Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer.

BACKGROUND: The use of peritumoral features to determine the survival time of patients with rectal cancer (RC) is still imprecise. PURPOSE: To explore the correlation between intratumoral, peritumoral and combined features, and overall survival (OS). STUDY TYPE: Retrospective. POPULATION: One hundred sixty-six RC patients (53 women, 113 men; average age: 55 ± 12 years) who underwent radical resection after neoadjuvant therapy. FIELD STRENGTH/SEQUENCE: 3 T; T2WI sagittal, T1WI axial, T2WI axial with fat suppression, and high-resolution T2WI axial sequences, enhanced T1WI axial and sagittal sequences with fat suppression. ASSESSMENT: Radiologist A segmented 166 patients, and radiologist B randomly segmented 30 patients. Intratumoral and peritumoral features were extracted, and features with good stability (ICC ≥0.75) were retained through intra-observer analysis. Seven classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), Extremely randomized trees (ET), eXtreme Gradient Boosting (XGBoost), and LightGBM (LGBM), were applied to select the classifier with the best performance. Next, the Rad-score of best classifier and the clinical features were selected to establish the models, thus, nomogram was built to identify the association with 1-, 3-, and 5-year OS. STATISTICAL TESTS: LASSO, regression analysis, ROC, DeLong method, Kaplan-Meier curve. P < 0.05 indicated a significant difference. RESULTS: Only Node (irregular tumor nodules in the surrounding mesentery) and ExtraMRF (lymph nodes outside the perirectal mesentery) were significantly different in 20 clinical features. Twelve intratumoral, 3 peritumoral, and 14 combined features related to OS were selected. LR, SVM, and RF classier showed the best efficacy in the intratumoral, peritumoral, and combined model, respectively. The combined model (AUC = 0.954 and 0.821) had better survival association than the intratumoral model (AUC = 0.833 and 0.813) and the peritumoral model (AUC = 0.824 and 0.687). DATA CONCLUSION: The proposed peritumoral model with radiomics features may serve as a tool to improve estimated survival time. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Drug resistance­related gene targets and molecular mechanisms in the A2780/Taxol­resistant epithelial ovarian cancer cell line.

Epithelial ovarian cancer (EOC) is a fatal gynecological malignant tumor with a low 5-year survival rate. The use of the first-line chemotherapeutic drug, paclitaxel, for the treatment of EOC is associated with resistance, often leading to treatment failure. The present study investigated the gene targets in an A2780 paclitaxel-resistant EOC cell line (A2780/Taxol), and the potential underlying mechanisms using transcriptome sequencing technology and bioinformatics analysis. The transcriptome of the A2780/Taxol cell line was sequenced, and 498 differentially expressed genes were obtained contained in the Gene Expression Omnibus dataset. Further bioinformatics analysis revealed that matrix metalloproteinase 1 (MMP1), zyxin (ZYX) and Unc-5 netrin receptor C (UNC5C) may be gene targets related to paclitaxel resistance. Moreover, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that a potential mechanism associated with paclitaxel resistance was related to cell migration. Furthermore, the expression levels of MMP1, ZYX and UNC5C were verified using western blotting, immunofluorescence and immunohistochemistry in vitro. The results revealed that the expression levels of MMP1 and ZYX were significantly increased in A2780/Taxol cells, while UNC5C expression was significantly decreased, which was consistent with the results of the transcriptome sequencing. The present study demonstrated that MMP1, ZYX and UNC5C may be the gene targets associated with paclitaxel resistance in EOC. These genes have potential to be used as molecular markers for EOC drug therapy, targeted elimination of drug resistance, and evaluation of treatment efficacy and patient prognosis.

Preoperative prediction of perineural invasion and lymphovascular invasion with CT radiomics in gastric cancer.

Objectives: To determine whether contrast-enhanced CT radiomics features can preoperatively predict lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancer (GC). Methods: A total of 148 patients were included in the LVI group, and 143 patients were included in the PNI group. Three predictive models were constructed, including clinical, radiomics, and combined models. A nomogram was developed with clinical risk factors to predict LVI and PNI status. The predictive performance of the three models was mainly evaluated using the mean area under the curve (AUC). The performance of three predictive models was assessed concerning calibration and clinical usefulness. Results: In the LVI group, the predictive power of the combined model (AUC=0.871, 0.822) outperformed the clinical model (AUC=0.792, 0.728) and the radiomics model (AUC=0.792, 0.728) in both the training and testing cohorts. In the PNI group, the combined model (AUC=0.834, 0.828) also had better predictive power than the clinical model (AUC=0.764, 0.632) and the radiomics model (AUC=0.764, 0.632) in both the training and testing cohorts. The combined models also showed good calibration and clinical usefulness for LVI and PNI prediction. Conclusion: CECT-based radiomics analysis might serve as a non-invasive method to predict LVI and PNI status in GC.

