Impact of preset and postset adaptive statistical iterative reconstruction-V on image quality in nonenhanced abdominal-pelvic CT on wide-detector revolution CT.

BACKGROUND: Adaptive statistical iterative reconstruction-V technique (ASIR-V) is usually set at different strengths according to the different clinical requirements and scenarios encountered when setting scanning protocols, such as setting a more aggressive tube current reduction (defined as preset ASIR-V). Reconstruction with ASIR-V is useful after scanning using image algorithms to improve image quality (defined as postset ASIR-V). The aim of this study was to investigate the quality of images reconstructed with preset and postset ASIR-V, using the same noncontrast abdominal-pelvic computed tomography (CT) protocols in the same individual on a wide detector CT. METHODS: We prospectively enrolled 141 patients. The scan protocols in Groups A-E were 0%, 20%, 40%, 60%, and 80% preset ASIR-V, respectively, in the 256 wide-detector row Revolution CT (GE Healthcare, Waukesha, WI, USA). Each group was further divided into 5 subgroups with 0%, 20%, 40%, 60%, and 80% postset ASIR-V, respectively. The 64-detector Discovery 750 HDCT (GE, USA) was used for Group F as a control group, using 0%, 20%, 40%, 60%, and 80% ASIR, respectively. Image noise was measured in the spleen, aorta, and muscle. The CT attenuation and image noise were analyzed using the paired t-test; analysis of variance and post hoc multiple comparisons were made using the Student-Newman-Keuls (SNK) method. RESULTS: The CT attenuation in Groups A-F exhibited no significant difference between subgroups in three organs (P>0.05). Only with increasing preset ASIR-V% (Groups A to E), did the image noise decrease, except in Group B in the aorta and muscle (NoiseB > NoiseA, PmuscleA&B=0.233, PaortaA&B=0.796). Only with increasing postset ASIR-V or ASIR% (Groups A and F), did the image noise decrease in the three organs. After preset and postset ASIR-V were combined, with preset ASIR-V% being equal to postset ASIR-V%, the image become similar to the corresponding preset ASIR-V part with the line of postset ASIR-V 0% (baseline of each group). When preset ASIR-V% was greater than the postset ASIR-V%, the image noise was higher than the baseline of each group. When preset ASIR-V% was less than the postset ASIR-V%, the image noise was lower than the baseline of each group. The radiation dose from B to E decreased from 11.2% to 57.1%. The CT dose index volume (CTDIvol) and dose length product (DLP) in Group F were significantly higher than those in Group A. CONCLUSIONS: Using both preset and postset ASIR-V allows dose reduction, with a potential to improve image quality only when postset ASIR-V% is higher than or equal to preset ASIR-V%. The image quality depends on postset ASIR-V%, whereas the decrease of radiation dose depends on preset ASIR-V%.

Submucosal Enhancing Stripe as a Contrast Material-enhanced MRI-based Imaging Feature for the Differentiation of Stage T0-T1 from Early T2 Rectal Cancers.

Background Accurate differentiation of stage T0-T1 rectal tumors from stage T2 rectal tumors facilitates the selection of appropriate surgical treatment. MRI is a recommended technique for local staging, but its ability to distinguish T1 from T2 tumors is poor. Purpose To explore the value of a submucosal enhancing stripe (SES), an uninterrupted enhancing band between the rectal tumor and the muscular layer on contrast material-enhanced T1-weighted images, as a potential imaging feature to differentiate T0-T1 from T2 rectal tumors. Materials and Methods This retrospective study included patients with pT0-T1 and pT2 rectal tumors who underwent pretreatment MRI and rectal tumor resection between January 2012 and November 2019. Two radiologists independently evaluated tumor characteristics (SES; status of muscularis propria [SMP]; and tumor shape, location, and size) at MRI. The associations of clinical and imaging characteristics with stage T0-T1 or T2 tumors were assessed, ß values were calculated, and predictive models were built. The diagnostic accuracies for the differentiation of T0-T1 tumors from T2 tumors with SES and SMP were compared. Results Data from 431 patients (mean age, 60 years ± 10 [standard deviation]; 261 men) were evaluated. SES (ß = 3.9; 95% CI: 3.1, 4.7; P < .001), SMP (ß = 1.3; 95% CI: 0.7, 1.9; P < .001), and carpetlike shape (ß = 1.6; 95% CI: 0.5, 2.8; P = .01) were independent factors distinguishing T0-T1 tumors from T2 tumors. The diagnostic accuracy was 87% (95% CI: 84, 90; 376 of 431) for SES and 67% (95% CI: 63, 72; 290 of 431) for SMP (P < .001). Conclusion Submucosal enhancing stripe (SES) at contrasted-enhanced MRI, status of muscularis propria (SMP) on T2-weighted images, and tumor shape can serve as independent imaging features to differentiate stage T0-T1 rectal tumors from stage T2 rectal tumors. Moreover, SES is a more accurate feature than is SMP. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

