Multi-contrast learning-guided lightweight few-shot learning scheme for predicting breast cancer molecular subtypes.

Invasive gene expression profiling studies have exposed prognostically significant breast cancer subtypes: normal-like, luminal, HER-2 enriched, and basal-like, which is defined in large part by human epidermal growth factor receptor 2 (HER-2), progesterone receptor (PR), and estrogen receptor (ER). However, while dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been generally employed in the screening and therapy of breast cancer, there is a challenging problem to noninvasively predict breast cancer molecular subtypes, which have extremely low-data regimes. In this paper, a novel few-shot learning scheme, which combines lightweight contrastive convolutional neural network (LC-CNN) and multi-contrast learning strategy (MCLS), is worthwhile to be developed for predicting molecular subtype of breast cancer in DCE-MRI. Moreover, MCLS is designed to construct One-vs-Rest and One-vs-One classification tasks, which addresses inter-class similarity among normal-like, luminal, HER-2 enriched, and basal-like. Extensive experiments demonstrate the superiority of our proposed scheme over state-of-the-art methods. Furthermore, our scheme is able to achieve competitive results on few samples due to joint LC-CNN and MCLS for excavating contrastive correlations of a pair of DCE-MRI.

MEAI: an artificial intelligence platform for predicting distant and lymph node metastases directly from primary breast cancer.

PURPOSE: Breast cancer patients typically have decent prognoses, with a 5-year survival rate of more than 90%, but when the disease metastases to lymph node or distant, the prognosis drastically declines. Therefore, it is essential for future treatment and patient survival to quickly and accurately identify tumor metastasis in patients. An artificial intelligence system was developed to recognize lymph node and distant tumor metastases on whole-slide images (WSIs) of primary breast cancer. METHODS: In this study, a total of 832 WSIs from 520 patients without tumor metastases and 312 patients with breast cancer metastases (including lymph node, bone, lung, liver, and other) were gathered. Based on the WSIs were randomly divided into the training and testing cohorts, a brand-new artificial intelligence system called MEAI was built to identify lymph node and distant metastases in primary breast cancer. RESULTS: The final AI system attained an area under the receiver operating characteristic curve of 0.934 in a test set of 187 patients. In addition, the potential for AI system to increase the precision, consistency, and effectiveness of tumor metastasis detection in patients with breast cancer was highlighted by the AI's achievement of an AUROC higher than the average of six board-certified pathologists (AUROC 0.811) in a retrospective pathologist evaluation. CONCLUSION: The proposed MEAI system can provide a non-invasive approach to assess the metastatic probability of patients with primary breast cancer.

A NOTCH1 Mutation Found in a Newly Established Ovarian Cancer Cell Line (FDOVL) Promotes Lymph Node Metastasis in Ovarian Cancer.

Peritoneal implantation and lymph node metastasis have different driving mechanisms in ovarian cancer. Elucidating the underlying mechanism of lymph node metastasis is important for treatment outcomes. A new cell line, FDOVL, was established from a metastatic lymph node of a patient with primary platinum-resistant ovarian cancer and was then characterized. The effect of NOTCH1-p.C702fs mutation and NOTCH1 inhibitor on migration was evaluated in vitro and in vivo. Ten paired primary sites and metastatic lymph nodes were analyzed by RNA sequencing. The FDOVL cell line with serious karyotype abnormalities could be stably passaged and could be used to generated xenografts. NOTCH1-p.C702fs mutation was found exclusively in the FDOVL cell line and the metastatic lymph node. The mutation promoted migration and invasion in cell and animal models, and these effects were markedly repressed by the NOTCH inhibitor LY3039478. RNA sequencing confirmed CSF3 as the downstream effector of NOTCH1 mutation. Furthermore, the mutation was significantly more common in metastatic lymph nodes than in other peritoneal metastases in 10 paired samples (60% vs. 20%). The study revealed that NOTCH1 mutation is probably a driver of lymph node metastasis in ovarian cancer, which offers new ideas for the treatment of ovarian cancer lymph node metastasis with NOTCH inhibitors.

Enhanced antitumor immune responses via a new agent [131I]-labeled dual-target immunosuppressant.