Comparison of selected photon shield and organ-based tube current modulation for radiation dose reduction in head computed tomography: A phantom study.

OBJECTIVE: The aim of this study is to investigate the radiation dose and image quality of head CT using SPS and OBTCM techniques. METHODS: Three anthropomorphic head phantoms (1-yr-old, 5-yr-old, and adult) were used. Images were acquired using four modes (Default protocol, OBTCM, SPS, and SPS+OBTCM). Absorbed dose to the lens, anterior brain (brain_A), and posterior brain (brain_P) was measured and compared. Image noise and CNR were assessed in the selected regions of interest (ROIs). RESULTS: Compared with that in the Default protocol, the absorbed dose to the lens reduced by up to 28.33%,71.38%, and 71.12% in OBTCM, SPS, and SPS+OBTCM, respectively. The noise level in OBTCM slightly (≤1.45HU) increased than that in Default protocol, and the SPS or SPS+OBTCM mode resulted in a quantitatively small increase (≤2.58HU) in three phantoms. There was no significant difference in CNR of different phantoms under varies scanning modes (p > 0.05). CONCLUSIONS: During head CT examinations, the SPS mode can reduce the radiation dose while maintaining image quality. SPS+OBTCM couldn't further effectively reduce the absorbed dose to the lens for 1-yr and 5-yr-old phantoms. Thus, SPS mode in pediatric and SPS+OBTCM mode in adult are better than other modes, and should be used in clinical practice.

A radiomics nomogram analysis based on CT images and clinical features for preoperative Lauren classification in gastric cancer.

PURPOSE: To develop a combined radiomics nomogram based on computed tomography (CT) images and clinical features to preoperatively distinguish Lauren's diffuse-type gastric cancer (GC) from intestinal-type GC. METHODS: Ninety-five patients with Lauren's intestinal or diffuse-type GC confirmed by postoperative pathology had their preoperative clinical information and dynamic contrast CT images retrospectively analyzed and were subdivided into training and test groups in a 7:3 ratio. To select the optimal features and construct the radiomic signatures, we extracted, filtered, and minimized the radiomic features from arterial phase (AP) and venous phase (VP) CT images. We constructed four models (clinical model, AP radiomics model, VP radiomics model, and radiomics-clinical model) to assess and compare their predictive performance between the intestinal- and diffuse-type GC. Receiver-operating characteristic (ROC) curve, area under the ROC curve (AUC), and the DeLong test were used for assessment and comparison. In this study, radiomic nomograms integrating combined radiomic signatures and clinical characteristics were developed. RESULTS: Compared to the AP radiomics model, the VP radiomics model had better performance, with an AUC of 0.832 (95% confidence interval [CI], 0.735, 0.929) in the training cohort and 0.760 (95% CI 0.580, 0.940) in the test cohort. Among the combined models that assessed Lauren's type GC, the model including age and VP radiomics showed the best performance, with an AUC of 0.849 (95% CI 0.758, 0.940) in the training cohort and 0.793 (95% CI 0.629, 0.957) in the test cohort. CONCLUSIONS: Nomogram incorporating radiomic signatures and clinical features effectively differentiated Lauren's diffuse-type from intestinal-type GC.

Optimization of scan parameters to reduce acquisition time for RESOLVE-based diffusion kurtosis imaging (DKI) in nasopharyngeal carcinoma (NPC).

