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.

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.

Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis.

AIM: Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis. MATERIALS AND METHODS: Twenty-five VX2 lung transplant tumors of twenty-two rabbits were included in the study. Contrast-enhanced spectral CT scanning in the arterial phase (AP) and venous phase (VP) was performed. Tumors were divided into strong and weak hypoxic groups by hypoxic probe staining results. Spectral CT image-related parameters [70 keV CT value, normalized iodine concentration (NIC), slope of spectral HU curve (λHU)] were measured and the texture analysis on the monochromatic images was performed. Imaging parameters and texture features between tumors with different hypoxic degrees were compared and their diagnostic efficacies for predicting hypoxia in lung cancers were analyzed using receiver operating characteristic (ROC) curve. RESULTS: NIC in VP and λHU in VP of the strong hypoxic group were significantly higher than those in the weak hypoxic group (p < 0.05). For the texture features, entropy in VP and kurtosis in AP were significantly different between the two hypoxic groups. According to ROC analysis, λHU in VP had a better diagnostic ability for predicting hypoxia in tumors [Area Under Curve (AUC): 0.883, sensitivity: 85.7%, specificity: 100%]. The combination of four features improved AUC to 0.955. CONCLUSION: NIC in VP, λHU in VP, entropy in VP and kurtosis in AP have certain values in predicting tumor hypoxia and a combination of image parameters and texture features improves diagnostic efficiency.

Determining the invasiveness of pure ground-glass nodules using dual-energy spectral computed tomography.

BACKGROUND: The present work aimed to investigate the clinical application of using quantitative parameters generated in the unenhanced phase (UP) and venous phase (VP) in dual-energy spectral CT for differentiating the invasiveness of pure ground-glass nodule (pGGN). METHODS: Sixty-two patients with 66 pGGNs who underwent preoperative dual-energy spectral CT in UP and VP were evaluated retrospectively. Nodules were divided into three groups based on pathology: adenocarcinoma in situ (AIS, n=19), minimally invasive adenocarcinoma (MIA, n=22) (both in the preinvasive lesion group) and invasive adenocarcinoma (IA, n=25). The iodine concentration (IC) and water content (WC) in nodules were measured in material decomposition images. The nodule CT numbers and slopes(k) were measured on monochromatic images. All measurements, including the maximum diameter of nodules were statistically compared between the AIS-MIA group and IA group. RESULTS: There were significant differences of WC in VP between AIS-MIA group and IA group (P<0.05). The CT attenuation values of the 40-140 keV monochromatic images in UP and VP were significantly higher for the invasive nodules. Logistic regression analysis showed that the maximum nodule diameter [odd ratio (OR) =1.21, 95% CI: 1.050-1.400, P<0.01] and CT number in 130 keV images in venous phase (OR =1.03, 95% CI: 1.014-1.047, P<0.001) independently predicted histological invasiveness. CONCLUSIONS: The quantitative parameters in dual-energy spectral CT in the unenhanced phase and venous phase provide useful information in differentiating preinvasive lesion group from IA group of pGGN, especially the maximum nodule diameter and CT number in the 130 keV images in the venous phase.

Quantitative assessment of angiographic perfusion reduction using color-coded digital subtraction angiography during transarterial chemoembolization.

PURPOSE: The aim of this study was to develop a quantitative measurement of perfusion reduction using color-coded digital subtraction angiography (ccDSA) to monitor intra-procedural arterial stasis during TACE. MATERIALS AND METHODS: A total number of 35 patients with hepatocellular carcinoma who had undergone TACE were enrolled into the study. Pre- and post-two-dimensional digital subtraction angiography scans were conducted with same protocol and post-processed with ccDSA prototype software. Time-contrast-intensity (CI[t]) curve was obtained by region-of-interest (ROI) measurement on the generated ccDSA image. Quantitative 2D perfusion parameters time to peak, area under the curve (AUC), maximum upslope, and contrast intensity peak (CI-Peak) derived from the ROI-based CI[t] curve for pre- and post-TACE were evaluated to assess the reduction of antegrade blood flow and tumor blush. Relationships between 2D perfusion parameters, subjective angiographic chemoembolization endpoint (SACE) scale, and clinical outcomes were analyzed. RESULTS: Area normalized AUC and CI-Peak revealed significant reduction after the TACE (P < 0.0001). AUCnorm decreased from pre-procedure of 0.867 ± 0.242 to 0.421 ± 0.171 (P < 0.001) after completion of TACE. CI-Peaknorm was 0.739 ± 0.221 before TACE and 0.421 ± 0.174 (P < 0.001) after TACE. Tumor blood supply time slowed down obviously after embolization. A perfusion reduction either from AUCnorm or CI-Peaknorm ranging from 30% to 40% was associated with SACE level III and a reduction ranging from 60% to 70% was equivalent to SACE level IV. For intermediate reduction (SACE level III), better tumor response was found after TACE rather than a higher reduction (SACE level IV). CONCLUSION: ccDSA application provides an objective approach to quantify the perfusion reduction and subjectively evaluate the arterial stasis of antegrade blood flow and tumor blush caused by TACE.