Radionuclides theranostic are ideal "partners" for bispecific antibodies to explore the immune response of patients and synergistic treatment. A bispecific single-domain antibody-Fc fusion protein, KN046, exhibits a good treatment effect by binding to programmed cell death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). An ionizing-radiation stimulus mediated by a low-dose of [131I] may be used for immunopotentiation. In this study, we established [131I]-labeled KN046 as a novel radioimmunotherapy agent to treat malignant melanoma and explored the mechanism. METHODS: After intravenous injection of [131I]-KN046, SPECT/CT imaging was applied to identify candidate targets for KN046 immunotherapy. [18F]-FDG and [68 Ga]-NOTA-GZP (granzyme B-specific PET imaging agent) micro-PET/CT imaging was used to assess the immune response in vivo after [131I]-KN046 treatment. The synergistic treatment effect of [131I]-KN046 was evaluated by exploring the [131I]-based radionuclide-induced release of tumor immunogenicity-related antigens as well as the histology and survival of tumor-bearing mice after treatment. RESULTS: The constructed [131I]-KN046 exhibited high affinity and specificity for PD-L1/CTLA-4 immune targets and had excellent in vivo intratumoral retention capability so as to achieve good antitumor efficacy. More importantly, the combination of low-dose [131I] and KN046-enhanced immunosensitivity increased the immunotherapy response rates significantly. Exposure of tumor cells to [131I]-KN046 led to upregulated expression of MHC-I and Fas surface molecules and significant increases in the degree of T-cell activation and counts of tumor-infiltrating immunocytes. CONCLUSION: Use of low-dose [131I] combined with a dual-target immunosuppressant could be exploited to identify the subset of treatment responders but also exhibited great potential for enhancing antitumor immune responses.

Semantic-Powered Explainable Model-Free Few-Shot Learning Scheme of Diagnosing COVID-19 on Chest X-Ray.

Chest X-ray (CXR) is commonly performed as an initial investigation in COVID-19, whose fast and accurate diagnosis is critical. Recently, deep learning has a great potential in detecting people who are suspected to be infected with COVID-19. However, deep learning resulting with black-box models, which often breaks down when forced to make predictions about data for which limited supervised information is available and lack inter-pretability, still is a major barrier for clinical integration. In this work, we hereby propose a semantic-powered explainable model-free few-shot learning scheme to quickly and precisely diagnose COVID-19 with higher reliability and transparency. Specifically, we design a Report Image Explanation Cell (RIEC) to exploit clinically indicators derived from radiology reports as interpretable driver to introduce prior knowledge at training. Meanwhile, multi-task collaborative diagnosis strategy (MCDS) is developed to construct N-way K-shot tasks, which adopts a cyclic and collaborative training approach for producing better generalization performance on new tasks. Extensive experiments demonstrate that the proposed scheme achieves competitive results (accuracy of 98.91%, precision of 98.95%, recall of 97.94% and F1-score of 98.57%) to diagnose COVID-19 and other pneumonia infected categories, even with only 200 paired CXR images and radiology reports for training. Furthermore, statistical results of comparative experiments show that our scheme provides an interpretable window into the COVID-19 diagnosis to improve the performance of the small sample size, the reliability and transparency of black-box deep learning models. Our source codes will be released on https://github.com/AI-medical-diagnosis-team-of-JNU/SPEMFSL-Diagnosis-COVID-19.

18F-FDG PET/CT radiomic analysis for classifying and predicting microvascular invasion in hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

