Investigation of the clinical implications of anterior cervical invasion in locally advanced cervical squamous cell carcinoma.

PURPOSES: This study investigates the clinical significance of the anterior parametrical invasion in surgically treated patients with cervical squamous cell carcinoma (SCC). METHODS: We included patients diagnosed with cervical SCC with local lesions classified as T2b, who were treated at our department between January 2006 and December 2020. We evaluated the degree of anterior invasion using pretreatment magnetic resonance imaging and divided patients into three groups: partial, equivocal, and full invasion. The frequency of recurrence within 3 years (early recurrence) and overall prognosis were assessed. RESULTS: There were 12, 24, and 46 cases in the partial equivocal, and full invasion groups, respectively. Neoadjuvant chemotherapy followed by surgery and adjuvant chemotherapy was the mainstay of treatment across all groups (7, 17, and 27 cases, respectively). Although the frequency of early recurrence tended to be worse in the full group (partial; 2/7 cases, equivocal; 3/17 cases and full; 9/27 cases), all early local recurrence cases in the full group (four cases) responded well to the subsequent treatment. As for overall survival, the full invasion group had the best prognosis among the three groups. CONCLUSIONS: In surgical treatment, although full anterior invasion may increase the risk of early local recurrence, it was considered to have little prognostic impact.

Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023.

The staging of endometrial cancer is based on the International Federation of Gynecology and Obstetrics (FIGO) staging system according to the examination of surgical specimens, and has revised in 2023, 14 years after its last revision in 2009. Molecular and histological classification has incorporated to new FIGO system reflecting the biological behavior and prognosis of endometrial cancer. Nonetheless, the basic role of imaging modalities including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography, as a preoperative assessment of the tumor extension and also the evaluation points in CT and MRI imaging are not changed, other than several point of local tumor extension. In the field of radiology, it has also undergone remarkable advancement through the rapid progress of computational technology. The application of deep learning reconstruction techniques contributes the benefits of shorter acquisition time or higher quality. Radiomics, which extract various quantitative features from the images, is also expected to have the potential for the quantitative prediction of risk factors such as histological types and lymphovascular space invasion, which is newly included in the new FIGO system. This article reviews the preoperative imaging diagnosis in new FIGO system and recent advances in imaging analysis and their clinical contributions in endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Nodal infiltration in endometrial cancer: a prediction model using best subset regression.

OBJECTIVES: To build preoperative prediction models with and without MRI for regional lymph node metastasis (r-LNM, pelvic and/or para-aortic LNM (PENM/PANM)) and for PANM in endometrial cancer using established risk factors. METHODS: In this retrospective two-center study, 364 patients with endometrial cancer were included: 253 in the model development and 111 in the external validation. For r-LNM and PANM, respectively, best subset regression with ten-time fivefold cross validation was conducted using ten established risk factors (4 clinical and 6 imaging factors). Models with the top 10 percentile of area under the curve (AUC) and with the fewest variables in the model development were subjected to the external validation (11 and 4 candidates, respectively, for r-LNM and PANM). Then, the models with the highest AUC were selected as the final models. Models without MRI findings were developed similarly, assuming the cases where MRI was not available. RESULTS: The final r-LNM model consisted of pelvic lymph node (PEN) ≥ 6 mm, deep myometrial invasion (DMI) on MRI, CA125, para-aortic lymph node (PAN) ≥ 6 mm, and biopsy; PANM model consisted of DMI, PAN, PEN, and CA125 (in order of correlation coefficient ß values). The AUCs were 0.85 (95%CI: 0.77-0.92) and 0.86 (0.75-0.94) for the external validation, respectively. The model without MRI for r-LNM and PANM showed AUC of 0.79 (0.68-0.89) and 0.87 (0.76-0.96), respectively. CONCLUSIONS: The prediction models created by best subset regression with cross validation showed high diagnostic performance for predicting LNM in endometrial cancer, which may avoid unnecessary lymphadenectomies. CLINICAL RELEVANCE STATEMENT: The prediction risks of lymph node metastasis (LNM) and para-aortic LNM can be easily obtained for all patients with endometrial cancer by inputting the conventional clinical information into our models. They help in the decision-making for optimal lymphadenectomy and personalized treatment. KEY POINTS: •Diagnostic performance of lymph node metastases (LNM) in endometrial cancer is low based on size criteria and can be improved by combining with other clinical information. •The optimized logistic regression model for regional LNM consists of lymph node ≥ 6 mm, deep myometrial invasion, cancer antigen-125, and biopsy, showing high diagnostic performance. •Our model predicts the preoperative risk of LNM, which may avoid unnecessary lymphadenectomies.