Differentiation of lung cancers from inflammatory masses with dual-energy spectral CT imaging.

RATIONALE AND OBJECTIVES: To investigate the value of dual-energy spectral computed tomography (DESCT) in the quantitative differentiation between pulmonary malignant masses and inflammatory masses. MATERIALS AND METHODS: This study was an institutional review board-approved study, and written informed consent was obtained from all patients. Sixty patients with 35 lung cancers and 25 inflammatory masses underwent DESCT scan during arterial phase (AP) and venous phase (VP). CT numbers of net enhancement in 70 keV monochromatic images in central and peripheral regions of masses and their differences (dCT) were measured. Iodine concentrations in the two regions were measured and normalized to the aorta as normalized iodine concentrations (NICs). The slopes of spectral attenuation curves (λHU) in the two regions were also calculated. The two-sample t test was used to compare quantitative parameters. Receiver operating characteristic (ROC) curves were generated to calculate sensitivity and specificity. RESULTS: CT numbers of net enhancement and NICs in central regions, and λHU values both in the central and peripheral region of lung cancers were significantly lower than those of inflammatory masses during AP and VP. On the other hand, the dCT values of lung cancers were higher than that of inflammatory masses. NIC value in the central regions in VP had the highest sensitivity (86%) and specificity (100%) in differentiating malignant masses from inflammatory masses. CONCLUSIONS: DESCT imaging with quantitative parameters such as CT numbers of 70 keV monochromatic images, NIC, and λHU may be a new method for differentiating lung cancers from inflammatory masses.

Entropy of T2-weighted imaging combined with apparent diffusion coefficient in prediction of uterine leiomyoma volume response after uterine artery embolization.

RATIONALE AND OBJECTIVES: To determine the potential value of entropy of T2-weighted imaging combined with apparent diffusion coefficient (ADC) before uterine artery embolization (UAE) for prediction of uterine leiomyoma volume reduction (VR) after UAE. MATERIALS AND METHODS: In this prospective study, 11 patients with uterine leiomyomas who underwent pelvic magnetic resonance imaging including diffusion-weighted imaging before and 6 months after UAE were included. A total number of 16 leiomyomas larger than 2 cm in diameter were evaluated. The volume of each leiomyoma before and after UAE was determined, and the percentage change in volume was calculated. Entropy of T2-weighted imaging and ADC before UAE were assessed. Pearson correction coefficients were calculated between leiomyoma VR after UAE and age, leiomyoma volume, ADC, and entropy, respectively. Multiple regression analysis was performed to investigate the parameters that determine the VR after UAE. Receiver operating characteristic curve analysis was used to determine the sensitivity and specificity of ADC, entropy and the combination of ADC and entropy for predicting volume response. RESULTS: The mean leiomyoma VR was 58.9% (range 25.8%-95.0%) in the 6-month follow-up. The mean ADC of leiomyomas was 1.37 × 10(-3) mm(2)/s (range 1.05 × 10(-3)-2.32 × 10(-3) mm(2)/s) and the mean entropy of T2-weighted imaging was 5.36 (range 4.62-5.91) before UAE. ADC and entropy were significantly correlated with leiomyoma VR, respectively (r = 0.61, P = .012; r = 0.73, P = .001). On multiple regression analysis, a combination of ADC and entropy constituted the best model for determining leiomyoma VR using Akaike information criterion. For predicting ≥50% VR, the optimal cutoff value of ADC was 1.39 × 10(-3) mm(2)/s (sensitivity 45.5%, specificity 80.0%) and the optimal cutoff value of entropy was 5.15 (sensitivity 90.9%, specificity 60.0%). The combination of ADC and entropy (area under the curve [AUC] 0.86) provided better classification accuracy than ADC or entropy alone (AUC 0.69 and 0.82, respectively). CONCLUSIONS: Pre-UAE entropy of T2-weighted imaging and ADC of leiomyomas were significantly correlated with the leiomyoma VR 6 months after embolization. Higher entropy and higher ADC may be related to greater leiomyoma VR after UAE. A combination of entropy and ADC may have predictive value for leiomyoma VR after UAE.

Gadolinium-chitosan nanoparticles as a novel contrast agent for potential use in clinical bowel-targeted MRI: a feasibility study in healthy rats.

BACKGROUND: MRI is of increasing importance in the diagnostic evaluation of gastrointestinal diseases, with depiction of mucosal enhancement obtained with conventional intravenous contrast. Routine clinical use of contrast agents has been carried out using intravenous injection for mucosal imaging. Contrast agents that specifically target the intestinal mucosa are therefore needed to improve clinical imaging of the mucosal surface. PURPOSE: To synthesize a novel contrast agent for gadopentetic acid (Gd-DTPA)-loaded chitosan nanoparticles and observe the absorption of the nanoparticles in the colon wall of healthy rats by MR imaging in vivo. MATERIAL AND METHODS: A contrast agent was successfully synthesized by a modified emulsion coalescence method, and the resulting agents were characterized in detail by dynamic light-scattering spectroscopy and inductively coupled plasma emission spectroscopy. The cytotoxicity of Gd-chitosan nanoparticles was evaluated by an MTT assay. Gadolinium-chitosan (Gd@chitosan) nanoparticles were administered to the colon mucosa of healthy rats by rectal administration, and MRI scans in vivo were carried out with a 3.0 T imaging scanner at various time points. RESULTS: The prepared Gd@chitosan nanoparticles were ~420 nm in diameter with a 74.4% Gd-DTPA content. The MTT assay indicated little cytotoxicity. MRI results showed that nanoparticles can be retained in both the stratum submucosum and epithelial cells of the colon for almost 80 min. Transmission electron microscopy images further revealed that Gd@chitosan nanoparticles were localized inside the mucosal cells or intercellular space, while tissue from Gd-DTPA aqueous solution administration showed nothing. Due to the infusion of Gd@chitosan nanoparticles, the MR signal intensity of colon mucosa increased from about 6% to 35%, and the contrast enhancement was highest at 20 min after administration. CONCLUSION: Gd@chitosan nanoparticles with high Gd-DTPA content were successfully prepared for use as a novel MRI contrast agent. All results indicated that rectally administered Gd@chitosan nanoparticles have the potential for MRI diagnosis of colon mucosal disease.

Pulmonary embolism detection and characterization through quantitative iodine-based material decomposition images with spectral computed tomography imaging.

OBJECTIVES: To assess the diagnostic value of pulmonary embolism (PE) detection and characterization through quantitative iodine-based material decomposition images with spectral computed tomography (CT) imaging. MATERIALS AND METHODS: Fifty-three patients underwent CT pulmonary angiography (CTPA) with spectral imaging mode with the simultaneous acquisition of 80 kVp and 140 kVp on a GE Discovery CT750HD scanner to generate monochromatic CTPA and material decomposition images. CTPA images were reviewed for the presence, localization, and degree (occlusive or nonocclusive) of PE. The iodine distribution in the lung parenchyma on the iodine-based material decomposition images was used to identify perfusion defects, which were then correlated to the CTPA findings. The iodine densities for the perfusion defects and the normal lung parenchyma were measured and statistically compared. Twelve PE patients underwent anticoagulation, and the iodine densities for the perfusion defects before and after the treatment were also measured and compared. The receiver operating characteristics curve was generated to assess the differential diagnostic performances of iodine density in distinguishing the presence or absence of PE and the occlusive or nonocclusive PE. RESULTS: A total of 93 clots (51 occlusive and 42 nonocclusive) were found in 19 patients with lobar (26), segmental (54), or subsegmental (13) distribution. CTPA identified 88 clots initially and 5 more retrospectively with the help of iodine mapping. Thirty-three of 34 normal CTPA patients had symmetric iodine distribution. All occlusive clots and 11 nonocclusive clots showed clear evidence of iodine distribution defects. There was a significant difference for the iodine density among normal lung parenchyma (1.89 mg/mL [0.85-3.29 mg/mL]), nonocclusive perfusion defects (0.83 mg/mL [0.44-1.26 mg/mL]), and occlusive perfusion defects (0.27 mg/mL [0.00-0.62 mg/mL]) (P < 0.001). The iodine densities of perfusion defects before and after anticoagulation were significantly different (P < 0.001). Receiver operating characteristics analyses showed high discriminatory power for using the quantification of iodine density in distinguishing the presence or absence of PE and the occlusive or nonocclusive PE. CONCLUSIONS: Spectral CT imaging generated both monochromatic CTPA images for morphologic analysis of PE and material decomposition images for quantitative depiction of pulmonary blood flow and perfusion defects. Quantification of iodine density may be used as a predictor in distinguishing the presence or absence of PE and the severity of PE.