OBJECTIVE: To shorten acquisition time of readout segmentation of long variable echo trains (RESOLVE)-based diffusion kurtosis imaging (DKI) via Readout Partial Fourier (RPF) and b-value combinations. METHODS: The RESOLVE-based DKI images of 38 patients with nasopharyngeal carcinoma (NPC) were prospectively enrolled. For RESOLVE-based DKI images with 5/8 RPF and without RPF, objective and subjective evaluations of image quality were performed. A total of nine groups with different b-value combinations were simulated, and the influence of different b-value combinations for RESOLVE-RPF-based DKI sequences was assessed using the intraclass correlation coefficient (ICC). RESULTS: The mean values of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in DKI images without RPF were higher than those with 5/8 RPF (252.9 ± 77.7 vs 247.3 ± 85.5 and 5.8 ± 2.8 vs 5.4 ± 2.3, respectively), but not significantly (p = 0.460 and p = 0.180, respectively). In comparing the ICCs between nine groups of different b-value combinations in RESOLVE-RPF-based DKI, group (200, 800, 2000 s/mm2), group (200, 400, 800, 2000 s/mm2) and group (200, 800, 1500, 2000 s/mm2) were not significantly different (p > 0.001) and showed excellent agreement (0.81-1.00) with that of group (200, 400, 800, 1500, 2000 s/mm2). Using b-value optimization and RPF technology, the group with RPF (200, 400, 800, 2000 s/mm2) showed a 56% reduced scanning compared with the group without RPF (200, 400, 800, 1500, 2000 s/mm2; 3 min 46 s vs 8 min 31 s, respectively). CONCLUSION: DKI with RPF did not significantly affect image quality, but both RPF and different b-value combinations can affect the scanning time. The combination of RPF and b-value optimization can ensure the stability of DKI parameters and reduce the scanning time by 56%. ADVANCES IN KNOWLEDGE: This work is to optimize scan parameters, e.g. RPF and b-value combinations, to reduce acquisition time for RESOLVE-based DKI in NPC. To our knowledge, the effect of RESOLVE-RPF and b-value combinations on DKI has not been reported.

Reproducibility of radiomics features derived from intravoxel incoherent motion diffusion-weighted MRI of cervical cancer.

BACKGROUND: The reproducibility of intravoxel incoherent motion (IVIM)-based radiomics studies in humans has not been reported. PURPOSE: To determine the inter- and intra-observer variability on the reproducibility of IVIM-based radiomics features in cervical cancer (CC). MATERIAL AND METHODS: The IVIM images of 25 patients with CC were retrospectively collected. Based on the high-resolution T2-weighted images, the regions of interest (ROIs) were independently delineated twice in diffusion-weighted images at a b value of 1000 s/mm2 (interval time was one month) by two radiologists. This was done at the largest transversal cross-sections of the tumors. The ROI was subsequently used in apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps derived from IVIM images. In total, 105 radiomics features were then finally extracted from the IVIM-derived maps. The inter- and intra-observer reproducibility of IVIM-derived features was then evaluated using the intraclass correlation coefficient. RESULTS: Inter- and intra-observer variability affected the reproducibility of radiomics features. D* map had 100% and 95% reproducible features, ADC map had 89% and 93%, D map had 97% and 86%, while f map had 54% and 62% reproducible features with good to excellent reliability in the intra-observer analysis. Similarly, D* map had 90% and 94%, ADC map had 85% and 70%, D map had 81% and 78%, while f map had 41% and 93% reproducible features with good to excellent reliability in the inter-observer analysis. CONCLUSION: Inter- and intra-observer variability can affect radiomics analysis. Cognizant to this, multicenter studies should pay more attention to intra- and inter-observer variability.

The Frequency of Circulating Tumour Cells and the Correlation with the Clinical Response to Standard Chemoradiotherapy in Locally Advanced Nasopharyngeal Carcinoma: A Prospective Study.

PURPOSE: Circulating tumour cells (CTCs) have been found to correlate with treatment response and prognosis in some cancers; however, such correlations have not been reported in nasopharyngeal carcinoma (NPC). We aimed to determine the relationship between CTCs and the treatment response in NPC. PATIENTS AND METHODS: In this prospective study, we ascertained the karyotype of CTCs and identified a possible correlation between karyotype and treatment response in locally advanced NPC (LANPC). We prospectively collected peripheral blood from LANPC patients. CTCs were measured by negative enrichment with immunofluorescence in situ hybridization (imFISH) and a centromere of chromosome 8 (CEP8) probe. Chromosome 8 was karyotyped in CTCs, which were identified as triploid, tetraploid or multiploid. Patients were then treated with platinum-based induction chemotherapy followed by concurrent chemoradiotherapy. CTCs were measured before and after treatment. RESULTS: We detected CTCs in 27 of 50 (54%) patients, which served as a baseline value. The results were independent of age, smoking history and NPC clinical stage. All of the 27 evaluable enrolled patients with detectable CTCs showed decreases in both total CTCs and CTCs of different ploidies after treatment (P<0.05). Reductions in CTCs were significantly more common in patients with a complete response (CR) than in those with a partial response (PR) (P<0.05). The presence of fewer tetraploid CTCs before treatment had a positive predictive value for a CR to chemoradiotherapy (P<0.05). CTC-positive patients had a shorter PFS after treatment (P=0.03). CONCLUSION: The decrease in CTCs was correlated with therapeutic efficacy in patients with LANPC, and the presence of tetraploid CTCs before treatment is a potential predictive factor for clinical outcomes.

