized uptake value (SUVmax) in primary intestinal lymphoma (PIL) and its correlation with D-dimer and lactate dehydrogenase (LDH). Methods Fifty-two patients diagnosed with PIL from June 2016 to December 2019 were analyzed. All patients underwent 18F-FDG PET/CT. The relationships between SUVmax and different pathological subtypes, clinical stages and risk grades were analyzed. The correlations between SUVmax and Ki-67, LDH and D-dimer were determined. Additionally, PET/CT imaging results were collected from 35 patients with primary intestinal cancer (PIC) and compared with the imaging features of PIL. Results SUVmax was significantly different between PIL and PIC groups and various PIL pathological subgroups. Patients in the high-risk PIL group had markedly higher SUVmax values than the intermediate-risk and low-risk groups. A significant positive correlation was observed between SUVmax and Ki-67 in patients with PIL. SUVmax was significantly different between the elevated and normal D-dimer groups. D-dimer showed a positive correlation with SUVmax. Conclusion 18F-FDG PET/CT SUVmax reflects the aggressiveness of lymphoma to a certain degree, is correlated with Ki-67 and determines the risk grades of PIL. Moreover, it facilitates differential diagnosis, clinical staging and treatment based on D-dimer levels.

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Staging in multidisciplinary (MDC) v serial care (SC) lung cancer (LCa) patients (Pts).

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.e20079 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. e20079-e20079

Author(s):

Matthew Smeltzer ◽

Nicholas Ryan Faris ◽

Fedoria Elaine Rugless Stewart ◽

Meredith Ray ◽

Nana Boateng ◽

...

Keyword(s):

Clinical Staging ◽

Tumor Board ◽

Insurance Status ◽

Newly Diagnosed ◽

Chi Square ◽

Pet Ct ◽

Node Positive Disease ◽

Chi Square Test ◽

N Stage ◽

Clinical Trial Information

e20079 Background: Multi-modal staging is associated with improved survival for pts with LCa. We evaluated the thoroughness of clinical staging within and outside a co-located MDC. Methods: Prospective cohort study comparing newly-diagnosed LCa patients in MDC to serially referred (SC) pts within the same healthcare system. Pts were enrolled before treatment began. Stage-confirmation was defined as invasive biopsy of a stage-defining lesion. Bimodal staging involved use of either PET scan or invasive biopsy with CT scan, trimodal staging involved all 3. We used the chi-square test and multivariable logistic regression. Results: From 2014-16, 162 pts were enrolled into MDC, 318 into SC. MDC pts were older (median age 69 v 66), more likely to be black (37% v 29%), and less likely to be commercially insured (36% v 43%) than SC pts. MDC pts had node positive disease identified by PET/CT in 70% of cases, but only 42% in SC (p=0.003). MDC pts were more likely to be clinical M0 (70% vs. 55%). M1b pts were biopsied in 45% of MDC v 36% of SC cases. MDC pts were more likely to have bimodal (90% v 73%) and trimodal staging (51% v 29%) (both p<0.0001, Table 1). The stage-confirmation rate (OR: 1.93 [CI 1.32,2.84]); p=0.0007) and mediastinal stage confirmation rate (OR: 2.16[1.46,3.18]; p=0.0001) were both significantly higher in MDC (Table 1). Adjusting for age, gender, clinical N stage, and histology, these results remained significant (aOR=2.13, p=0.0003); (aOR=2.35, p<0.0001). A subgroup of SC patients (N=64) was discussed at a tumor board. This group had a stage confirmation rate (48%) and mediastinal stage confirmation rate (44%) intermediate between MDC and pure SC (p=0.007, p<0.0001). Conclusions: MDC effectively reached a higher percentage of underserved persons based on age, race, and insurance status, while providing significantly more thorough clinical staging. A tumor board alleviated, but did not eliminate, the gap. Clinical trial information: NCT02123797. [Table: see text]

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A Novel Tool to Predict Early Death in Uterine Sarcoma Patients: A Surveillance, Epidemiology, and End Results-Based Study

