Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early-Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study

BACKGROUND

Deep stromal invasion (DSI) is one of the predominant risk factors that determined the types of radical hysterectomy (RH). Thus, the accurate assessment of DSI in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC) can facilitate optimal therapy decision.

PURPOSE

To develop a nomogram to identify DSI in cervical AC/ASC.

STUDY TYPE

Retrospective.

POPULATION

Six hundred and fifty patients (mean age of 48.2 years) were collected from center 1 (primary cohort, 536), centers 2 and 3 (external validation cohorts 1 and 2, 62 and 52).

FIELD STRENGTH/SEQUENCE

5-T, T2-weighted imaging (T2WI, SE/FSE), diffusion-weighted imaging (DWI, EPI), and contrast-enhanced T1-weighted imaging (CE-T1WI, VIBE/LAVA).

ASSESSMENT

The DSI was defined as the outer 1/3 stromal invasion on pathology. The region of interest (ROI) contained the tumor and 3 mm peritumoral area. The ROIs of T2WI, DWI, and CE-T1WI were separately imported into Resnet18 to calculate the DL scores (TDS, DDS, and CDS). The clinical characteristics were retrieved from medical records or MRI data assessment. The clinical model and nomogram were constructed by integrating clinical independent risk factors only and further combining DL scores based on primary cohort and were validated in two external validation cohorts.

STATISTICAL TESTS

Student's t-test, Mann-Whitney U test, or Chi-squared test were used to compare differences in continuous or categorical variables between DSI-positive and DSI-negative groups. DeLong test was used to compare AU-ROC values of DL scores, clinical model, and nomogram.

RESULTS

The nomogram integrating menopause, disruption of cervical stromal ring (DCSRMR), DDS, and TDS achieved AU-ROCs of 0.933, 0.807, and 0.817 in evaluating DSI in primary and external validation cohorts. The nomogram had superior diagnostic ability to clinical model and DL scores in primary cohort (all P < 0.0125 [0.05/4]) and CDS (P = 0.009) in external validation cohort 2.

DATA CONCLUSION

The nomogram achieved good performance for evaluating DSI in cervical AC/ASC.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Intratumoral and peritumoral MRI radiomics nomogram for predicting parametrial invasion in patients with early-stage cervical adenocarcinoma and adenosquamous carcinoma

OBJECTIVE

To develop a comprehensive nomogram based on MRI intra- and peritumoral radiomics signatures and independent risk factors for predicting parametrial invasion (PMI) in patients with early-stage cervical adenocarcinoma (AC) and adenosquamous carcinoma (ASC).

METHODS

A total of 460 patients with IB to IIB cervical AC and ASC who underwent preoperative MRI examination and radical trachelectomy/hysterectomy were retrospectively enrolled and divided into primary, internal validation, and external validation cohorts. The original (Ori) and wavelet (Wav)-transform features were extracted from the volumetric region of interest of the tumour (ROI-T) and 3mm- and 5mm-peritumoral rings (ROI-3 and ROI-5), respectively. Then the Ori and Ori-Wav feature-based radiomics signatures from the tumour (RST) and 3 mm- and 5 mm-peritumoral regions (RS3 and RS5) were independently built and their diagnostic performances were compared to select the optimal ones. Finally, the nomogram was developed by integrating optimal intra- and peritumoral signatures and clinical independent risk factors based on multivariable logistic regression analysis.

RESULTS

FIGO stage, disruption of the cervical stromal ring on MRI (DCSRMR), parametrial invasion on MRI (PMIMR), and serum CA-125 were identified as independent risk factors. The nomogram constructed by integrating independent risk factors, Ori-Wav feature-based RST, and RS5 yielded AUCs of 0.874 (0.810-0.922), 0.885 (0.834-0.924), and 0.966 (0.887-0.995) for predicting PMI in the primary, internal and external validation cohorts, respectively. Furthermore, the nomogram was superior to radiomics signatures and clinical model for predicting PMI in three cohorts.

CONCLUSION

The nomogram can preoperatively, accurately, and noninvasively predict PMI in patients with early-stage cervical AC and ASC.