An antioxidant self-healing hydrogel for 3D cell cultures.

In this paper, an antioxidant self-healing hydrogel has been prepared. The Biginelli reaction was used to prepare a monomer containing phenylboronic acid (PBA) and 3,4-dihydropyrimidin-2(1H)-one (DHPM) groups. This PBA-DHPM monomer was copolymerized with poly(ethylene glycol methyl ether) methacrylate (PEGMA) to produce a water-soluble copolymer via radical polymerization. The resulting copolymer quickly crosslinked poly(vinyl alcohol) (PVA) through borate ester bonds to generate a self-healing hydrogel under mild conditions (pH ∼ 7.4, 25 °C). The prepared hydrogel showed an inherent antioxidant ability because of the DHPM moieties in the hydrogel structure. It also showed no cytotoxicity, and in an in vivo mouse model the hydrogel injected under the skin of a mouse hardly caused any adverse reactions, suggesting that this hydrogel could be used as an implantable biomaterial. This first report of an antioxidant self-healing hydrogel demonstrates a new application of the Biginelli reaction in materials science, which might prompt a broad study of multicomponent reactions in interdisciplinary fields.

The Predictive Value of Pre-/Postneoadjuvant Chemoradiotherapy MRI Characteristics for Patient Outcomes in Locally Advanced Rectal Cancer.

RATIONALE AND OBJECTIVES: This study aimed to investigate the predictive value of pre-/postneoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) characteristics for the long-term survival outcomes in patients with locally advanced rectal cancer (LARC). MATERIALS AND METHODS: We retrospectively evaluated pre- and post-nCRT MRI and clinicopathologic characteristics of LARC patients. The 3-year disease-free survival (DFS) was estimated using the Kaplan-Meier product-limit method. Associations between MRI variabilities and survival outcomes were assessed using Cox proportional hazards model. RESULTS: In total, 171 LARC patients (112 men and 59 women) with a median age of 55 years (range, 27-82 years) treated with nCRT were evaluated. The median follow-up was 47.6 months, and the 3-, 4-, and 5-year DFS in the overall cohort was 76.6%, 74.5%, and 73.7%, respectively. MRI assessment of extramural venous invasion (mrEMVI) positivity was a significant independent adverse factor of long-term survival (hazard ratio [HR] = 2.589, 95% confidence interval [CI] = 1.398-4.794, p = 0.002) on multivariate analysis. Patients with positive mrEMVI had significantly lower 3-year DFS than those with negative mrEMVI (52.6 months vs 65.1 months; p = 0.003). Moreover, the tumor regression grade on MRI (mrTRG) also significantly correlated with survival outcomes in patients with LARC. Patients with partial response on post-nCRT MRI (mrPR) showed short DFS than those with complete response (mrCR; HR = 4.914, 95% CI = 1.176-20.533, p = 0.029). The 3-year DFS of mrCR and mrPR patients were 74.3 months and 58.9 months, respectively (p = 0.011). CONCLUSION: The pre-/post-nCRT MRI characteristics may be used to long-term survival stratification in LARC patients. mrEMVI positivity was an independent adverse prognostic indicator for 3-year DFS. Further, mrTRG may also be a predictive factor for the prognosis of LARC patients. The pre-/post-nCRT MR imaging may offer more information for providing individualized treatment.