Frontiers in Oncology ◽

10.3389/fonc.2020.608548 ◽

2020 ◽

Vol 10 ◽

Author(s):

Zixuan Song ◽

Yizi Wang ◽

Dandan Zhang ◽

Yangzi Zhou

Keyword(s):

Area Under The Curve ◽

Early Death ◽

Figo Stage ◽

Uterine Sarcoma ◽

Internal Validation ◽

Figo Staging ◽

Gynecology And Obstetrics ◽

Gynecologic Tumor ◽

Using Data ◽

End Results

BackgroundUterine sarcoma is a rare gynecologic tumor with a high degree of malignancy. There is a lack of effective prognostic tools to predict early death of uterine sarcoma.MethodsData on patients with uterine sarcoma registered between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) data. Important independent prognostic factors were identified by univariate and multivariate logistic regression analyses to construct a nomogram for total early deaths and cancer-specific early deaths.ResultsA total of 5,274 patients with uterine sarcoma were included in this study. Of which, 397 patients experienced early death (≤3 months), and 356 of whom died from cancer-specific causes. A nomogram for total early deaths and cancer-specific early deaths was created using data on age, race, tumor size, the International Federation of Gynecology and Obstetrics (FIGO) staging, histological classification, histological staging, treatment (surgery, radiotherapy, chemotherapy), and brain metastases. On comparing the C-index, area under the curve, and decision curve analysis, the created nomogram showed better predictive power and clinical practicality than one made exclusively with FIGO staging. Calibration of the nomogram by internal validation showed good consistency between the predicted and actual early death.ConclusionsNomograms that include clinical characteristics can provide a better prediction of the risk of early death for uterine sarcoma patients than nomograms only comprising the FIGO stage system. In doing so, this tool can help in identifying patients at high risk for early death because of uterine sarcoma.

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Imaging analysis of 13 rare cases of renal collecting (Bellini) duct carcinoma in northern China: a case series and literature review

BMC Medical Imaging ◽

10.1186/s12880-021-00574-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Zhehao Lyu ◽

Lili Liu ◽

Huimin Li ◽

Haibo Wang ◽

Qi Liu ◽

...

Keyword(s):

Magnetic Resonance ◽

Ct Scan ◽

Clinical Manifestations ◽

Northern China ◽

Renal Tumors ◽

Imaging Features ◽

Duct Carcinoma ◽

Pet Ct ◽

Bellini Duct Carcinoma ◽

Mass Type

Abstract Background Collecting (Bellini) duct carcinoma (CDC) is a highly malignant and rare kidney tumor. We report our 12-year experience with CDC and the results of a retrospective analysis of patients and tumor characteristics, clinical manifestations, and imaging features by computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)/CT. Methods Retrospective examination of tumors between January 2007 and December 2019 identified 13 cases of CDC from three medical centers in northern China. All 13 patients underwent CT scan, among which eight underwent dynamic enhanced CT scan, two underwent PET/CT scan, and one underwent magnetic resonance cholangiopancreatography (MRCP) examination. The lesions were divided into nephritis type and mass type according to the morphology of the tumors. Results The study group included ten men and three women with an average age of 64.23 ± 10.74 years. The clinical manifestations were gross hematuria, flank pain, and waist discomfort. The mean tumor size was 8.48 ± 2.48 cm. Of the 13 cases, six (46.2%) were cortical-medullary involved type and seven (53.8%) were cortex–medullary–pelvis involved type. Eleven (84.6%) cases were nephritis type and two (15.4%) were mass type. The lesions appeared solid or complex solid and cystic on CT and MRI. The parenchymal area of the tumors showed isodensity or slightly higher density on unenhanced CT scan in the 13 cases. PET/CT in two cases showed increased radioactivity intake. Evidence of intra-abdominal metastatic disease was present on CT in nine (69.2%) cases. Conclusions The imaging characteristics of CDC differ from those of other renal cell carcinomas. In renal tumors located in the junction zone of the renal cortex and medulla that show unclear borders, slight enhancement, and metastases in the early stage, a diagnosis of CDC needs to be considered. PET/CT provides crucial information for the diagnosis of CDC, as well as for designing treatment strategies including surgery.

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Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics

Cancers ◽

10.3390/cancers13081929 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1929

Author(s):

Jan C. Peeken ◽

Jan Neumann ◽

Rebecca Asadpour ◽

Yannik Leonhardt ◽

Joao R. Moreira ◽

...

Keyword(s):

Soft Tissue ◽

Soft Tissue Sarcomas ◽

Treatment Decision ◽

Staging System ◽

Predictive Performance ◽

Machine Learning Techniques ◽

Clinical Staging ◽

Imaging Features ◽

Prognostic Assessment ◽

Selection Operator

Background: In patients with soft-tissue sarcomas of the extremities, the treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients’ risk. In this work, we compared the value of MRI-based radiomics with expert-derived semantic imaging features for the prediction of overall survival (OS). Methods: Fat-saturated T2-weighted sequences (T2FS) and contrast-enhanced T1-weighted fat-saturated (T1FSGd) sequences were collected from two independent retrospective cohorts (training: 108 patients; testing: 71 patients). After preprocessing, 105 radiomic features were extracted. Semantic imaging features were determined by three independent radiologists. Three machine learning techniques (elastic net regression (ENR), least absolute shrinkage and selection operator, and random survival forest) were compared to predict OS. Results: ENR models achieved the best predictive performance. Histologies and clinical staging differed significantly between both cohorts. The semantic prognostic model achieved a predictive performance with a C-index of 0.58 within the test set. This was worse compared to a clinical staging system (C-index: 0.61) and the radiomic models (C-indices: T1FSGd: 0.64, T2FS: 0.63). Both radiomic models achieved significant patient stratification. Conclusions: T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment.

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Automated quantification of baseline imaging PET metrics on FDG PET/CT images of pediatric Hodgkin lymphoma patients

EJNMMI Physics ◽

10.1186/s40658-020-00346-3 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Amy J. Weisman ◽

Jihyun Kim ◽

Inki Lee ◽

Kathleen M. McCarten ◽

Sandy Kessel ◽

...

Keyword(s):

Hodgkin Lymphoma ◽

Correlation Coefficient ◽

Pet Imaging ◽

Fdg Pet ◽

Relative Difference ◽

Ct Images ◽

Imaging Features ◽

Pediatric Hodgkin Lymphoma ◽

Pet Ct ◽

Fdg Pet Ct

Abstract Purpose For pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma. Methods 18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson’s correlation coefficient and relative percent differences were calculated between automated and physician-extracted features. Results Median Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78–0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson’s correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of − 4.3% (− 10.0–5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of − 0.4% (− 5.2–7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6–4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR − 7.5–40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically. Conclusions An automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

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Not all that glitters is COVID! Differential diagnosis of FDG-avid interstitial lung disease in low-prevalence regions

European Journal of Hybrid Imaging ◽

10.1186/s41824-020-00088-6 ◽

2020 ◽

Vol 4 (1) ◽

Author(s):

Annalisa Papa ◽

Chiara Pozzessere ◽

Francesco Cicone ◽

Fabiola Rizzuto ◽

Giuseppe Lucio Cascini

Keyword(s):

Differential Diagnosis ◽

Interstitial Lung Diseases ◽

Routine Activity ◽

Imaging Features ◽

Pet Ct ◽

Oncologic Patients ◽

The Many ◽

Fdg Pet Ct ◽

Low Prevalence ◽

Similar Imaging

Abstract Coronavirus disease-19 (COVID-19) is only one of the many possible infectious and non-infectious diseases that may occur with similar imaging features in patients undergoing [18F]-fluorodeoxyglucose (18FDG) monitoring, particularly in the most fragile oncologic patients. We briefly summarise some key radiological elements of differential diagnosis of interstitial lung diseases which, in our opinion, could be extremely useful for physicians reporting 18FDG PET/CT scans, not only during the COVID-19 pandemic, but also for their normal routine activity.

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