Background: Microvascular invasion (MVI) is a critical risk factor for early recurrence of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). The aim of this study was to explore the contribution of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomic features for the preoperative prediction of HCC and ICC classification and MVI. Methods: In this retrospective study, 127 (HCC: ICC =76:51) patients with suspected MVI accompanied by either HCC or ICC were included (In HCC group, MVI positive: negative =46:30 in ICC group, MVI positive: negative =31:20). Results-driven feature engineering workflow was used to select the most predictive feature combinations. The prediction model was based on supervised machine learning classifier. Ten-fold cross validation on training cohort and independent test cohort were constructed to ensure stability and generalization ability of models. Results: For HCC and ICC classification, radiomics predictors composed of two PET and one CT feature achieved area under the curve (AUC) of 0.86 (accuracy, sensitivity, specificity was 0.82, 0.78, 0.88, respectively) on test cohort. For MVI prediction, in HCC group, our MVI prediction model achieved AUC of 0.88 (accuracy, sensitivity, specificity was 0.78, 0.88, 0.60 respectively) with three PET features associated with tumor stage on test cohort. In ICC group, the phenotype composed of two PET features and carbohydrate antigen 19-9 (CA19-9) achieved AUC of 0.90 (accuracy, sensitivity, specificity was 0.77, 0.75, 0.80, respectively). Conclusions: 18F-FDG PET/CT radiomic features integrating clinical factors have potential in HCC and ICC classification and MVI prediction, while PET features have dominant predictive power in model performance. The prediction model has value in providing a non-invasive biomarker for an earlier indication and comprehensive quantification of primary liver cancers.

Intelligent design of polymer nanogels for full-process sensitized radiotherapy and dual-mode computed tomography/magnetic resonance imaging of tumors.

Rationale: Development of intelligent radiosensitization nanoplatforms for imaging-guided tumor radiotherapy (RT) remains challenging. We report here the construction of an intelligent nanoplatform based on poly(N-vinylcaprolactam) (PVCL) nanogels (NGs) co-loaded with gold (Au) and manganese dioxide (MnO2) nanoparticles (NPs) for dual-mode computed tomography (CT)/magnetic resonance (MR) imaging-guided "full-process" sensitized RT of tumors. Methods: PVCL NGs were synthesized via precipitation polymerization and in situ loaded with Au and MnO2 NPs. The created PVCL-Au-MnO2 NGs were well characterized and systematically examined in their cytotoxicity, cellular uptake, intracellular oxygen and ·OH production, and cell cycle arrest in vitro, evaluated to disclose their RT sensitization effects of cancer cells and a tumor model, and assessed to validate their dual-mode CT/MR imaging potential, pharmacokinetics, biodistribution, and biosafety in vivo. Results: The formed PVCL-Au-MnO2 NGs with a size of 121.5 nm and good stability can efficiently generate reactive oxygen species through a Fenton-like reaction to result in cell cycle distribution toward highly radiosensitive G2/M phase prior to X-ray irradiation, sensitize the RT of cancer cells under X-ray through the loaded Au NPs to induce the significant DNA damage, and further prevent DNA-repairing process after RT through the continuous production of O2 catalyzed by MnO2 in the hybrid NGs to relieve the tumor hypoxia. Likewise, the in vivo tumor RT can also be guided through dual mode CT/MR imaging due to the Au NPs and Mn(II) transformed from MnO2 NPs. Conclusion: Our study suggests an intelligent PVCL-based theranostic NG platform that can achieve "full-process" sensitized tumor RT under the guidance of dual-mode CT/MR imaging.

Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization.

Positron Emission Tomography (PET) has become a preferred imaging modality for cancer diagnosis, radiotherapy planning, and treatment responses monitoring. Accurate and automatic tumor segmentation is the fundamental requirement for these clinical applications. Deep convolutional neural networks have become the state-of-the-art in PET tumor segmentation. The normalization process is one of the key components for accelerating network training and improving the performance of the network. However, existing normalization methods either introduce batch noise into the instance PET image by calculating statistics on batch level or introduce background noise into every single pixel by sharing the same learnable parameters spatially. In this paper, we proposed an attentive transformation (AT)-based normalization method for PET tumor segmentation. We exploit the distinguishability of breast tumor in PET images and dynamically generate dedicated and pixel-dependent learnable parameters in normalization via the transformation on a combination of channel-wise and spatial-wise attentive responses. The attentive learnable parameters allow to re-calibrate features pixel-by-pixel to focus on the high-uptake area while attenuating the background noise of PET images. Our experimental results on two real clinical datasets show that the AT-based normalization method improves breast tumor segmentation performance when compared with the existing normalization methods.

Fibronectin-Coated Metal-Phenolic Networks for Cooperative Tumor Chemo-/Chemodynamic/Immune Therapy via Enhanced Ferroptosis-Mediated Immunogenic Cell Death.