Imaging Characteristics of USPIO Nanoparticles (<5 nm) as MR Contrast Agent In Vitro and in the Liver of Rats.

Iron nanoparticles have an increasingly more and more important role in MR molecular imaging due to their novel magnetic and surface chemical properties. They provide new possibilities for noninvasive diagnosis and treatment monitoring, especially for tissues that are rich in macrophages. The smaller size and prolongation of the plasma half-life change the in vivo fate of ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles captured by liver in reticuloendothelial system (RES) or mononuclear phagocytic system (MPS). However, there is still a lack of MR imaging studies on the liver assessing USPIO nanoparticles <5 nm in size to reflect its absorption and clearance properties. In this study, we used MRI to study the in vitro phantom and in vivo rat liver imaging characteristics of USPIO nanoparticles (<5 nm). The results showed that USPIO nanoparticles (<5 nm) could potentially reduce longitudinal and transverse relaxation times and showed similar T 1 relaxation rates compared with commercial gadolinium chelates. In addition, USPIO nanoparticles (<5 nm) in vivo demonstrated both positive (T 1) and negative (T 2) liver contrast enhancement in healthy rats' liver. Furthermore, USPIO nanoparticles showed relatively good in vitro biocompatibility and fast clearance (within 45.17 minutes after intravenous injection) in the normal liver. Taken together, these data might inspire a new personalized and precise diagnostic tool and stimulate new applications for specific targeted molecular probes.

Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma.

OBJECTIVE: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC). METHODS: Breath-hold diffusion weighted imaging (DWI) was performed in 64 patients (33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging (MRI) and follow-up computed tomography (CT) or MRI. The ADC values (ADC10, ADC30, ADCmedian and ADCmax) were obtained from the histogram's 10th, 30th, 50th and 100th percentiles. The ratios of ADC10, ADC30, ADCmedian and ADCmax to the mean non-lesion area-ADC (RADC10, RADC30, RADCmedian, and RADCmax) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test. RESULTS: The ADC30, ADCmedian, ADCmax, RADC30, RADCmedian, and RADCmax were significantly larger in the progressive group than in the stable group (P<0.05). The median progression-free survival (PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months, respectively. Univariate analysis indicated that RADC10, RADC30, and RADCmedian were significantly correlated with the PFS [hazard ratio (HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADCmedian was the only independent predictor of tumor progression (P=0.04). And the cutoff value of RADCmedian was 0.71. CONCLUSIONS: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.

A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD.

PURPOSE: Computer-aided diagnosis (CAD) can aid in improving diagnostic level; however, the main problem currently faced by CAD is that it cannot obtain sufficient labeled samples. To solve this problem, in this study, we adopt a generative adversarial network (GAN) approach and design a semisupervised learning algorithm, named G2C-CAD. METHODS: From the National Cancer Institute (NCI) Lung Image Database Consortium (LIDC) dataset, we extracted four types of pulmonary nodule sign images closely related to lung cancer: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, obtaining a total of 3,196 samples. In addition, we randomly selected 2,000 non-lesion image blocks as negative samples. We split the data 90% for training and 10% for testing. We designed a DCGAN generative adversarial framework and trained it on the small sample set. We also trained our designed CNN-based fuzzy Co-forest on the labeled small sample set and obtained a preliminary classifier. Then, coupled with the simulated unlabeled samples generated by the trained DCGAN, we conducted iterative semisupervised learning, which continually improved the classification performance of the fuzzy Co-forest until the termination condition was reached. Finally, we tested the fuzzy Co-forest and compared its performance with that of a C4.5 random decision forest and the G2C-CAD system without the fuzzy scheme, using ROC and confusion matrix for evaluation. RESULTS: Four different types of lung cancer-related signs were used in the classification experiment: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, along with negative image samples. For these five classes, the G2C-CAD system obtained AUCs of 0.946, 0.912, 0.908, 0.887, and 0.939, respectively. The average accuracy of G2C-CAD exceeded that of the C4.5 random decision tree by 14%. G2C-CAD also obtained promising test results on the LISS signs dataset; its AUCs for GGO, lobulation, spiculation, pleural indentation, and negative image samples were 0.972, 0.964, 0.941, 0.967, and 0.953, respectively. CONCLUSION: The experimental results show that G2C-CAD is an appropriate method for addressing the problem of insufficient labeled samples in the medical image analysis field. Moreover, our system can be used to establish a training sample library for CAD classification diagnosis, which is important for future medical image analysis.