Risk Stratification for Pregnancies Diagnosed With Fetal Growth Restriction Based on Placental MRI.

BACKGROUND: Diagnosis of fetal growth restriction (FGR) entails difficulties with differentiating fetuses not fulfilling their growth potential because of pathologic conditions, such as placental insufficiency, from constitutionally small fetuses. The feasibility of placental MRI for risk stratification among pregnancies diagnosed with FGR remains unexplored. PURPOSE: To explore quantitative MRI features useful to identify pregnancies with unfavorable outcomes and to assess the diagnostic performance of visual analysis of MRI to detect pregnancies with unfavorable outcomes, among pregnancies diagnosed with FGR. STUDY TYPE: Retrospective. POPULATION: Thirteen pregnancies with unfavorable outcomes (preterm emergency cesarean section or intrauterine fetal death) and 11 pregnancies with favorable outcomes performed MRI at gestational weeks 21-36. FIELD STRENGTH/SEQUENCE: A 5-T, half-Fourier-acquired single-shot turbo spin echo (HASTE), spin-echo echo-planar imaging (SE-EPI) and T2 map derived from SE-EPI. ASSESSMENT: Placental size on HASTE sequences and T2 mapping-based histogram features were extracted. Three radiologists qualitatively evaluated the visibility of maternal cotyledon on HASTE and SE-EPI sequences with echo times (TEs) = 60, 90, and 120 msec using 3-point Likert scales: 0, absent; 1, equivocal; and 2, present. STATISTICAL TESTS: Welch's t-test or Mann-Whitney U test for quantitative features between the favorable and unfavorable outcome groups. Areas under the receiver operating curves (AUCs) of the three readers' visual analyses to detect pregnancies with unfavorable outcomes. A P value of <0.05 was inferred as statistically significant. RESULTS: Placental size (major and minor axis, estimated area of placental bed, and volume of placenta) and T2 mapping-based histogram features (mean, skewness, and kurtosis) were statistically significantly different between the two groups. Visual analysis of HASTE and SE-EPI with TE = 60 msec showed AUCs of 0.80-0.86 to detect pregnancies with unfavorable outcomes. DATA CONCLUSION: Placental size, histogram features, and visual analysis of placental MRI may allow for risk stratification regarding outcomes among pregnancies diagnosed with FGR. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Advantage of a higher position of the tracheostoma with glottic closure for preventing complications related to tracheostomy tube: a retrospective cohort study.