The development of nanomedicine formulations to overcome the disadvantages of traditional chemotherapeutic drugs and integrate cooperative theranostic modes still remains challenging. Herein, we report the facile construction of a multifunctional theranostic nanoplatform based on doxorubicin (DOX)-loaded tannic acid (TA)-iron (Fe) networks (for short, TAF) coated with fibronectin (FN) for combination tumor chemo-/chemodynamic/immune therapy under the guidance of magnetic resonance (MR) imaging. We show that the DOX-TAF@FN nanocomplexes created through in situ coordination of TA and Fe(III) and physical coating with FN have a mean particle size of 45.0 nm, are stable, and can release both DOX and Fe in a pH-dependent manner. Due to the coexistence of the TAF network and DOX, significant immunogenic cell death can be caused through enhanced ferroptosis of cancer cells via cooperative Fe-based chemodynamic therapy and DOX chemotherapy. Through further treatment with programmed cell death ligand 1 antibody for an immune checkpoint blockade, the tumor treatment efficacy and the associated immune response can be further enhanced. Meanwhile, with FN-mediated targeting, the DOX-TAF@FN platform can specifically target tumor cells with high expression of αvß3 integrin. Finally, the TAF network also enables the DOX-TAF@FN to have an r1 relaxivity of 6.1 mM-1 s-1 for T1-weighted MR imaging of tumors. The developed DOX-TAF@FN nanocomplexes may represent an updated multifunctional nanosystem with simple compositions for cooperative MR imaging-guided targeted chemo-/chemodynamic/immune therapy of tumors.

The value of preoperative 18F-FDG PET metabolic and volumetric parameters in predicting microvascular invasion and postoperative recurrence of hepatocellular carcinoma.

BACKGROUND: Microvascular invasion (MVI) is very important in the evaluation of hepatocellular carcinoma (HCC), but diagnosis is determined by postoperative pathology; thus, preoperative noninvasive methods will play an active role. The purpose of the study was to assess the performance of metabolic parameters of preoperative 18F-fluorodeoxyglucose PET/computerized tomography (18F-FDG PET/CT) in the prediction of MVI and postoperative recurrence in primary hepatocellular carcinoma. METHODS: We retrospectively collected 72 patients with HCC who have performed 18F-FDG PET/CT scan before partial hepatectomy between 2016 and 2019. We used both normal liver tissue and inferior vena cava as the reference background and combined with clinicopathological features, 18F-FDG PET/CT metabolic and volumetric indices to predict MVI and postoperative recurrence of primary HCC before surgery. RESULTS: Twenty-one of the 72 patients recurred, in recurrent cases showed higher maximum standard uptake value (SUVmax), TNR (ratio of tumor SUVmax to mean SUV [SUVmean] of the background tissue), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than nonrecurrence cases (P < 0.001). All 18F-FDG PET metabolic and volumetric indices for predicting postoperative HCC recurrence were significant on receiver-operating-characteristic (ROC) curve analyses (P < 0.05). TNRIVC, TNRNL, MTVIVC, MTVNL TLGIVC and TLGNL were significant factors for predicting MVI in HCC (P < 0.05). On multivariate analyses, MVI, SUVmax, TNRIVC, TNRNL, MTVIVC, MTVNL, TLGIVC and TLGNL (P < 0.05) are independent risk factors for predicting postoperative HCC recurrence. TNRIVC is the most relevant PET/CT parameter for predicting MVI in HCC, and MTVIVC is the most valuable for predicting postoperative HCC recurrence. Moreover, the PET/CT parameters are more accurate for prognosis with inferior vena cava as a reference background than with normal liver tissue. CONCLUSION: 18F-FDG PET/CT metabolic and volumetric indices are effective predictors, and could noninvasively provide more comprehensive predictive information on MVI and postoperative recurrence of primary HCC before surgery.

A core-shell Au@Cu2-xSe heterogeneous metal nanocomposite for photoacoustic and computed tomography dual-imaging-guided photothermal boosted chemodynamic therapy.