Comparison of ultrasound and digital mammography plus tomosynthesis in determining benign and malignant breast lesions using pathology as a gold standard, in 102 Chinese women.

OBJECTIVE: This study was to evaluate performance characteristics of ultrasonography (US) and a combined two-and three-dimensional (2D+3D) digital mammography in identifying breast tumors in Chinese women. SUBJECTS AND METHODS: One hundred and two women with suspected breast tumors were examined using diagnostic imaging techniques of US and a combined 2D+3D imaging protocol. Detection of breast tumors in women with and without dense breasts was validated according to the features of image-detected breast tumors which were proven by histological exam in this study cohort. RESULTS: Breast US was superior to 2D+3D imaging in assessing benign lesions (P<0.01). The diagnostic measure on 2D+3D mammography was more accurate than the US exam in breast cancer detection. Furthermore, 2D+3D imaging was more sensitive than US in identifying malignant lesions in size of ≤1cm and in relatively high breast density (P<0.01 or 0.05). Breast US showed a better correlation with the sizes of benign tumor as compared to 2D+3D imaging with correlation coefficients of 0.930 and 0.920. Conversely, 2D+3D imaging showed a better correlation with the sizes of malignant tumors as compared to US with correlation coefficients of 0.951 and 0.815. Additionally, presence of microcalcifications on mammography significantly increased in breast cancers as compared to benign tumors (P<0.001). CONCLUSION: Breast US and 2D+3D mammography imaging play an additive role in identifying breast tumors. Intervention of the 2D+3D imaging technique helps recognize appearance and characteristics of breast lesions particularly in the women with a lesion measure of ≤1cm and those with dense breasts or breast microcalcifications.

Value of 3.0T magnetic resonance imaging in the diagnosis of retroperitoneal tumors.

BACKGROUND: To evaluate the diagnostic value of 3.0T MR for differentiating benign from malignant primary retroperitoneal tumors (RPTs). METHODS: A total of 81 patients (44 males and 37 females; 31 benign and 50 malignant lesions) who underwent surgical resection for RPT were evaluated retrospectively. The MR features included lesion location, number, size, margin, surfaces, texture (solid or non-solid), MRhyperintense and MRhypointense signal intensity, apparent diffusion coefficient (ADC) value and the presence of fat, necrosis and hemorrhage. Categorical variables were tested with a χ2 test or Fisher's exact test for the diagnostic indices and the sensitivity and specificity of MR characteristics. RESULTS: Using six indices (ill-defined margins, irregular surface, major diameter >5.85 cm, minor diameter >5.35 cm, solid texture and ADC <1.2×10-3 mm2/s) to diagnose malignant RPT, sensitivity and specificity were 36.0% vs. 93.5%, 68.0% vs. 58.1%, 80.0% vs. 64.5%, 64.0% vs. 90.3%, 65.0% vs. 63.5%, and 64.0% vs. 74.2%, respectively. Combining all those radiological features into a comprehensive evaluation, sensitivity and specificity were 82.0% and 77.4%, respectively (χ2=27.984, P<0.001) when scores ≥4. Other findings had no statistical significance. CONCLUSIONS: More accurate differential diagnosis of primary RPTs could be made through comprehensive analysis of combined diagnostic indices.

MRI morphologic and clinicopathologic characteristics for predicting outcomes in patients with locally advanced rectal cancer.