CLINICAL RELEVANCE STATEMENT

The nomogram can preoperatively, accurately, and noninvasively predict PMI and facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy in patients with early-stage cervical AC and ASC.

KEY POINTS

The accurate preoperative prediction of PMI in early-stage cervical AC and ASC can facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy. The nomogram integrating independent risk factors, Ori-Wav feature-based RST, and RS5 can preoperatively, accurately, and noninvasively predict PMI in early-stage cervical AC and ASC. The nomogram was superior to radiomics signatures and clinical model for predicting PMI in early-stage cervical AC and ASC.

MRI Texture Analysis for Preoperative Prediction of Lymph Node Metastasis in Patients with Nonsquamous Cell Cervical Carcinoma

RATIONALE AND OBJECTIVES

To preoperatively predict lymph node metastasis (LNM) in patients with cervical nonsquamous cell carcinoma (non-SCC) based on magnetic resonance imaging (MRI) texture analysis.

MATERIALS AND METHODS

This retrospective study included 104 consecutive patients (mean age of 47.2 ± 11.3 years) with stage IB-IIA cervical non-SCC. According to the ratio of 7:3, 72, and 32 patients were randomly divided into the training and testing cohorts. A total of 272 original features were extracted. In the process of feature selection, features with intraclass correlation coefficients (ICCs) less than 0.8 were eliminated. The Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) were applied to reduce redundancy, overfitting, and selection biases. Further, a support vector machine (SVM) with linear kernel function was applied to select the optimal feature set with a high discrimination power.

RESULTS

The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI (LN status on MRI)-based SVM models yielded an AUC and accuracy of 0.78 and 0.79; 0.79 and 0.69; 0.79 and 0.81 for predicting LNM in the training cohort, and 0.82 and 0.78; 0.82 and 0.69; 0.79 and 0.72 in the testing cohort. The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI-based SVM models performed better than morphologic criteria of LNS-MRI and yield similar discrimination abilities in predicting LNM in the training and testing cohorts (all p-value > 0.05). In addition, the T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the AC and ASC subgroups (all p-value > 0.05).

CONCLUSION

The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI+DWI+LNS-MRI-based SVM models showed similar good discrimination ability and performed better than the morphologic criteria of LNS-MRI in predicting LNM in patients with cervical non-SCC. The inclusion of the CE-T1WI sequence and morphologic criteria of LNS-MRI did not significantly improve the performance of the T2WI + DWI-based model. The T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the subgroup analysis.

The diagnostic performance of ADC value for tumor grade, deep myometrial invasion and lymphovascular space invasion in endometrial cancer: a meta-analysis

BACKGROUND

Disputes exist regarding whether the apparent diffusion coefficient (ADC) can differentiate the tumor grade, deep myometrial invasion and lymphovascular space invasion (LVSI) in endometrial cancer. The aim of this review was to assess the diagnostic performance of the ADC value in endometrial cancer.

MATERIAL AND METHODS

The PubMed, Web of Science, Embase and Cochrane Library databases were searched for studies that used the ADC value to assess tumor grade, deep myometrial invasion and LVSI in endometrial cancer. We used forest plots to analyze the heterogeneity and generate the pooled sensitivity (SEN) and specificity (SPE). We used summary receiver operating characteristic (SROC) curves to work out the area under the SROC curve (AUC). Likelihood ratios (LRs) were also obtained.

RESULTS

Of the 460 identified studies, 11 studies met our inclusion criteria and were included. Overall, nine studies (491 patients) aimed at differentiating high tumor grade had a pooled SEN, SPE and AUC of 77%, 73% and 81%, respectively; three studies (181 patients) for differentiating deep myometrial invasion had a pooled SEN, SPE and AUC of 71%, 67% and 77%, respectively; and two studies (106 patients) for differentiating LVSI had a pooled SEN and SPE of 66% and 74%, respectively. The positive and negative LRs were 2.77 and 0.35 for the tumor grade, 2.08 and 0.45 for deep myometrial invasion, and 2.48 and 0.45 for LVSI.

CONCLUSION

This meta-analysis showed that the ADC value had a moderate diagnostic performance for the tumor grade, deep myometrial invasion and LVSI in endometrial cancer.

[Efficacy and safety of transbronchial cryobiopsy in the etiologic diagnosis of diffuse lung disease]

Objective: To assess the efficacy and safety of transbronchial cryobiopsy (TBCB) for the etiologic evaluation of diffuse lung disease (DLD). Methods: Between December 2015 to April 2017, a total of 38 patients with DLD met the inclusion criteria for TBCB in the First Affiliated Hospital of Chongqing Medical University, and 35 of them consented to undergo the procedure under rigid or flexible bronchoscopy. On the tissues obtained from the 35 patients, histopathologic and microbiological evaluations were performed, and together with clinical and radiological manifestations, diagnoses were made and the efficacy of TBCB in the diagnosis of DLD was confirmed, and then therapies were planned accordingly. Complications of the biopsy procedures were recorded. Results: Of the 35 patients who were enrolled, 24 underwent TBCB under rigid bronchoscopy and 11 under flexible bronchoscopy. Another 3 patients refused the procedure due to disinclination to invasive examinations. One single procedure of TBCB took (51.8±19.2) min on average, the median number of tissues obtained was 6 (5, 8), and the median area of tissues was 15 (9, 20) mm(2).Definite diagnoses were reached in 33 patients, including idiopathic nonspecific interstitial pneumonia (n=8), connective tissue disease-interstitial lung disease (n=8), occupational lung disease (n=4), idiopathic pulmonary fibrosis (n=3), interstitial pneumonia with autoimmune features (n=3), tuberculosis (n=2), cryptogenic organization pneumonia (n=1), acute interstitial pneumonia (n=1), pulmonary infection (n=1), hypersensitivity pneumonia (n=1) and sarcoidosis (n=1). Diagnostic yield was 94.3% (33 out of 35 cases diagnosed). Pneumothorax occurred in 3 patients (1 patients with mild pneumothorax , 1 moderate and 1 severe), and were resolved with thoracic puncture or pleural drainage. Bleeding occurred in all 24 patients who received TBCB under rigid bronchoscopy (11 patients with mild bleeding, 12 moderate and 1 severe) and was controlled after coagulation measures. After one month of treatment according to the diagnoses acquired with cryobiopsy, the condition was cured in 1 patient (3.0%), alleviated in 17 (51.5%), stable in 11 (33.3%), and deteriorated in 4 (12.1%). Conclusion: TBCB yields reliable diagnoses with a good safety profile.

[Magnetic resonance imaging characteristics of encephalopathy of prematurity]

Objective: To explore the MRI manifestation of encephalopathy of prematurity (EOP), so as to find an access to the early prevention, early diagnosis, effective treatment and prognosis. Methods: A total of 2 718 premature infants were collected, MRI and clinical data were analyzed who were admitted to NICU of Children's Hospital of Fudan University between January 1, 2009 and December 31, 2014. The manifestation and lesions distribution in MRI were analyzed. Results: All the 2 718 preterm infants underwent MRI. 58.8% (1 599/2 718) of which had normal MRI apperance, whereas 24.9% (678/2 718) showed manifestations of EOP.78.8% (534/678) EOP were non-cystic EOP. 21.2% (144/678) EOP were cystic EOP. Periventricular and cerebral lobe white matter were primary distributions of these lesions. Cystic lesions were primarily distributed in the body of periventricular whiter matter (49.3%). However, more non-cystic EOP were found in cerebral parietal lobe whiter matter (25.1%). Non-cystic EOP were also distributed in the body of periventricular whiter matter, frontal lobe and basal ganglia(20.8%, 20.2% and 18.9%, respectively ). Conclusions: The morbidity rate of EOP in preterm infants was 24.9%. 21.2% (144/678) EOP were cystic EOP. 78.8% (534/678) EOP were non-cystic EOP. Cystic lesions were primarily distributed in the body of periventricular whiter matter. Non-cystic EOP were also distributed in the body of periventricular whiter matter, frontal lobe and basal ganglia.