BACKGROUND: Surgery to prevent aspiration has complications related to tracheostomy tube, such as the trachea-brachiocephalic artery fistula. Glottic closure procedure makes tracheostoma at a position higher than the first ring of the trachea and theoretically has a potential to prevent such complications owing to a longer distance between the tip of tracheostomy tube and the tracheal membrane adjacent to the brachiocephalic artery. Our aim is to evaluate the safety of glottic closure in neurologically impaired patients by comparing outcomes with laryngotracheal separation. METHODS: This study is a single-center retrospective study from 2004 to 2019, using data of 15 and 12 patients who underwent glottic closure (GC) and laryngotracheal separation (LTS). The primary outcome was the incidence of postoperative complications induced by tracheostomy tube placement and adjustment of the tracheostomy tube position to prevent these complications, such as by converting to a length-adjustable tube and/or placing gauze between the skin and tube flange. Additionally, we analyzed the anatomical relationship between the tracheostomy tube tip and brachiocephalic artery and measured the distance between them using postoperative CT images. RESULTS: No patients in either group had trachea-brachiocephalic artery fistula. Erosion or granuloma formation occurred in 1 patient (7%) and 4 patients (33%) in the GC and LTS groups, respectively. Adjustment of the tracheostomy tube was needed in 2 patients (13%) and 6 patients (50%) in the GC and LTS groups. CT revealed a higher proportion of patients with the tracheostomy tube tip superior to the brachiocephalic artery in GC than LTS group. The mean tracheostoma-brachiocephalic artery distance was 40.8 and 32.4 mm in the GC and LTS groups. CONCLUSIONS: Glottic closure reduces the risk of postoperative complications related to a tracheostomy tube. This may be due to the higher position of the tracheostoma at the level of the cricoid cartilage, increasing the distance between the tracheostoma and brachiocephalic artery.

Diagnostic Accuracy of Magnetic Resonance Imaging for International Federation of Gynecology and Obstetrics 2018 IB to IIB Cervical Cancer Staging: Comparison Among Magnetic Resonance Sequences and Pathologies.

OBJECTIVE: This study aimed to investigate the most accurate magnetic resonance (MR) sequence for tumor detection, maximal tumor diameter, and parametrial invasion compared with histopathologic diagnoses. METHODS: Fifty-one patients with International Federation of Gynecology and Obstetrics 2018 IB1 to IIB cervical cancer underwent preoperative MR imaging and surgical resection. Two radiologists independently evaluated the tumor detection, parametrial invasion, and tumor size in each of T2-weighted image, diffusion-weighted image, and contrast-enhanced T1-weighted image. Results obtained for squamous cell carcinoma (SCC) and adenocarcinoma were also compared. RESULTS: Neither the tumor detection rate nor parametrial invasion was found to be significantly different among sequences. Tumor size assessment using MR imaging with pathology showed good correlation: r = 0.63-0.72. The adenocarcinoma size tended to be more underestimated than SCC in comparison with the pathologic specimen. CONCLUSIONS: Cervical cancer staging by MR images showed no significant difference among T2-weighted image, diffusion-weighted image, and contrast-enhanced T1-weighted image. Adenocarcinoma was prone to be measured as smaller than the pathologic specimen compared with SCC.

Diffusion-weighted imaging of uterine adenomyosis: Correlation with clinical backgrounds and comparison with malignant uterine tumors.

AIM: To elucidate correlation between signal intensity on diffusion-weighted images (SI-DWI) and clinical backgrounds for uterine adenomyosis and to compare SI-DWI of adenomyosis and malignant uterine tumors. METHODS: This study examined 46 adenomyosis patients diagnosed using magnetic resonance imaging and 25 patients with surgically confirmed malignant uterine myometrial tumor. First, adenomyosis cases were classified visually into high-intensity and low-intensity groups based on the SI-DWI compared with that of normal uterine myometrium. Secondly, correlation was assessed between SI-DWI of adenomyosis and patient clinical background information such as age, menopausal status, menstrual cycle and dysmenorrhea severity. Third, quantitative comparison was made of low-intensity adenomyosis (LIA), high-intensity adenomyosis (HIA) and malignant tumor groups for the signal intensity ratio (SIR) on DWI and the apparent diffusion coefficient (ADC). Their diagnostic performance was evaluated using logistic regression analysis and receiver operating characteristic (ROC) analysis. RESULTS: The 46 adenomyosis cases were classified as 26 low-intensity and 20 high-intensity cases. Significant correlation was found only for menstrual cycle phases. HIA had significantly lower SIR and higher ADC than malignant tumor. The ADC of HIA was significantly higher than that of LIA. The combination of SIR and ADC showed excellent diagnostic performance (area under ROC curve, 0.99). CONCLUSION: There is a variation in signal intensity on DWI of uterine adenomyosis and it is associated with menstrual cycle phase. Adenomyosis with high signal intensity on DWI can be differentiated from malignant lesions by its lower signal intensity on DWI and higher ADC than that found for malignant uterine tumors, however overlaps exist.

Amino acid losses are lower during pre-dilution on-line HDF than HD of the same Kt/V for urea.

In this study, we investigated differences in amino acid losses between HD and pre-dilution on-line HDF with equal Kt/V for urea to determine which modality removes less amino acids from extravascular pools and ensures better nutrition. The subjects were patients receiving pre-dilution on-line HDF (n = 10) or HD (n = 10) at this hospital. Dialysis time was 4 h for all patients. In patients on HD, the blood flow rate was 200 mL/min and the dialysate flow rate was 463 ± 29.3 mL/min. In patients on pre-dilution on-line HDF, the blood flow rate was 240 ± 20 mL/min, the dialysate flow rate was 565.0 ± 42.5 mL/min, and the substitution flow rate (substitution volume) was 252.8 ± 26.4 mL/min (57.0 ± 6.0 L). Kt/V for urea was comparable between patients on HD and patients on pre-dilution on-line HDF (1.46 ± 0.25 vs. 1.46 ± 0.31). Amino acid loss and clear space were evaluated. Patients on pre-dilution on-line HDF lost significantly less glutamine and arginine (p < 0.01 and p = 0.032) and significantly less nonessential amino acids (NEAAs) than patients on HD (p = 0.013). They also had significantly lower clear space of total amino acids (TAAs), NEAAs, essential amino acids (EAAs), and branched-chain amino acids (BCAAs) than patients on HD (Total AA p = 0.019, NEAA p = 0.018, EAA p = 0.024, BCAA p = 0.042). When Kt/V for urea is equal, pre-dilution on-line HDF ensures better nutrition than does HD.

Restless legs syndrome effectively treated with constant-pressure predilution online hemodiafiltration.

BACKGROUND: We encountered a case of unstable predilution online HDF due to elevated transmembrane pressure (TMP) when performing constant-speed predilution online hemodiafiltration (HDF) as treatment for restless legs syndrome (RLS) in a dialysis patient. We report the effectiveness of incorporating a newly developed constant-pressure predilution online HDF system as a preventive measure against unstable online HDF and frequent adjustment of settings when treating dialysis patients with RLS. CASE PRESENTATION: A 55-year-old man had suffered from RLS and been undergoing constant-speed online HDF with 45 L target predilution and an ABH-21P hemodiafilter. The symptoms of RLS rated 10 on the International Restless Legs Syndrome Rating Scale (IRLS). The α1-microglobulin (α1-MG) removal rate was only 27.8%, so the hemodiafilter was subsequently replaced with a PEPA hemodiafilter. However, episodes of elevated TMP exceeding 250 mmHg occurred frequently after the replacement and were managed by reducing dialysate flow rate. Therefore, we incorporated a constant-pressure predilution online HDF that maintains TMP below 200 mmHg. The amount of replacement was maintained at approximately 43.5 ± 6.98 L and the α1-MG removal rate was 39.5%, with no need to manually reduce the flow rate. The Alb leakage in dialysate waste was 7.9 g. The patient has maintained an IRLS rating of 0 with no RLS symptoms for the past 4 years. CONCLUSIONS: Using the constant-pressure mode enabled achieved the clinical endpoint, namely, resolution of RLS with no need to manually reduce the flow rate.

A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient.