PURPOSE: The aim of this study was to investigate the value of MRI morphologic and clinicopathologic factors for predicting 3-year disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC). METHOD: In this retrospective study, pre- and post-neoadjuvant chemoradiotherapy (nCRT) MRI morphologic (e.g., pre-nCRT MRI-detected extramural venous invasion) and clinicopathologic variabilities (e.g., pathological complete response) were evaluated in all patients. Three-year DFS was estimated using Kaplan-Meier product-limit method, and Cox proportional hazards models were used to determine associations between morphologic or clinicopathologic variabilities and survival outcomes. RESULTS: A total of 115 patients (39 females and 76 males; median age, 54 years; age range, 28-82 years) with LARC treated with nCRT were enrolled. With a median follow-up of 48.0 months, the 3-year DFS was 79.0% for all patients. During follow-up, 18 patients died, 28 patients experienced relapse (26 distant, one local, and one both), and 69 patients were censored. MRI-detected extramural venous invasion (mrEMVI) was the only significantly independent factor of long-term survival, while HR was 2.308 (95% CI 1.151-4.629, P = 0.018) on univariate and 2.495 (95% CI 1.243-5.012, P = 0.010) on multivariate analysis. The 3-year cumulative survival rate in patients with mrEMVI negativity compared with positivity were 86.6% versus 65.0% (P = 0.015), respectively. CONCLUSION: In conclusion, pre-nCRT mrEMVI status was the independent significant risk factor for long-term outcomes in LARC patients treated with nCRT, while the other morphologic and clinicopathologic characteristics were not related to the patient survival.

Investigating the correlation of arterial spin labeling and dynamic contrast enhanced perfusion in primary tumor of nasopharyngeal carcinoma.

PURPOSE: This prospective study aimed to investigate the correlation between two perfusion methods: arterial spin labeling (ASL) and dynamic contrast enhanced (DCE) technique in patients with nasopharyngeal carcinoma (NPC) and to optimize ASL protocol. MATERIALS AND METHODS: Forty-five newly diagnosed NPC patients underwent MR examinations with both 3D pseudo-continuous ASL (pCASL) and DCE-MRI sequences. Tumor blood flow (TBF) derived in pCASL with three post-labeling delay (PLD) times (i.e. 1.0 s, 1.5 s, and 2.0 s) and DCE derived parameters including MaxSlop, contrast enhancement ratio (CER), Initial area under the gadolinium curve (IAUGC), Ktrans, Kep and Ve were measured by two independent observers, and their correlation coefficients were investigated using Spearman test. RESULTS: Inter-observer reproducibility (ICC = 0.931-0.998) was observed to be excellent. Positive correlations between mean, maximum and minimum value of TBFs with different PLDs and DCE-MRI parameters (except Ve) were respectively observed (r = 0.308-0.688, P = 0.000-0.040). CONCLUSION: pCASL may be an alternative method for DCE-MRI in assessing the perfusion level in NPC in the future.

Therapy Effects of Advanced Hypopharyngeal and Laryngeal Squamous Cell Carcinoma: Evaluated using Dual-Energy CT Quantitative Parameters.

The accurate evaluation of the therapeutic effects of advanced laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) remains challenging. In this study, we determined the value of quantitative parameters derived from dual-energy computed tomography (DECT) for predicting the therapeutic effects of advanced LHSCC and to provide valuable evidence for early judgement of the tumour's response to therapy in clinical practice. We prospectively analysed 41 patients with pathologically confirmed LHSCC. All patients received a DECT scan before therapy. Nineteen of 41 patients showed complete remission (CR), and 22 showed non-complete remission (NCR). The mean of the slope of spectral Hounsfield unit curve (λHU), standardized iodine concentration and effective atomic number in the CR group were significantly lower than the NCR group (P < 0.05). There were no significant differences for T stage, treatment modality and standardized water concentration between two groups (P > 0.05). The best predictor of CR effect was λHU. The 2-year cumulative recurrence rate of patients with higher λHU values was significantly higher than that of patients with lower λHU values (P < 0.05), while the 2-year survival rate of those patients was not significantly different (P > 0.05). DECT could easily identify CR patients and potentially help to choose the appropriate treatment regimen for advanced LHSCC.

MRI texture analysis in predicting treatment response to neoadjuvant chemoradiotherapy in rectal cancer.