3D-printed breast phantom for multi-purpose and multi-modality imaging.

BACKGROUND: Breast imaging technology plays an important role in breast cancer planning and treatment. Recently, three-dimensional (3D) printing technology has become a trending issue in phantom constructions for medical applications, with its advantages of being customizable and cost-efficient. However, there is no current practice in the field of multi-purpose breast phantom for quality control (QC) in multi-modalities imaging. The purpose of this study was to fabricate a multi-purpose breast phantom with tissue-equivalent materials via a 3D printing technique for QC in multi-modalities imaging. METHODS: We used polyvinyl chloride (PVC) based materials and a 3D printing technique to construct a breast phantom. The phantom incorporates structures imaged in the female breast such as microcalcifications, fiber lesions, and tumors with different sizes. Moreover, the phantom was used to assess the sensitivity of lesion detection, depth resolution, and detectability thresholds with different imaging modalities. Phantom tissue equivalent properties were determined using computed tomography (CT) attenuation [Hounsfield unit (HU)] and magnetic resonance imaging (MRI) relaxation times. RESULTS: The 3D-printed breast phantom had an average background value of 36.2 HU, which is close to that of glandular breast tissue (40 HU). T1 and T2 relaxation times had an average relaxation time of 206.81±17.50 and 20.22±5.74 ms, respectively. Mammographic imaging had improved detection of microcalcification compared with ultrasound and MRI with multiple sequences [T1WI, T2WI and short inversion time inversion recovery (STIR)]. Soft-tissue lesion detection and cylindrical tumor contrast were superior with mammography and MRI compared to ultrasound. Hemispherical tumor detection was similar regardless of the imaging modality used. CONCLUSIONS: We developed a multi-purpose breast phantom using a 3D printing technique and determined its value for multi-modal breast imaging studies.

Design and fabrication of a personalized anthropomorphic phantom using 3D printing and tissue equivalent materials.

To fabricate an individualized anthropomorphic lung phantom with tissue-equivalent radiation attenuation properties using a cost-effective three-dimensional (3D) printing technique. Based on anonymized human chest CT images, the phantom contained a 3D-printed skin shell, filled with tissue equivalent materials with similar radiation attenuation characteristics. The filling materials were a mixture of CaCO3, MgO, agarose, NaCl, pearl powder and silica gel. The dose calculation accuracy of different treatment planning system (TPS) algorithms was validated and compared with the ion chamber measurements in the phantom, including tumor and surrounding normal tissues. The chest phantom was shown to represent a human's chest in terms of radiation attenuation property and human anatomy. The Hounsfield unit ranges were -60 to -100, 20 to 60, and 120 to 300 for fat, muscle, and bone, respectively. The actual measured values of the ionization chamber were 213.7 cGy for the tumor, 53.85 cGy for normal lung tissue, and 4.1 cGy for the spinal cord, compared to 214.1, 55.2, and 4.5 cGy, respectively, with use of the Monte Carlo algorithm in TPS. The application of 3D printing in anthropomorphic phantoms can improve personalized medical need and efficiency with reduce costs thus, can be used for radiation dose verification.

Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer.

Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung cancer and possible recurrences upon completion of treatment. Radiomics, an emerging noninvasive technology using medical imaging analysis and data mining methodology, has been adopted to the area of cancer diagnostics in recent years. Its potential application in response assessment for cancer treatment has also drawn considerable attention. Radiomics seeks to extract a large amount of valuable information from patients' medical images (both pretreatment and follow-up images) and quantitatively correlate image features with diagnostic and therapeutic outcomes. Radiomics relies on computers to identify and analyze vast amounts of quantitative image features that were previously overlooked, unmanageable, or failed to be identified (and recorded) by human eyes. The research area has been focusing on the predictive accuracy of pretreatment features for outcome and response and the early discovery of signs of tumor response, recurrence, distant metastasis, radiation-induced lung injury, death, and other outcomes, respectively. This review summarized the application of radiomics in response assessments in radiotherapy and chemotherapy for non-small cell lung cancer, including image acquisition/reconstruction, region of interest definition/segmentation, feature extraction, and feature selection and classification. The literature search for references of this article includes PubMed peer-reviewed publications over the last 10 years on the topics of radiomics, textural features, radiotherapy, chemotherapy, lung cancer, and response assessment. Summary tables of radiomics in response assessment and treatment outcome prediction in radiation oncology have been developed based on the comprehensive review of the literature.

[Effects of Qili Qiangxin Capsule on Lung Structural Remodeling in Heart Failure Rats after Myocardial Infarction and Its Mechanism].

Objective To observe the effect of Qili Qiangxin Capsule (QQC) in improving lung struc- tural remodeling on heart failure (HF) rats after myocardial infarction (Ml) and to study its possible mecha- nism. Methods The proximal left anterior descending branch of coronary artery was ligated using a terylene suture to establish acute myocardial infarction (AMI) rat model. After successful AMI modeling rats were ran- domly divided into the model group (intragastrically administered with distilled water at 1 mL/100 g, n =13) and the QQC group (intragastrically administered with QQC at the daily dose of 1 g/kg, n =9). And the sham-opera- tion group (intragastrically administered with distilled water at 1 mL/100 g, n =10) was also set up. After four weeks intervention heart functions of rats were detected using echocardiography. The pathological changes of lung structures were observed by HE and Masson staining method. Protein expressions of lung α-SMA, Collagen I, TGF-ß1, and p-Smad3 of the lung tissue were detected by immunohistochemistry and Western blot. Re- sults Compared with the sham-operation group, ejection fraction (EF) and fraction shortening (FS) decreased (P <0. 05) , protein expressions of lung left ventricular internal diastolic diameter (LVIDd), left ventric- ular internal systolic diameter (LVIDs), end diastolic volume (EDV), end systolic volume (ESV), α-smooth muscle actin (a-SMA), Collagen I, tumor growth factor-ß1 (TGF-ß1), and p-Smad3 increased (P <0.05) in the model group. The muscularized small arteries ratio and collagen area of the lung tissue increased in the model group (P <0. 05). Compared with the model group, EF and FS increased (P <0. 05), protein expressions of LVIDs, ESV, α-SMA, Collagen I, TGF-ß, , and p-Smad3 decreased (P <0.05) in the QQC group. The muscular- ized small arteries ratio and collagen area of the lung tissue decreased in the QQC group (P <0. 05). Conclusion QQC could improve lung structural remodeling degree of HF rats after MI, and its possible mechanism might be achieved by regulating TGF-beta,/Smad3 signaling pathways.

Beneficial Effects of Qili Qiangxin Capsule on Lung Structural Remodeling in Ischemic Heart Failure via TGF-ß1/Smad3 Pathway.

Qili qiangxin (QL) capsule is a traditional Chinese medicine that is widely used for the treatment of patients with chronic heart failure (CHF) of all etiologies, although the exact mechanisms of action remain unclear. CHF leads to pulmonary vascular remodelling and thickening of the alveolar-capillary barrier that may be important mechanisms in the poor clinical outcome in patients with end-stage heart failure. We examined whether QL could improve lung injury in ischemic CHF by reducing lung remodeling. Rats with myocardial infarct received QL (1.0 g/kg/day) for 4 weeks. Echocardiographic and morphometric measurements were obtained followed by echocardiography, histological staining, and immunohistochemical analysis of lung sections. CHF caused significant lung structural remodeling evidenced by collagen deposition and thickening of the alveolar septa after myocardial infarct that were greatly improved by QL. Lung weight increased after infarct with no evidence of pulmonary edema and was normalized by QL. QL also reduced lung transforming growth factor-ß1 (TGF-ß1), p-Smad3, tumor necrosis factor-α (TNF-α), and Toll-like receptor-4 (TLR4) expression. Thus, QL reduces lung remodeling associated with CHF, mainly by suppressing the TGF-ß1/Smad3 signaling pathway. The mechanism may also involve inhibition of TLR4 intracellular signaling.