OBJECTIVES: The aim of this study was to assess the prognostic and incremental value of pretreatment apparent diffusion coefficient (ADC) values of tumors for the prediction of tumor recurrence after complete resection of the tumor in patients with endometrial cancer. METHODS: This study enrolled 210 patients with stages IA to IIIC endometrial cancer who had undergone complete resection of the tumor and pretreatment magnetic resonance imaging. The minimum and mean ADC values (ADCmin, ADCmean) of tumors and normalized ADC (nADCmin, nADCmean) were calculated from magnetic resonance imaging. The primary outcome was recurrence-free survival (RFS). Receiver operating characteristic analysis was performed to compare the diagnostic performance of ADC values of 4 types. The Kaplan-Meier method, log-rank tests, and Cox regression were used to explore associations between recurrence and the ADC values with adjustment for clinicopathological factors. RESULTS: In receiver operating characteristic curve analysis, the areas under the curve were significant for ADCmean and nADCmean predicting tumor recurrence but were not significant for ADCmin and nADCmin. Regarding univariate analysis, ADCmean and nADCmean were significantly associated with increased risk of recurrence. Multivariate analysis showed that ADCmean and nADCmean remained independently associated with shorter RFS. In the high-risk group, the RFS of patients with lower ADC values (ADCmean and nADCmean) was significantly shorter than that of patients in the higher ADC value group. CONCLUSIONS: Pretreatment tumor ADCmean and nADCmean were important imaging biomarkers for predicting recurrence in patients after complete resection of the tumor. They might improve existing risk stratification.

Diagnostic performance of MR imaging findings and quantitative values in the differentiation of seromucinous borderline tumour from endometriosis-related malignant ovarian tumour.

OBJECTIVES: To evaluate the diagnostic performance of quantitative values and MRI findings for differentiating seromucinous borderline tumours (SMBTs) from endometriosis-related malignant ovarian tumours (MT). METHODS: This retrospective study examined 19 lesions from SMBT and 84 lesions from MT. The following quantitative values were evaluated using receiver-operating characteristic analysis: overall and solid portion sizes, fluid signal intensity (SI), degree of contrast-enhancement, and mean and minimum apparent diffusion coefficient (ADC) values of the solid portion. Two radiologists independently evaluated four MRI findings characteristic of SMBT, fluid SI on the T1-weighted image and SI of the solid portion on diffusion-weighted image. The diagnostic values of these findings and interobserver agreement were assessed. RESULTS: For diagnosing SMBT, the mean ADC value of the solid portion showed the greatest area under the curve (0.860) (cut-off value: 1.31 × 10-3 mm2/s, sensitivity: 1.00, specificity: 0.61). The T2-weighted image (T2WI) high SI solid portion was the most useful finding, with high specificity and interobserver agreement (sensitivity, 0.58; specificity, 0.95-0.96, kappa = 0.96), followed by T2WI low SI core (sensitivity, 0.48-0.63; specificity, 0.98, kappa = 0.68). CONCLUSION: Mean ADC values of the solid portion, T2WI high SI solid portion, and T2WI low SI core were useful for differentiating SMBT from MT. KEY POINTS: • SMBT is a newly categorised ovarian tumour often associated with endometriosis. • Differentiation of SMBT from endometriosis-related malignant ovarian tumour is clinically important. • Diagnostic performances of quantitative values and MRI findings were evaluated. • Mean ADC value of the solid portion was the most useful value. • "T2WI high SI solid portion" was the most useful MRI finding.

Uterine peristalsis and junctional zone: correlation with age and postmenopausal status.

Background Although age-related change of junctional zone (JZ) of the uterus has been known, there has been no previous systematic study of age-related changes of uterine peristalsis that is observed as the wave conduction of the thickest or darkest area within the JZ. Purpose To examine the age-related changes of uterine peristalsis in pre and postmenopausal women using cine magnetic resonance imaging (MRI), and to determine the correlation between peristalsis and JZ on T2-weighted (T2W) imaging. Material and Methods Cine MRI analysis was performed in 64 premenopausal volunteers and in 43 postmenopausal women. The peristaltic frequency, JZ detectability, and JZ thickness were evaluated and compared between the two groups. In the premenopausal group, the correlations between age and each item was examined. In the postmenopausal group, the number of years after menopause was used instead of age. The correlation between peristaltic frequency and JZ detectability or thickness was also analyzed. Results Peristaltic frequency and JZ detectability significantly differed between the two groups, while JZ thickness did not. Peristaltic frequency did not vary significantly with age before menopause and no peristalsis was observed after menopause. JZ detectability did not change significantly with age or number of years after menopause, while JZ thickness significantly increased with age before menopause, but did not vary after menopause. A significant moderate correlation was observed between JZ detectability and peristaltic frequency, but not between JZ thickness and peristaltic frequency. Conclusion Uterine peristalsis frequency did not change significantly according to age, but observed peristalsis on MRI significantly decreased after menopause.

Two cases of Wolffian tumor with novel magnetic resonance imaging findings reflecting characteristic pathology.

A Wolffian tumor is a rare tumor arising from the remnants of the mesonephric duct. Herein, we report two cases. A 61-year-old woman presented with swollen left adnexa. On T2 weighted magnetic resonance imaging (MRI), a 4.4 cm solid pelvic mass showed slightly high signal intensity, with a low-signal-intensity rim. Microscopically, cuboidal cells with bland nuclei were arranged in a dense tubular form. A 40-year-old woman complained of lower abdominal pain. On T2 weighted MRI, a 6.0 cm solid mass with a low-signal-intensity rim was found. The pathology of the resected tumor was similar to that of case 1. Both cases were diagnosed as Wolffian tumor. The rims of the tumors in both cases were composed of eosinophilic spindle-shaped cells immunoreactive to alpha-smooth muscle actin and desmin, identical to the smooth muscle cells surrounding the mesonephric duct remnants. MRI findings reflecting smooth muscle rims might contribute to an accurate preoperative diagnosis of this rare tumor.

Development of deep learning model for diagnosing muscle-invasive bladder cancer on MRI with vision transformer.

Rationale and objectives: To develop and validate a deep learning (DL) model to automatically diagnose muscle-invasive bladder cancer (MIBC) on MRI with Vision Transformer (ViT). Materials and methods: This multicenter retrospective study included patients with BC who reported to two institutions between January 2016 and June 2020 (training dataset) and a third institution between May 2017 and May 2022 (test dataset). The diagnostic model for MIBC and the segmentation model for BC on MRI were developed using the training dataset with 5-fold cross-validation. ViT- and convolutional neural network (CNN)-based diagnostic models were developed and compared for diagnostic performance using the area under the curve (AUC). The performance of the diagnostic model with manual and auto-generated regions of interest (ROImanual and ROIauto, respectively) was validated on the test dataset and compared to that of radiologists (three senior and three junior radiologists) using Vesical Imaging Reporting and Data System scoring. Results: The training and test datasets included 170 and 53 patients, respectively. Mean AUC of the top 10 ViT-based models with 5-fold cross-validation outperformed those of the CNN-based models (0.831 ± 0.003 vs. 0.713 ± 0.007-0.812 ± 0.006, p < .001). The diagnostic model with ROImanual achieved AUC of 0.872 (95 % CI: 0.777, 0.968), which was comparable to that of junior radiologists (AUC = 0.862, 0.873, and 0.930). Semi-automated diagnosis with the diagnostic model with ROIauto achieved AUC of 0.815 (95 % CI: 0.696, 0.935). Conclusion: The DL model effectively diagnosed MIBC. The ViT-based model outperformed CNN-based models, highlighting its utility in medical image analysis.

Label Distribution Learning for Automatic Cancer Grading of Histopathological Images of Prostate Cancer.

We aimed to develop and evaluate an automatic prediction system for grading histopathological images of prostate cancer. A total of 10,616 whole slide images (WSIs) of prostate tissue were used in this study. The WSIs from one institution (5160 WSIs) were used as the development set, while those from the other institution (5456 WSIs) were used as the unseen test set. Label distribution learning (LDL) was used to address a difference in label characteristics between the development and test sets. A combination of EfficientNet (a deep learning model) and LDL was utilized to develop an automatic prediction system. Quadratic weighted kappa (QWK) and accuracy in the test set were used as the evaluation metrics. The QWK and accuracy were compared between systems with and without LDL to evaluate the usefulness of LDL in system development. The QWK and accuracy were 0.364 and 0.407 in the systems with LDL and 0.240 and 0.247 in those without LDL, respectively. Thus, LDL improved the diagnostic performance of the automatic prediction system for the grading of histopathological images for cancer. By handling the difference in label characteristics using LDL, the diagnostic performance of the automatic prediction system could be improved for prostate cancer grading.

Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study.

This study aimed to develop a versatile automatic segmentation model of bladder cancer (BC) on MRI using a convolutional neural network and investigate the robustness of radiomics features automatically extracted from apparent diffusion coefficient (ADC) maps. This two-center retrospective study used multi-vendor MR units and included 170 patients with BC, of whom 140 were assigned to training datasets for the modified U-net model with five-fold cross-validation and 30 to test datasets for assessment of segmentation performance and reproducibility of automatically extracted radiomics features. For model input data, diffusion-weighted images with b = 0 and 1000 s/mm2, ADC maps, and multi-sequence images (b0-b1000-ADC maps) were used. Segmentation accuracy was compared between ours and existing models. The reproducibility of radiomics features on ADC maps was evaluated using intraclass correlation coefficient. The model with multi-sequence images achieved the highest Dice similarity coefficient (DSC) with five-fold cross-validation (mean DSC = 0.83 and 0.79 for the training and validation datasets, respectively). The median (interquartile range) DSC of the test dataset model was 0.81 (0.70-0.88). Radiomics features extracted from manually and automatically segmented BC exhibited good reproducibility. Thus, our U-net model performed highly accurate segmentation of BC, and radiomics features extracted from the automatic segmentation results exhibited high reproducibility.

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.

MRI in the Diagnosis of Endometriosis and Related Diseases.

Endometriosis, a common chronic inflammatory disease in female of reproductive age, is closely related to patient symptoms and fertility. Because of its high contrast resolution and objectivity, MRI can contribute to the early and accurate diagnosis of ovarian endometriotic cysts and deeply infiltrating endometriosis without the need for any invasive procedure or radiation exposure. The ovaries, which are the most frequent site of endometriosis, can be afflicted by multiple related conditions and diseases. For the diagnosis of deeply infiltrating endometriosis and secondary adhesions among pelvic organs, fibrosis around the ectopic endometrial gland is usually found as a T2 hypointense lesion. This review summarizes the MRI findings obtained for ovarian endometriotic cysts and their physiologically and pathologically related conditions. This article also includes the key imaging findings of deeply infiltrating endometriosis.

MR findings of polypoid endometriosis of female genital organs: report of three cases.

Polypoid endometriosis is a benign, rare variant of endometriosis that forms polypoid nodules mimicking malignant tumors. For three cases of polypoid endometriosis of female genital organs, this report presents characteristic MR imaging features reflecting the histopathological findings. The solid and microcystic pattern or the multilocular pattern both reflecting dilated endometrial glands, and characteristic morphology of the nodules, multilobulated or polypoid-shaped, were helpful diagnostic clues present in these three cases. Earlier reported MR findings were also recognized, including signal intensity similar to that of the endometrium on T2-weighted image and contrast enhanced T1-weighted image, hypointense rim on T2-weighted image, lack of diffusion restriction, and hyperintense foci on T1-weighted image. Two cases were diagnosed preoperatively based on MR imaging findings as polypoid endometriosis. Fertility-preserving treatment was administered for one patient. Preoperative inference of polypoid endometriosis from MR imaging can avoid overtreatment and lead to fertility preservation.