To evaluate the importance of MRI texture analysis in prediction and early assessment of treatment response before and early neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). This retrospective study comprised of 59 patients. The tumoral texture parameters were compared between pre- and early nCRT. Area Under receiver operating characteristic (ROC) Curves [AUCs] were used to compare the diagnostic performance of statistically significant difference parameters and logistic regression analysis predicted probabilities for discriminating responders and nonresponders. The Standard Deviation (SD), kurtosis and uniformity were statistically significantly difference between pre- and early nCRT (p = 0.0012, 0.0001, and < 0.0001, respectively). In pathological complete response (pCR) group, pre-uniformity and pre-Energy were significantly higher than that of nonresponders (p = 0.03 and p < 0.01, respectively), while the pre-entropy in nonresponder was reverse (p = 0.01). The diagnostic performance of pre-kurtosis and pre-Energy were higher in tumor regression grade (TRG) and pCR group (AUC = 0.67, 0.73, respectively). Logistic regression analysis showed that diagnostic performance for prediction responder and nonresponder did not significantly improve compared with to pre-uniformity, energy and entropy in pCR group (AUC = 0.76, p = 0.2794, 0.4222 and 0.3512, respectively). Texture parameters as imaging biomarkers have the potential to prediction and early assessment of tumoral treatment response to neoadjuvant chemoradiotherapy in patients with LARC.

Novel radiomic signature as a prognostic biomarker for locally advanced rectal cancer.

BACKGROUND: Locally advanced rectal cancer (LARC) patient stratification by clinicoradiologic factors may yield variable results. Therefore, more efficient prognostic biomarkers are needed for improved risk stratification of LARC patients, personalized treatment, and prognostication. PURPOSE/HYPOTHESIS: To compare the ability of a radiomic signature to predict disease-free survival (DFS) with that of a clinicoradiologic risk model in individual patients with LARC. STUDY TYPE: Retrospective study. POPULATION: In all, 108 consecutive patients (allocated to a training and validation set with a 1:1 ratio) with LARC treated with neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision (TME). FIELD STRENGTH/SEQUENCE: Axial 3D LAVA multienhanced MR sequence at 3T. ASSESSMENT: ITK-SNAP software was used for manual segmentation of 3D pre-nCRT MR images. All manual tumor segmentations were performed by a gastrointestinal tract radiologist, and validated by a senior radiologist. The clinicoradiologic risk factors with potential prognostic outcomes were identified in univariate analysis based on the Cox regression model for the whole set. The results showed that ypT, ypN, EMVI, and MRF were potential clinicoradiologic risk factors. Interestingly, only ypN and MRF were identified as independent predictors in multivariate analysis based on the Cox regression model. STATISTICAL TESTS: A radiomic signature based on 485 3D features was generated using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The association of the radiomic signature with DFS was investigated by Kaplan-Meier survival curves. Survival curves were compared by the log-rank test. Three models were built and assessed for their predictive values, using the Harrell concordance index and integrated time-dependent area under the curve. RESULTS: The novel radiomic signature stratified patients into low- and high-risk groups for DFS in the training set (hazard ratio [HR] = 6.83; P < 0.001), and was successfully validated in the validation set (HR = 2.92; P < 0.001). The model combining the radiomic signature and clinicoradiologic findings had the best performance (C index = 0.788, 95% confidence interval [CI] 0.72-0.86; integrated time-dependent area under the curve of 0.837 at 3 years). DATA CONCLUSION: The novel radiomic signature could be used to predict DFS in patients with LARC. Furthermore, combining this radiomic signature with clinicoradiologic features significantly improved the ability to estimate DFS (P = 0.001, 0.005 in training set and in validation set, respectively), and may help guide individualized treatment in such patients. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018.

Vertebral fractures among breast cancer survivors in China: a cross-sectional study of prevalence and health services gaps.