Chemodynamic therapy (CDT) has aroused extensive attention for conquering cancers because of its high specificity and low invasiveness. Quick generation of hydroxyl radicals (·OH) during CDT could induce more irreparable damage to cancer cells. The generation rate of ·OH could be magnified via the selection of suitable nanocatalysts or under the assistance of exogenous thermal energy from photothermal therapy (PTT). Here, we construct a kind of monodisperse core-shell Au@Cu2-xSe heterogeneous metal nanoparticles (NPs) for PTT boosted CDT synergistic therapy. Due to the localized surface plasmon resonance (LSPR) coupling effect in the core-shell structure, the photothermal conversion efficiency of Au@Cu2-xSe NPs is up to 56.6%. The in situ generated heat from photothermal can then accelerate the Fenton-like reaction at Cu+ sites to produce abundant ·OH, which will induce apoptotic cell death by attacking DNA, contributing to a heat-boosted CDT. Both in vitro and in vivo results showed that after this synergistic therapy, tumors could be remarkably suppressed. Guided by photoacoustic (PA) and computed tomography (CT) imaging, the therapeutic effects were more specified. Our results revealed that PA and CT dual-imaging-guided PTT boosted CDT synergistic therapy based on core-shell Au@Cu2-xSe NPs is an effective cancer treatment strategy.

Engineering a Smart Agent for Enhanced Immunotherapy Effect by Simultaneously Blocking PD-L1 and CTLA-4.

Combinations of immune checkpoint therapies show encouraging results in the treatment of many human cancers. However, the higher costs and greater side effects of such combinations compared with single-agent immunotherapies limit their further applications. In this work, a novel smart agent, KN046@19 F-ZIF-8, is developed to overcome these limitations. KN046 is a novel recombinant humanized PD-L1/CTLA-4 bispecific single-domain antibody-Fc fusion protein, which can bind to both PD-L1 and CTLA-4 effectively. ZIF-8 is a smart delivery system, which can safely and effectively deliver KN406 to a tumor. In vitro and in vivo results demonstrate that the smart agent KN046@19 F-ZIF-8 not only improves the immune response rate of the antibody drug in treatment of tumors but also reduces its toxic side effects, thereby achieving excellent antitumor efficacy. This study provides an engineering strategy for clinical applications of a more effective immunotherapy.

Overcoming T Cell Exhaustion via Immune Checkpoint Modulation with a Dendrimer-Based Hybrid Nanocomplex.

T cell exhaustion, in which dysfunctional T cells are limited in cytokine release and constrained in immune response, leads to immune escape of cancer cells and decreased efficiency of cancer immunotherapy. Direct regulation or blocking of programmed death 1 (PD-1) represents a promising strategy to overcome T cell exhaustion for reinvigorating anticancer immunity. Here, the construction of a 1,3-propanesultone (1,3-PS)-grafted zwitterionic dendrimer-entrapped gold nanoparticle platform chelated with Gd(III) (Gd-Au DENP-PS) for immune checkpoint modulation is reported. The developed Gd-Au DENP-PS possesses good stability, antifouling property, biocompatibility, and dual-mode computed tomography (CT)/magnetic resonance (MR) imaging functions, and allows for efficient packaging and serum-enhanced delivery of PD-1 siRNA to mediate PD-1 gene silencing in T cells in vitro, and also in vivo in a melanoma-bearing mouse model and in healthy aging mice. The dendrimer nanocomplexes or T cell-laden nanocomplexes enable suppression of tumor growth through the generation of significant effector CD8+ and CD4+ T cells, and the tumor immunotherapeutic potency can be further improved by combination with an indoleamine 2,3-dioxygenase inhibitor. This study identifies a new possibility with a functional dendrimer-based nanohybrid platform for dual-mode CT/MR imaging-guided cancer immunotherapy via the regulation of T cell exhaustion.

68Ga-FAPI and 18F-FDG PET/CT in Perineum Extramammary Paget Disease.

ABSTRACT: Extramammary Paget disease is a rare skin intraepithelial adenocarcinoma. Our case presents 68Ga-fibroblast activation protein inhibitor and 18F-FDG PET/CT imaging in a patient with perineum extramammary Paget disease. Compared with 18F-FDG PET/CT, the primary tumor, enlarged pelvic lymph nodes and right maxillofacial lesion showed higher uptake in 68Ga-fibroblast activation protein inhibitor PET/CT.

A pH-responsive photoacoustic imaging probe for tumor pH imaging in vivo based on polyaniline-bovine serum albumin.

Precise pH detection in tumors can guide the design of pH-responsive drugs and theranostic agents to improve treatment efficacy. However, most reported pH-responsive probes are fluorescent probes, for which in vivo application is limited by low probe penetration depth. In this study, a pH-responsive polyaniline-bovine serum albumin (BSA) probe was constructed for precise pH detection in tumors using photoacoustic imaging. The probe can be used to generate high-resolution images of deep biological tissues. The photoacoustic signal of the polyaniline-BSA probe exhibits a clear linear relationship with pH in the range of 5-6.8 both in vitro and in vivo, indicating that the probe is ideal for precise pH detection in most tumors. The polyaniline-BSA probe also exhibits satisfactory biocompatibility, low toxicity, fast response, and good reversibility. This work provides a useful in vivo pH detection probe for developing pH-responsive drugs and theranostic agents.

Diffusion-weighted magnetic resonance imaging reflects activation of signal transducer and activator of transcription 3 during focal cerebral ischemia/reperfusion.

Signal transducer and activator of transcription (STAT) is a unique protein family that binds to DNA, coupled with tyrosine phosphorylation signaling pathways, acting as a transcriptional regulator to mediate a variety of biological effects. Cerebral ischemia and reperfusion can activate STATs signaling pathway, but no studies have confirmed whether STAT activation can be verified by diffusion-weighted magnetic resonance imaging (DWI) in rats after cerebral ischemia/reperfusion. Here, we established a rat model of focal cerebral ischemia injury using the modified Longa method. DWI revealed hyperintensity in parts of the left hemisphere before reperfusion and a low apparent diffusion coefficient. STAT3 protein expression showed no significant change after reperfusion, but phosphorylated STAT3 expression began to increase after 30 minutes of reperfusion and peaked at 24 hours. Pearson correlation analysis showed that STAT3 activation was correlated positively with the relative apparent diffusion coefficient and negatively with the DWI abnormal signal area. These results indicate that DWI is a reliable representation of the infarct area and reflects STAT phosphorylation in rat brain following focal cerebral ischemia/reperfusion.

Prediction of Vascular Invasion Using a 3-Point Scale Computed Tomography Grading System in Pancreatic Ductal Adenocarcinoma: Correlation With Surgery.

OBJECTIVE: The aim of this study was to evaluate the correlation between a 3-point scale multidetector computed tomography (MDCT) grading system and surgical exploration in predicting vascular invasion and resectability in patients with pancreatic ductal adenocarcinoma (PDA). METHODS: Fifty-five patients with surgical and pathologic confirmation of PDA were retrospectively analyzed by 3 radiologists independently. All patients had MDCT examination with multiplanar reformatted images, computed tomography (CT) angiography, and negative-contrast CT cholangiopancreatography (nCTCP). A 3-point scale CT grading system and criteria for unresectability adopting the latest guidelines were used in predicting the correlation between the invasion and resectability of 5 peripancreatic vessels and surgical grade and pathology. RESULTS: Tumor location was correctly identified in all patients including 2 isodense lesions by means of nCTCP. The mean sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MDCT were 92%, 83%, 95%, 78%, and 90%, respectively, in predicting tumor resectability compared with surgery and pathology and with good agreement (κ = 0.72-0.77). A correlation was observed between CT and surgical grade in predicting vascular invasion on a per-vessel basis, and the agreement presented as good to excellent (κ = 0.66-1.00). CONCLUSIONS: A 3-point scale CT grading system is a simple and practical method in predicting peripancreatic vessel invasion and, importantly, correlates with surgical grade and pathology. Axial images combined with multiplanar reformation, nCTCP, and CT angiography can strengthen the comprehensive evaluation of PDA for resectability.

Erythropoietin reduces apoptosis of brain tissue cells in rats after cerebral ischemia/reperfusion injury: a characteristic analysis using magnetic resonance imaging.

Some in vitro experiments have shown that erythropoietin (EPO) increases resistance to apoptosis and facilitates neuronal survival following cerebral ischemia. However, results from in vivo studies are rarely reported. Perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) have been applied successfully to distinguish acute cerebral ischemic necrosis and penumbra in living animals; therefore, we hypothesized that PWI and DWI could be used to provide imaging evidence in vivo for the conclusion that EPO could reduce apoptosis in brain areas injured by cerebral ischemia/reperfusion. To validate this hypothesis, we established a rat model of focal cerebral ischemia/reperfusion injury, and treated with intra-cerebroventricular injection of EPO (5,000 U/kg) 20 minutes before injury. Brain tissue in the ischemic injury zone was sampled using MRI-guided localization. The relative area of abnormal tissue, changes in PWI and DWI in the ischemic injury zone, and the number of apoptotic cells based on TdT-mediated dUTP-biotin nick end-labeling (TUNEL) were assessed. Our findings demonstrate that EPO reduces the relative area of abnormally high signal in PWI and DWI, increases cerebral blood volume, and decreases the number of apoptotic cells positive for TUNEL in the area injured by cerebral ischemia/reperfusion. The experiment provides imaging evidence in vivo for EPO treating cerebral ischemia/reperfusion injury.

Presurgical Evaluation of Pancreatic Cancer: A Comprehensive Imaging Comparison of CT Versus MRI.

OBJECTIVE: The purpose of this study was to compare comprehensive CT and MRI in the presurgical evaluation of pancreatic cancer. MATERIALS AND METHODS: Thirty-eight patients with pathologically proven pancreatic cancer were included in a retrospective study. CT with negative-contrast CT cholangiopancreatography and CT angiography (CTA) (CT image set) versus MRI with MRCP and MR angiography (MRI image set) were analyzed independently by two reviewers for tumor detection, extension, metastasis, vascular invasion, and resectability. These results were compared with the surgical and pathologic findings. RESULTS: The rate of detection of tumors was higher with MRI than with CT but not significantly so (reviewer 1, p = 1.000; reviewer 2, p = 0.500). In the evaluation of vessel involvement, nodal status, and resectability, although CT had higher ROC AUC values than did MRI (reviewer 1, 0.913 vs 0.858, 0.613 vs 0.503, and 0.866 vs 0.774; reviewer 2, 0.879 vs 0.849, 0.640 vs 0.583, and 0.830 vs 0.815), the differences were not statistically significant (p = 0.189 vs 0.494, 0.328 vs 0.244, and 0.193 vs 0.813 for reviewers 1 and 2). In the evaluation of tumor extension and organ metastases in the 38 patients, correct diagnosis of one of two liver metastases was achieved with both image sets, one case of omental and one case of peritoneal seeding were underestimated, and one case of stomach invasion was overestimated. CONCLUSION: MRI and CT had similar performance in the presurgical evaluation of pancreatic cancer.

Differentiation of noncalculous periampullary obstruction: comparison of CT with negative-contrast CT cholangiopancreatography versus MRI with MR cholangiopancreatography.

OBJECTIVES: The purpose of this study was to compare CT with negative-contrast CT cholangiopancreatography (nCTCP) using subvolume minimum intensity projection (MinIP) versus MRI with MRCP in differentiating noncalculous periampullary obstruction. METHODS: Sixty-four patients with clinically proven noncalculous periampullary obstructions who had undergone both MDCT and MR examinations before operation were reviewed retrospectively. Two reviewers independently interpreted the two image sets (the CT with nCTCP set [CT set] vs. the MRI with MRCP set [MRI set]) in differentiating both benign from malignant obstruction and pancreatic head carcinoma (PHC) from non-PHC, and the results were compared to the final clinical records. RESULTS: In this study, no statistically significant differences were observed in the accuracy of differentiating benign from malignant periampullary obstruction (p = 0.754 for reviewer 1 and p = 0.508 for reviewer 2) on the two image sets. The accuracy of differentiating PHC from non-PHC was also statistically insignificant (p = 0.125 for reviewer 1 and p = 1.000 for reviewer 2) on the two image sets. CONCLUSION: The CT set provides a comparable performance to that of the MRI set in differentiating noncalculous periampullary obstruction. KEY POINTS: • nCTCP with subvolume MinIP is a practical tool in evaluating biliary obstruction • Two image sets have a comparable performance in differentiating noncalculous periampullary obstruction • MDCT could serve as an alternative in patients not eligible for MRI.