Effect of contrast agent on T2-weighted fat-suppressed imaging and diffusion-weighted imaging in the diagnosis of breast tumors.

Background: Although previous studies have shown that the injection of contrast agents can improve image quality, the specific impact of this on T2-weighted fat-suppressed (T2 FS) and diffusion-weighted imaging (DWI) sequences in the diagnosis of breast cancer remains incompletely understood. In particular, there is insufficient research on how contrast agents affect the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values within these sequences, and how these changes influence the diagnosis of benign and malignant breast tumors. Methods: Breast magnetic resonance images (MRI) were obtained from 178 consecutive patients on a 3T scanner. The SNR and CNR of lesions on T2 FS sequence were calculated before and after contrast agent injection and compared. Differences between pre- and post-contrast ADC in identifying different tumor types were compared using the Kruskal-Wallis H-test and the paired comparison test. The accuracy of ADC values between pre- and post-contrast in distinguishing benign and malignant breast masses was assessed using receiver operating characteristic (ROC) curves. Results: The SNR and CNR of T2 FS sequence increased after contrast injection, and especially for invasive cancer and benign tumor, the increase was significant. For DWI, there was a slight increase or decrease of ADC values after contrast injection, but the ADC values before and after contrast had a similar effect in identifying different types of tumors. In the ROC curve analysis for assessing benign and malignant breast tumors, the area under the curve (AUC) before and after contrast showed similar results. Conclusions: Contrast agent injection can improve the SNR and CNR of T2 FS sequence, thus providing higher quality images for the diagnosis of breast lesions. Furthermore, injection of contrast agent had little effect on the ability of ADC values to identify different types of lesions and both ADC values before and after the contrast agent were able to distinguish between benign and malignant tumors with almost the same accuracy.

Nanodelivery Systems as a Novel Strategy to Overcome Treatment Failure of Cancer.

Despite the tremendous progress in cancer treatment in recent decades, cancers often become resistant due to multiple mechanisms, such as intrinsic or acquired multidrug resistance, which leads to unsatisfactory treatment effects or accompanying metastasis and recurrence, ultimately to treatment failure. With a deeper understanding of the molecular mechanisms of tumors, researchers have realized that treatment designs targeting tumor resistance mechanisms would be a promising strategy to break the therapeutic deadlock. Nanodelivery systems have excellent physicochemical properties, including highly efficient tissue-specific delivery, substantial specific surface area, and controllable surface chemistry, which endow nanodelivery systems with capabilities such as precise targeting, deep penetration, responsive drug release, multidrug codelivery, and multimodal synergy, which are currently widely used in biomedical researches and bring a new dawn for overcoming cancer resistance. Based on the mechanisms of tumor therapeutic resistance, this review summarizes the research progress of nanodelivery systems for overcoming tumor resistance to improve therapeutic efficacy in recent years and offers prospects and challenges of the application of nanodelivery systems for overcoming cancer resistance.

5T magnetic resonance imaging: radio frequency hardware and initial brain imaging.

Background: We aimed to demonstrate the feasibility of generating high-resolution human brain magnetic resonance imaging (MRI) at 5 Tesla (T) using a quadrature birdcage transmit/48-channel receiver coil assembly. Methods: A quadrature birdcage transmit/48-channel receiver coil assembly was designed for human brain imaging at 5T. The radio frequency (RF) coil assembly was validated by electromagnetic (EM) simulations and phantom imaging experimental studies. The simulated B1+ field inside a human head phantom and inside a human head model generated by the birdcage coils driven in circularly polarized (CP) mode at 3T, 5T and 7T was compared. Signal-to-noise ratio (SNR) maps, the inverse g-factor maps for evaluation of parallel imaging performance, anatomic images, angiography images, vessel wall images and susceptibility weighted images (SWI) were acquired using the RF coil assembly at 5T and compared to those acquired using a 32-channel head coil on a 3T MRI scanner. Results: For the EM simulations, 5T MRI provided less RF inhomogeneity compared to that of 7T. In the phantom imaging study, the distributions of the measured B1+ field were consistent with the distributions of the simulated B1+ field. In the human brain imaging study, the average SNR value of the brain in the transversal plane at 5T was 1.6 times of that at 3T. The 48-channel head coil at 5T had higher parallel acceleration capability than the 32-channel head coil at 3T. The anatomic images at 5T also showed higher SNR than those at 3T. Improved delineation of the hippocampus, lenticulostriate arteries, and basilar arteries was observed at 5T compared to 3T. SWI with a higher resolution of 0.3 mm ×0.3 mm ×1.2 mm could be acquired at 5T, which enabled better visualization of small blood vessels compared to that at 3T. Conclusions: 5T MRI can provide significant SNR improvement compared to that of 3T with less RF inhomogeneity than that of 7T. The ability to obtain high quality in vivo human brain images at 5T using the quadrature birdcage transmit/48-channel receiver coil assembly has significant in clinical and scientific research applications.

Dark blood T2-weighted imaging of the human heart with AI-assisted compressed sensing: a patient cohort study.

Background: Dark blood T2-weighted (DB-T2W) imaging is widely used to evaluate myocardial edema in myocarditis and inflammatory cardiomyopathy. However, this technique is sensitive to arrhythmia, tachycardia, and cardiac and respiratory motion due to the long scan time with multiple breath-holds. The application of artificial intelligence (AI)-assisted compressed sensing (ACS) has facilitated significant progress in accelerating medical imaging. However, the effect of DB-T2W imaging on ACS has not been elucidated. This study aimed to examine the effects of ACS on the image quality of single-shot and multi-shot DB-T2W imaging of edema. Methods: Thirty-three patients were included in this study and received DB-T2W imaging with ACS, including single-shot acquisition (SS-ACS) and multi-shot acquisition (MS-ACS). The resulting images were compared with those of the conventional multi-shot DB-T2W imaging with parallel imaging (MS-PI). Quantitative assessments of the signal-to-noise ratio (SNR), tissue contrast ratio (CR), and contrast-to-noise ratio (CNR) were performed. Three radiologists independently evaluated the overall image quality, blood nulling, free wall of the left ventricle, free wall of the right ventricle, and interventricular septum using a 5-point Likert scale. Results: The total scan time of the DB-T2W imaging with ACS was significantly reduced compared to the conventional parallel imaging [number of heartbeats (SS-ACS:MS-ACS:MS-PI) =19:63:99; P<0.001]. The SNRmyocardium and CNRblood-myocardium of MS-ACS and SS-ACS were higher than those of MS-PI (all P values <0.01). Furthermore, the CRblood-myocardium of SS-ACS was also higher than that of MS-PI (P<0.01). There were significant differences in overall image quality, blood nulling, left ventricle free wall visibility, and septum visibility between the MS-PI, MS-ACS, and SS-ACS protocols (all P values <0.05). Moreover, blood in the heart was better nulled using SS-ACS (P<0.01). Conclusions: The ACS method shortens the scan time of DB-T2W imaging and achieves comparable or even better image quality compared to the PI method. Moreover, DB-T2W imaging using the ACS method can reduce the number of breath-holds to 1 with single-shot acquisition.

Significance of differential expression of OLFM4 in the development of endometrial adenocarcinoma.

The incidence of endometrial adenocarcinoma (EA) has increased worldwide in recent years due to the widespread use of estrogen therapy and the overall increase in life expectancy. However, we know of no sensitive molecular index that can be used to predict the onset of EA, evaluate the therapeutic effects of treatment agents, or provide prognostic benefit in post-treatment follow-up. To explore the correlation between human olfactomedin 4 (OLFM4) and the clinicopathologic parameters of EA, and to determine the precise involvement of OLFM4 as a related factor in the occurrence and development of EA. We enrolled 61 gynecologic patients for a retrospective study at the Tai'an Central Hospital of Shandong Province from January 1, 2016, to June 30, 2022. We determined the expression levels of estrogen receptor α (ERα), progesterone receptor (PR), and OLFM4 proteins in endometrial tissue with the immunohistochemical S-P staining method, and analyzed the correlations among ERα, PR, and OLFM4 protein expression levels and with the pathologic stage, histologic grade, myometrial invasiveness, and lymphatic metastasis of EA. The expression levels of OLFM4 in EA were higher than in normal endometrium (P = .036). The expression level of OLFM4 protein in stage II-III patients was higher than that in stage I patients (P = .034), and the expression levels of ERα and PR proteins in EA were lower than those in normal endometrial tissue (P = .014 and P = .0005). While we observed no correlation in endometrial tissues of disparate pathologic types between OLFM4 and the expression levels of ERα and PR proteins, we noted a positive correlation between the expression levels of ERα and PR protein. The expression level of OLFM4 protein increased with the malignant degree of endometrial lesions and OLFM4 protein expression was related to the FIGO stage of EA. And OLFM4 protein can be used as 1 of the potential diagnostic factors for endometrial lesions, which is worthy of further study.

Mid-term follow-up surgical results in 284 cases of clival chordomas: the risk factors for outcome and tumor recurrence.

OBJECTIVE: Skull base chordoma (SBC) is rare and one of the most challenging diseases to treat. We aimed to assess the optimal timing of adjuvant radiation therapy (RT) and to evaluate the factors that influence resection and long-term outcomes. METHODS: In total, 284 patients with 382 surgeries were enrolled in this retrospective study. Postsurgically, 64 patients underwent RT before recurrence (pre-recurrence RT), and 47 patients underwent RT after recurrence. During the first attempt to achieve gross-total resection (GTR), when the entire tumor was resected, 268 patients were treated with an endoscopic midline approach, and 16 patients were treated with microscopic lateral approaches. Factors associated with the success of GTR were identified using χ2 and logistic regression analyses. Risk factors associated with chordoma-specific survival (CSS) and progression-free survival (PFS) were evaluated with the Cox proportional hazards model. RESULTS: In total, 74.6% of tumors were marginally resected [GTR (40.1%), near-total resection (34.5%)]. History of surgery, large tumor volumes, and tumor locations in the lower clivus were associated with a lower GTR rate. The mean follow-up period was 43.9 months. At the last follow-up, 181 (63.7%) patients were alive. RT history, histologic subtype (dedifferentiated and sarcomatoid), non-GTR, no postsurgical RT, and the presence of metastasis were associated with poorer CSS. Patients with pre-recurrence RT had the longest PFS and CSS, while patients without postsurgical RT had the worst outcome. CONCLUSION: GTR is the goal of initial surgical treatment. Pre-recurrence RT would improve outcome regardless of GTR.

Implementation and prospective clinical validation of AI-based planning and shimming techniques in cardiac MRI.

PURPOSE: Cardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce image acquisition time without compromising image quality (IQ), and improve magnetic field uniformity. Here, we aim to implement two AI-based deep learning techniques for automatic slice alignment and cardiac shimming and evaluate their performance in clinical cardiac magnetic resonance imaging (MRI). METHODS: Two deep neural networks were developed, trained, and validated on pre-acquired cardiac MRI datasets (>500 subjects) to achieve automatic slice planning and shimming (implemented in the scanner) for CMR. To examine the performance of our automated cardiac planning (EasyScan) and AI-based shim (AI shim), two prospective studies were performed subsequently. For the EasyScan validation, 10 healthy subjects underwent two identical CMR protocols: with manual cardiac planning and with AI-based EasyScan to assess protocol scan time difference and accuracy of cardiac plane prescriptions on a 1.5 T clinical MRI scanner. For the AI shim validation, a total of 20 subjects were recruited: 10 healthy and 10 cardio-oncology patients with referrals for a CMR examination. Cine images were obtained with standard cardiac volume shim and with AI shim to assess signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall IQ (sharpness and MR image degradation), ejection fraction (EF), and absolute wall thickening. A hybrid statistical method using of nonparametric (Wilcoxon) and parametric (t-test) assessments was employed for statistical analyses. RESULTS: CMR protocol with AI-based plane prescriptions, EasyScan, minimized operator dependence and reduced overall scanning time by over 2 min (∼13 % faster, p < 0.001) compared to the protocol with manual cardiac planning. EasyScan plane prescriptions also demonstrated more accurate (less plane angulation errors from planes manually prescribed by a certified cardiac MRI technologist) cardiac planes than previously reported strategies. Additionally, AI shim resulted in improved B0 field homogeneity. Cine images obtained with AI shim revealed a significantly higher SNR (12.49%; p = 0.002) than those obtained with volume shim (volume shim: 32.90 ± 7.42 vs. AI shim: 37.01 ± 8.87) for the left ventricle (LV) myocardium. LV myocardium CNR was 12.48% higher for cine imaging with AI shim (149.02 ± 39.15) than volume shim (132.49 ± 33.94). Images obtained with AI shim resulted in sharper images than those obtained with volume shim (p = 0.012). The LVEF and absolute wall thickening also showed that differences exist between the two shimming methods. The LVEF by AI shim was shown to be slightly larger than LVEF by volume shim in two groups: 2.87% higher with AI shim for the healthy group and 1.70% higher with AI shim for the patient group. The LV absolute wall thickening (in mm) also showed that differences exist between shimming methods for each group with larger changes observed in the patient group (healthy: 3.31%, p = 0.234 and patient group: 7.29%, p = 0.059). CONCLUSIONS: CMR exams using EasyScan for cardiac planning demonstrated accelerated cardiac exam compared to the CMR protocol with manual cardiac planning. Improved and more uniform B0 magnetic field homogeneity also achieved using AI shim technique compared to volume shimming.

Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging.

OBJECTIVE: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. MATERIALS AND METHODS: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (µFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. RESULTS: FA, MD, MKA, MKI, MKT, µFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). CONCLUSION: DIVIDE is a promising technique for glioma characterization and diagnosis. KEY POINTS: • DIVIDE metrics MKI is related to cell density heterogeneity while MKA and µFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKI was larger than MKA which indicates predominant cell density heterogeneity in gliomas. • MKA and MKI increased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKA in relation to the cell density heterogeneity metric MKI.

Clinical Implication of Systemic Immune-Inflammation Index and Prognostic Nutritional Index in Skull Base Chordoma Patients.

Inflammation associated markers and nutritional indexes are associated with survival, and act as novel prognostic grading systems in patients with cancer, though the role of these markers in chordoma remains unclear. The current study aimed to characterize systemic immune-inflammation index (SII) and prognostic nutritional index (PNI), and their relationship with clinicopathological data and survival in skull base chordoma. Our retrospective study enrolled 183 patients with primary skull base chordoma who received surgical treatment. Clinicopathological data and preoperative blood tests including neutrophil, lymphocyte, platelet counts and albumin level were collected from medical records. Neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), SII, PNI were calculated and the optimal cut-off values of these markers were used for further survival analysis via Kaplan-Meier survival analysis and Cox proportional hazards regression analysis. The value of NLR, PLR, SII, and PNI in skull base chordoma ranged from 0.44-6.48, 45.36-273.94, 113.37-1761.45, and 43.40-70.65, respectively. PNI was significantly correlated with patients' sex (p = 0.005) and age (p = 0.037). SII was positively correlated with NLR and PLR, but negatively correlated with PNI. The median overall survival (OS) time was 74.0 months and Kaplan-Meier survival analysis indicated that all four indexes were associated with OS. Multivariable Cox proportional hazards regression analysis identified that high SII was an independent prognostic factor for poor OS. More importantly, patients with high SII and PNI had the worst outcomes and combined use of SII and PNI increased the predictive ability for patients' survival in skull base chordoma. Our results suggest SII and PNI may be effective prognostic indicators of OS for patients with primary skull base chordoma after surgical resection.

Whole genome sequencing of skull-base chordoma reveals genomic alterations associated with recurrence and chordoma-specific survival.

Chordoma is a rare bone tumor with an unknown etiology and high recurrence rate. Here we conduct whole genome sequencing of 80 skull-base chordomas and identify PBRM1, a SWI/SNF (SWItch/Sucrose Non-Fermentable) complex subunit gene, as a significantly mutated driver gene. Genomic alterations in PBRM1 (12.5%) and homozygous deletions of the CDKN2A/2B locus are the most prevalent events. The combination of PBRM1 alterations and the chromosome 22q deletion, which involves another SWI/SNF gene (SMARCB1), shows strong associations with poor chordoma-specific survival (Hazard ratio [HR] = 10.55, 95% confidence interval [CI] = 2.81-39.64, p = 0.001) and recurrence-free survival (HR = 4.30, 95% CI = 2.34-7.91, p = 2.77 × 10-6). Despite the low mutation rate, extensive somatic copy number alterations frequently occur, most of which are clonal and showed highly concordant profiles between paired primary and recurrence/metastasis samples, indicating their importance in chordoma initiation. In this work, our findings provide important biological and clinical insights into skull-base chordoma.

A Series of 62 Skull Base Chordomas in Pediatric and Adolescent Patients: Clinical Characteristics, Treatments, and Outcomes.

BACKGROUND: Skull base chordomas in pediatric and adolescent patients are rare and challenging for surgeons. OBJECTIVE: Well-specified diagnosis and treatment are of great value for the long-term control of chordoma. This study summarizes well-followed pediatric and adolescent chordoma (PAC) patients treated in a single Asian center. METHODS: PAC patients were enrolled. Data collected included clinical presentation, tumor volume, texture, surgical approach, pathology, complications, adjuvant radiotherapy (RT), and long-term outcomes. RESULTS: Sixty-two patients were identified from a total of 516 skull base chordoma patients (12%). Diplopia was the most prominent complaint (30%). The craniocervical junction area was the most common location (41.8%) and had the highest proportion of large tumors. The gross total resection (GTR) rate was 20.3%. The GTR rate was lowest for tumors located in the craniocervical junction area. Thirty-eight cases experienced surgical complications. Of note, there was a significant difference in the complication rate between endoscopic approaches (22.7%) and open approaches (57.9%) (P = 0.005). The mean follow-up was 66.5 months. The GTR group showed better survival compared with the non-GTR group (P = 0.043). Metastases were found in two cases. No significant difference in the overall survival (OS) time was found between the group with RT and the group without RT (P = 0.559). CONCLUSIONS: A higher proportion of PAC patients than previously reported exist in the population in Asia, and the metastatic rate is lower. GTR predicts excellent long-term control of the disease. RT should be considered on an individual basis.

Mean platelet volume and platelet distribution width serve as prognostic biomarkers in skull base chordoma: a retrospective study.

BACKGROUND: Increasing studies have demonstrated that activated platelets play an essential role in tumour progression. However, the level and prognostic role of platelet indices in chordoma patients remain unclear. The aim of the current study was to characterize the prognostic performance of platelet count (PLT), mean platelet volume (MPV) and platelet distribution width (PDW) in skull base chordoma patients. METHODS: 187 primary skull base chordoma patients between January 2008 and September 2014 were enrolled in this retrospective study. The optimal cut-off values were determined by X-tile software, and the correlations between PLT, MPV, PDW and clinicopathological features were further analysed. Kaplan-Meier curve and Cox regression analysis were used for survival analysis. RESULTS: The values of preoperative PTL, MPV and PDW ranged from 104 to 501 × 109/L, 6.7 to 14.2 fl, and 7.8 to 26.2%, respectively. Elevated PLT was associated with larger tumour volume (p = 0.002). Kaplan-Meier survival analysis revealed that increased MPV and PDW were associated with shorter overall survival (p = 0.022 and 0.008, respectively). Importantly, multivariate Cox analysis demonstrated that elevated PDW was an independent unfavourable predictive factor for overall survival (hazard ratio (HR), 2.154, 95% confidence interval (CI), 1.258-3.688, p = 0.005). CONCLUSIONS: Our data show that elevated MPV and PDW are associated with poor outcomes in skull base chordoma and that PDW may be helpful to identify patients with high risk.

Prognostic Value of Cumulative Score Based on Preoperative Fibrinogen and Albumin Level in Skull Base Chordoma.

OBJECTIVE: Inflammation and malnutrition have been shown to be correlated with tumor progression and a poor prognosis in various cancers. However, the clinical implications of biomarkers of inflammation and malnutrition in chordoma have not been elucidated. We attempted to characterize the fibrinogen and albumin levels in skull base chordoma and investigate their correlations with clinicopathological data and survival. METHODS: The preoperative levels of fibrinogen and albumin were assessed in 183 primary skull base chordoma patients. The cutoff values were determined by X-tile software, and their correlations with patient prognosis were further explored using the Kaplan-Meier curve and Cox proportional hazards regression analysis. In addition, the predictive performances of these markers in survival were evaluated by receiver operating characteristic curves. RESULTS: The values of fibrinogen and albumin in skull base chordoma patients ranged from 1.73 to 7.40 and 37.6 to 53.0 g/L, respectively. The optimal cutoff values for fibrinogen and albumin were 3.29 and 44.60 g/L, respectively. Fibrinogen and albumin were correlated with the patient age and tumor pathology types. Albumin, but not fibrinogen, was associated with the patients' progression-free survival and overall survival. Importantly, the FA score, which combines fibrinogen and albumin, could independently predict both progression-free survival and overall survival, and enhanced the performance of fibrinogen or albumin in survival prediction in skull base chordoma. CONCLUSION: Our data reveal the clinical prognostic role of albumin and suggest that the FA score may be a valuable prognostic grading system in skull base chordoma.

LncRNA and mRNA expression profiles reveal the potential roles of lncRNA contributing to regulating dural penetration in clival chordoma.

Chordoma is a rare bone cancer originating from embryologic notochordal remnants. Clival chordomas show different dural penetration ability, with serious dural penetration exhibiting poorer prognosis. The molecular mechanism of dural penetration is not clear. We analyzed lncRNA and mRNA profiles in 12 chordoma patients with different degrees of dural penetration using expression microarrays. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA-mRNA co-expression network. LncRNAs were classified into lincRNA, enhancer-like lncRNA, or antisense lncRNA. Biological functions for lncRNAs were predicted according to the lncRNA-mRNA network and adjacent coding genes by pathway analysis. The 2760 lncRNAs and 3988 mRNAs were differentially expressed in chordomas between two groups of patients with and without dural penetration. Possible pathway involvement of the significance among the 55 lncRNAs located in the lncRNA-mRNA network, 24 lincRNAs, 7 enhancer-like lncRNAs, and 14 antisense lncRNAs include cell adhesion, metastasis, invasion, proliferation, and apoptosis. Expression of 10 lncRNAs and mRNAs, and epidermal growth factor mRNA with two identified lncRNAs were subsequently verified by qRT-PCR in chordoma tissues. Our report predicts the biological functions of many lncRNAs which may be used as diagnostic and prognostic biomarkers as well as therapeutic targets during the process of dural penetration in chordoma.

Predictive Value of Transforming Growth Factor-α and Ki-67 for the Prognosis of Skull Base Chordoma.

OBJECTIVE: We aimed to characterize the expression of transforming growth factor-α (TGF-α) and Ki-67 and to assess the relationship between TGF-α and Ki-67 expression and prognostic factors in skull base chordoma. METHODS: We retrospectively analyzed the data from 46 patients with skull base chordoma. The follow-up duration ranged from 1 to 168 months (mean, 74.1). The survival data were statistically analyzed using the Kaplan-Meier method and multivariate Cox regression analysis. The expression of TGF-α and Ki-67 were detected by immunohistochemical staining of paraffin-embedded patient tissue specimens. RESULTS: The total resection (TR) group had longer overall survival compared with the non-TR group (P = 0.042). The TR group also had longer progression-free survival (PFS) than did the non-TR group (P = 0.046). The group with a high Ki-67 labeling index (Ki-67LI) had shorter overall survival than did the group with a low Ki-67LI (P = 0.039). Also, the group with a high Ki-67LI had significantly shorter PFS than did the group with a low Ki-67LI (P = 0.016). Moreover, the group with high TGF-α expression had significantly shorter PFS compared with the group with low TGF-α expression (P = 0.005). CONCLUSIONS: Our results have shown that high levels of TGF-α and Ki-67 are associated with shorter PFS in patients with chordoma. We have confirmed the role of Ki-67 as a functional molecular marker of poor prognosis. We also identified TGF-α as a potential novel biomarker for predicting prognosis for patients with skull base chordoma.

Seed prioritized unwrapping (SPUN) for MR phase imaging.

BACKGROUND: Region-growing-based phase unwrapping methods have the potential for lossless phase aliasing removal, but generally suffer from unwrapping error propagation associated with discontinuous phase and/or long calculation times. The tradeoff point between robustness and efficiency of phase unwrapping methods in the region-growing category requires improvement. PURPOSE: To demonstrate an accurate, robust, and efficient region-growing phase unwrapping method for MR phase imaging applications. STUDY TYPE: Prospective. SUBJECTS, PHANTOM: normal human subjects (10) / brain surgery patients (2) / water phantoms / computer simulation. FIELD STRENGTH/SEQUENCE: 3 T/gradient echo sequences (2D and 3D). ASSESSMENT: A seed prioritized unwrapping (SPUN) method was developed based on single-region growing, prioritizing only a portion (eg, 100 seeds or 1% seeds) of available seed voxels based on continuity quality during each region-growing iteration. Computer simulation, phantom, and in vivo brain and pelvis scans were performed. The error rates, seed percentages, and calculation times were recorded and reported. SPUN unwrapped phase images were visually evaluated and compared with Laplacian unwrapped results. STATISTICAL TESTS: Monte Carlo simulation was performed on a 3D dipole phase model with a signal-to-noise ratio (SNR) of 1-9 dB, to obtain the mean and standard deviation of calculation error rates and calculation times. RESULTS: Simulation revealed a very robust unwrapping performance of SPUN, reaching an error rate of <0.4% even with SNR as low as 1 dB. For all in vivo data, SPUN was able to robustly unwrap the phase images of modest SNR and complex morphology with visually minimal errors and fast calculation speed (eg, <4 min for 368 × 312 × 128 data) when using a proper seed priority number, eg, Nsp = 1 or 10 voxels for 2D and Nsp = 1% for 3D data. DATA CONCLUSION: SPUN offers very robust and fast region-growing-based phase unwrapping, and does not require any tissue masking or segmentation, nor poses a limitation over imaging parameters. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:62-70.

Using the K-nearest neighbor algorithm for the classification of lymph node metastasis in gastric cancer.

Accurate tumor, node, and metastasis (TNM) staging, especially N staging in gastric cancer or the metastasis on lymph node diagnosis, is a popular issue in clinical medical image analysis in which gemstone spectral imaging (GSI) can provide more information to doctors than conventional computed tomography (CT) does. In this paper, we apply machine learning methods on the GSI analysis of lymph node metastasis in gastric cancer. First, we use some feature selection or metric learning methods to reduce data dimension and feature space. We then employ the K-nearest neighbor classifier to distinguish lymph node metastasis from nonlymph node metastasis. The experiment involved 38 lymph node samples in gastric cancer, showing an overall accuracy of 96.33%. Compared with that of traditional diagnostic methods, such as helical CT (sensitivity 75.2% and specificity 41.8%) and multidetector computed tomography (82.09%), the diagnostic accuracy of lymph node metastasis is high. GSI-CT can then be the optimal choice for the preoperative diagnosis of patients with gastric cancer in the N staging.