BACKGROUND: Breast cancer survivors are at high risk for fracture due to cancer treatment-induced bone loss, however, data is scarce regarding the scope of this problem from an epidemiologic and health services perspective among Chinese women with breast cancer. METHODS: We designed a cross-sectional study comparing prevalence of vertebral fractures among age- and BMI-matched women from two cohorts. Women in the Breast Cancer Survivors cohort were enrolled from a large cancer hospital in Beijing. Eligibility criteria included age 50-70 years, initiation of treatment for breast cancer at least 5 years prior to enrollment, and no history of metabolic bone disease or bone metastases. Data collected included sociodemographic characteristics; fracture-related risk factors, screening and preventive measures; breast cancer history; and thoracolumbar x-ray. The matched comparator group was selected from participants enrolled in the Peking Vertebral Fracture Study, an independent cohort of healthy community-dwelling postmenopausal women from Beijing. RESULTS: Two hundred breast cancer survivors were enrolled (mean age 57.5 ± 4.9 years), and compared with 200 matched healthy women. Twenty-two (11%) vertebral fractures were identified among breast cancer survivors compared with 7 (3.5%) vertebral fractures in the comparison group, yielding an adjusted odds ratio for vertebral fracture of 4.16 (95%CI 1.69-10.21, p < 0.01). The majority had early stage (85.3%) and estrogen and/or progesterone receptor positive (84.6%) breast cancer. Approximately half of breast cancer survivors reported taking calcium supplements, 6.1% reported taking vitamin D supplements, and only 27% reported having a bone density scan since being diagnosed with breast cancer. CONCLUSIONS: Despite a four-fold increased odds of prevalent vertebral fracture among Chinese breast cancer survivors in our study, rates of screening for osteoporosis and fracture risk were low reflecting a lack of standardization of care regarding cancer-treatment induced bone loss.

Mortality outcomes of low-dose computed tomography screening for lung cancer in urban China: a decision analysis and implications for practice.

BACKGROUND: Mortality outcomes in trials of low-dose computed tomography (CT) screening for lung cancer are inconsistent. This study aimed to evaluate whether CT screening in urban areas of China could reduce lung cancer mortality and to investigate the factors that associate with the screening effect. METHODS: A decision tree model with three scenarios (low-dose CT screening, chest X-ray screening, and no screening) was developed to compare screening results in a simulated Chinese urban cohort (100,000 smokers aged 45-80 years). Data of participant characteristics were obtained from national registries and epidemiological surveys for estimating lung cancer prevalence. The selection of other tree variables such as sensitivities and specificities of low-dose CT and chest X-ray screening were based on literature research. Differences in lung cancer mortality (primary outcome), false diagnoses, and deaths due to false diagnosis were calculated. Sensitivity analyses were performed to identify the factors that associate with the screening results and to ascertain worst and optimal screening effects considering possible ranges of the variables. RESULTS: Among the 100,000 subjects, there were 448, 541, and 591 lung cancer deaths in the low-dose CT, chest X-ray, and no screening scenarios, respectively (17.2% reduction in low-dose CT screening over chest X-ray screening and 24.2% over no screening). The costs of the two screening scenarios were 9387 and 2497 false diagnoses and 7 and 2 deaths due to false diagnosis among the 100,000 persons, respectively. The factors that most influenced death reduction with low-dose CT screening over no screening were lung cancer prevalence in the screened cohort, low-dose CT sensitivity, and proportion of early-stage cancers among low-dose CT detected lung cancers. Considering all possibilities, reduction in deaths (relative numbers) with low-dose CT screening in the worst and optimal cases were 16 (5.4%) and 288 (40.2%) over no screening, respectively. CONCLUSIONS: In terms of mortality outcomes, our findings favor conducting low-dose CT screening in urban China. However, approaches to reducing false diagnoses and optimizing important screening conditions such as enrollment criteria for screening are highly needed.

Diagnostic value of single-source dual-energy spectral computed tomography for papillary thyroid microcarcinomas.

BACKGROUND: Ultrasound (US) and computed tomography (CT) are common diagnostic imaging methods for detecting and diagnosing papillary thyroid microcarcinoma (PTMC). However, single-source dual-energy spectral computed tomography (spectral CT) reduces beam hardening artefacts and optimizes contrast, which may add value in detecting PTMC. OBJECTIVE: To investigate values of applying single-source dual-energy spectral CT for diagnosing PTMCs, in comparison with high frequency ultrasound and conventional polychromatic images. METHODS: Thirty-one patients with suspected PTMC underwent contrast-enhanced dual-energy spectral CT. The images were analyzed by two experienced radiologists. Noise and contrast-noise-ratio (CNR) were compared between conventional CT and spectral CT. Ultrasonography was also performed by an experienced radiologist with a 7 to 12-MHz linear array transducer. Detection and diagnostic sensitivity were determined and compared. RESULTS: Forty-six pathologically-confirmed PTMC lesions were detected in 31 patients. Spectral CT had lower noise and higher CNR than conventional CT (P < 0.05). US detected more tumors (45/46 [97.8%] than conventional CT images (40/46 [87.0%]) or spectral CT images (44/46 [95.7%]). Among them, 30 (65.2%), 36 (78.3%), and 40 (87.0%) lesions were diagnosed correctly by conventional CT, spectral CT and US, respectively. Spectral CT had higher sensitivity than conventional CT (P = 0.031). However, there was no significant difference between spectral CT and US diagnostic sensitivities (P = 0.125). CONCLUSION: Single-source dual-energy spectral CT was superior to conventional polychromatic images and similar to high frequency ultrasound in detecting and diagnosing for PTMCs. CT had advantages in detecting level VI and VII lymph nodes. Spectral CT and US provided good results for PTMC, and aid preoperative diagnosis.

Empirical Driven Automatic Detection of Lobulation Imaging Signs in Lung CT.

Computer-aided detection (CAD) of lobulation can help radiologists to diagnose/detect lung diseases easily and accurately. Compared to CAD of nodule and other lung lesions, CAD of lobulation remained an unexplored problem due to very complex and varying nature of lobulation. Thus, many state-of-the-art methods could not detect successfully. Hence, we revisited classical methods with the capability of extracting undulated characteristics and designed a sliding window based framework for lobulation detection in this paper. Under the designed framework, we investigated three categories of lobulation classification algorithms: template matching, feature based classifier, and bending energy. The resultant detection algorithms were evaluated through experiments on LISS database. The experimental results show that the algorithm based on combination of global context feature and BOF encoding has best overall performance, resulting in F1 score of 0.1009. Furthermore, bending energy method is shown to be appropriate for reducing false positives. We performed bending energy method following the LIOP-LBP mixture feature, the average positive detection per image was reduced from 30 to 22, and F1 score increased to 0.0643 from 0.0599. To the best of our knowledge this is the first kind of work for direct lobulation detection and first application of bending energy to any kind of lobulation work.

Chemical shift effect predicting lymph node status in rectal cancer using high-resolution MR imaging with node-for-node matched histopathological validation.

OBJECTIVES: To evaluate the value of the chemical shift effect (CSE) as well as other criteria for the prediction of lymph node status. MATERIALS AND METHODS: Twenty-nine patients who underwent radical surgery of rectal cancers were studied with pre- and postoperative specimen MRI. Lymph nodes were harvested from transverse whole-mount specimens and compared with in vivo and ex vivo images to obtain a precise slice-for-section match. Preoperative MR characteristics including CSE, as well as other predictors, were evaluated by two readers independently between benign and metastatic nodes. RESULTS: A total of 255 benign and 35 metastatic nodes were obtained; 71.4% and 69.4% of benign nodes were detected with regular CSE for two readers, whereas 80.0% and 74.3% of metastatic nodes with absence of CSE. The CSE rendered areas under the ROC curve (AUC) of 0.879 and 0.845 for predicting nodal status for two readers. The criteria of nodal location, border, signal intensity and minimum distance to the rectal wall were also useful but with AUCs (0.629-0.743) lower than those of CSE. CONCLUSIONS: CSE is a reliable predictor for differentiating benign from metastatic nodes. Additional criteria should be taken into account when it is difficult to determine the nodal status by using only a single predictor. KEY POINTS: • CSE is good for predicting nodal status with high confidence. • Nodal border and signal intensity are useful for assessing nodal status. • Location of mesorectal nodes could facilitate the prediction of nodal status. • Primary tumour stage could be used as reference for nodal staging.

A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency.