Digital pathology, deep learning, and cancer: a narrative review.

Background and Objective: Cancer is a leading cause of morbidity and mortality worldwide. The emergence of digital pathology and deep learning technologies signifies a transformative era in healthcare. These technologies can enhance cancer detection, streamline operations, and bolster patient care. A substantial gap exists between the development phase of deep learning models in controlled laboratory environments and their translations into clinical practice. This narrative review evaluates the current landscape of deep learning and digital pathology, analyzing the factors influencing model development and implementation into clinical practice. Methods: We searched multiple databases, including Web of Science, Arxiv, MedRxiv, BioRxiv, Embase, PubMed, DBLP, Google Scholar, IEEE Xplore, Semantic Scholar, and Cochrane, targeting articles on whole slide imaging and deep learning published from 2014 and 2023. Out of 776 articles identified based on inclusion criteria, we selected 36 papers for the analysis. Key Content and Findings: Most articles in this review focus on the in-laboratory phase of deep learning model development, a critical stage in the deep learning lifecycle. Challenges arise during model development and their integration into clinical practice. Notably, lab performance metrics may not always match real-world clinical outcomes. As technology advances and regulations evolve, we expect more clinical trials to bridge this performance gap and validate deep learning models' effectiveness in clinical care. High clinical accuracy is vital for informed decision-making throughout a patient's cancer care. Conclusions: Deep learning technology can enhance cancer detection, clinical workflows, and patient care. Challenges may arise during model development. The deep learning lifecycle involves data preprocessing, model development, and clinical implementation. Achieving health equity requires including diverse patient groups and eliminating bias during implementation. While model development is integral, most articles focus on the pre-deployment phase. Future longitudinal studies are crucial for validating models in real-world settings post-deployment. A collaborative approach among computational pathologists, technologists, industry, and healthcare providers is essential for driving adoption in clinical settings.

Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier.

Background: Immune microenvironment plays a critical role in cancer from onset to relapse. Machine learning (ML) algorithm can facilitate the analysis of lab and clinical data to predict lung cancer recurrence. Prompt detection and intervention are crucial for long-term survival in lung cancer relapse. Our study aimed to evaluate the clinical and genomic prognosticators for lung cancer recurrence by comparing the predictive accuracy of four ML models. Methods: A total of 41 early-stage lung cancer patients who underwent surgery between June 2007 and October 2014 at New York University Langone Medical Center were included (with recurrence, n=16; without recurrence, n=25). All patients had tumor tissue and buffy coat collected at the time of resection. The CIBERSORT algorithm quantified tumor-infiltrating immune cells (TIICs). Protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to unearth potential molecular drivers of tumor progression. The data was split into training (75%) and validation sets (25%). Ensemble linear kernel support vector machine (SVM) ML models were developed using optimized clinical and genomic features to predict tumor recurrence. Results: Activated natural killer (NK) cells, M0 macrophages, and M1 macrophages showed a positive correlation with progression. Conversely, T CD4+ memory resting cells were negatively correlated. In the PPI network, TNF and IL6 emerged as prominent hub genes. Prediction models integrating clinicopathological prognostic factors, tumor gene expression (45 genes), and buffy coat gene expression (47 genes) yielded varying receiver operating characteristic (ROC)-area under the curves (AUCs): 62.7%, 65.4%, and 59.7% in the training set, 58.3%, 83.3%, and 75.0% in the validation set, respectively. Notably, merging gene expression with clinical data in a linear SVM model led to a significant accuracy boost, with an AUC of 92.0% in training and 91.7% in validation. Conclusions: Using ML algorithm, immune gene expression data from tumor tissue and buffy coat may enhance the precision of lung cancer recurrence prediction.

Reading a preoperative CT scan to guide complex abdominal wall reconstructive surgery.

Computed tomography (CT) scanning is the imaging modality of choice when planning the overall management and operative approach to complex abdominal wall hernias. Despite its availability and well-recognised benefits there are no guidelines or recommendations regarding how best to read or report such scans for this application. In this paper we aim to outline an approach to interpreting preoperative CT scans in abdominal wall reconstruction (AWR). This approach breaks up the interpretive process into 4 steps-concentrating on the hernia or hernias, any complicating features of the hernia(s), the surrounding soft tissues and the abdominopelvic cavity as a whole-and was developed as a distillation of the authors' collective experience. We describe the key features that should be looked for at each of the four steps and the rationale for their inclusion.

Development of a dosimeter prototype with machine learning based 3-D dose reconstruction capabilities.

A 3-D dosimeter fills the need for treatment plan and delivery verification required by every modern radiation-therapy method used today. This report summarizes a proof-of-concept study to develop a water-equivalent solid 3-D dosimeter that is based on novel radiation-hard scintillating material. The active material of the prototype dosimeter is a blend of radiation-hard peroxide-cured polysiloxane plastic doped with scintillating agent P-Terphenyl and wavelength-shifter BisMSB. The prototype detector was tested with 6 MV and 10 MV x-ray beams at Ohio State University's Comprehensive Cancer Center. A 3-D dose distribution was successfully reconstructed by a neural network specifically trained for this prototype. This report summarizes the material production procedure, the material's water equivalency investigation, the design of the prototype dosimeter and its beam tests, as well as the details of the utilized machine learning approach and the reconstructed 3-D dose distributions.

A machine learning-based prediction of the micropapillary/solid growth pattern in invasive lung adenocarcinoma with radiomics.

BACKGROUND: Micropapillary/solid (MP/S) growth patterns of lung adenocarcinoma are vital for making clinical decisions regarding surgical intervention. This study aimed to predict the presence of a MP/S component in lung adenocarcinoma using radiomics analysis. METHODS: Between January 2011 and December 2013, patients undergoing curative invasive lung adenocarcinoma resection were included. Using the "PyRadiomics" package, we extracted 90 radiomics features from the preoperative computed tomography (CT) images. Subsequently, four prediction models were built by utilizing conventional machine learning approaches fitting into radiomics analysis: a generalized linear model (GLM), Naïve Bayes, support vector machine (SVM), and random forest classifiers. The models' accuracy was assessed using a receiver operating curve (ROC) analysis, and the models' stability was validated both internally and externally. RESULTS: A total of 268 patients were included as a primary cohort, and 36.6% (98/268) of them had lung adenocarcinoma with an MP/S component. Patients with an MP/S component had a higher rate of lymph node metastasis (18.4% versus 5.3%) and worse recurrence-free and overall survival. Five radiomics features were selected for model building, and in the internal validation, the four models achieved comparable performance of MP/S prediction in terms of area under the curve (AUC): GLM, 0.74 [95% confidence interval (CI): 0.65-0.83]; Naïve Bayes, 0.75 (95% CI: 0.65-0.85); SVM, 0.73 (95% CI: 0.61-0.83); and random forest, 0.72 (95% CI: 0.63-0.81). External validation was performed using a test cohort with 193 patients, and the AUC values were 0.70, 0.72, 0.73, and 0.69 for Naïve Bayes, SVM, random forest, and GLM, respectively. CONCLUSIONS: Radiomics-based machine learning approach is a very strong tool for preoperatively predicting the presence of MP/S growth patterns in lung adenocarcinoma, and can help customize treatment and surveillance strategies.

Automated Lung Cancer Detection Using Artificial Intelligence (AI) Deep Convolutional Neural Networks: A Narrative Literature Review.

Lung cancer is the number one cause of cancer-related deaths in the United States as well as worldwide. Radiologists and physicians experience heavy daily workloads, thus are at high risk for burn-out. To alleviate this burden, this narrative literature review compares the performance of four different artificial intelligence (AI) models in lung nodule cancer detection, as well as their performance to physicians/radiologists reading accuracy. A total of 648 articles were selected by two experienced physicians with over 10 years of experience in the fields of pulmonary critical care, and hospital medicine. The data bases used to search and select the articles are PubMed/MEDLINE, EMBASE, Cochrane library, Google Scholar, Web of science, IEEEXplore, and DBLP. The articles selected range from the years between 2008 and 2019. Four out of 648 articles were selected using the following inclusion criteria: 1) 18-65 years old, 2) CT chest scans, 2) lung nodule, 3) lung cancer, 3) deep learning, 4) ensemble and 5) classic methods. The exclusion criteria used in this narrative review include: 1) age greater than 65 years old, 2) positron emission tomography (PET) hybrid scans, 3) chest X-ray (CXR) and 4) genomics. The model performance outcomes metrics are measured and evaluated in sensitivity, specificity, accuracy, receiver operator characteristic (ROC) curve, and the area under the curve (AUC). This hybrid deep-learning model is a state-of-the-art architecture, with high-performance accuracy and low false-positive results. Future studies, comparing each model accuracy at depth is key. Automated physician-assist systems as this model in this review article help preserve a quality doctor-patient relationship.

The consensus Immunoscore in phase 3 clinical trial (N0147) and impact on patient management decisions.

The consensus Immunoscore is a routine assay quantifying the adaptive immune response within the tumor microenvironment. It has a prognostic value that has been confirmed in a phase 3 clinical trial (NCCTG N0147) in stage III colon cancers. Moreover, results from another phase 3 randomized trial revealed the predictive value of Immunoscore for response to adjuvant chemotherapy duration. These results highlight the clinical utility of Immunoscore. In its latest edition, the World Health Organization classification of Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criterion for colorectal cancer. Within the tumor microenvironment, the immune response provides an important estimate of the risk of recurrence and death in colon cancer. The international validation of the prognostic value of the consensus Immunoscore together with its prognostic value in the N0147 trial and its predictive utility for response to chemotherapy in stage III patients provide valuable information for patient management.

Level of evidence used in recommendations by the National Comprehensive Cancer Network (NCCN) guidelines beyond Food and Drug Administration approvals.

BACKGROUND: A previous analysis of 113 National Comprehensive Cancer Network® (NCCN®) recommendations reported that NCCN frequently recommends beyond Food and Drug Administration (FDA)-approved indications (44 off-label recommendations) and claimed that the evidence for these recommendations was weak. METHODS: In order to determine the strength of the evidence, we carried out an in-depth re-analysis of the 44 off-label recommendations listed in the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). RESULTS: Of the 44 off-label recommendations, 14 were later approved by the FDA and/or are supported by randomized controlled trial (RCT) data. In addition, 13 recommendations were either very minor extrapolations from the FDA label (n = 8) or were actually on-label (n = 5). Of the 17 remaining extrapolations, 8 were for mechanism-based agents applied in rare cancers or subsets with few available treatment options (median response rate = 43%), 7 were based on non-RCT data showing significant efficacy (>50% response rates), and 2 were later removed from the NCCN Guidelines because newer therapies with better activity and/or safety became available. CONCLUSION: Off-label drug use is a frequent component of care for patients with cancer in the United States. Our findings indicate that when the NCCN recommends beyond the FDA-approved indications, the strength of the evidence supporting such recommendations is robust, with a significant subset of these drugs later becoming FDA approved or supported by RCT. Recommendations without RCT data are often for mechanism-based drugs with high response rates in rare cancers or subsets without effective therapies.

Hospital management of colonic perforations complicating ambulatory outpatient colonoscopy via over-the-scope clips or surgery: a case series.

BACKGROUND: Colonoscopy is the standard of care for the diagnosis and treatment of many colonic disorders. Over the past few years, endoscopic closure of colonoscopy-related perforation has become more common. Endoscopic closure of perforation secondary to colonoscopy has been undertaken in patients in the hospital setting and often during the same colonoscopic procedure in which the perforation itself occurred. The aim of our study was to analyze our experience with emergency endoscopic closure of colonoscopy-related perforation with over-the-scope clip (OTSC) technique. METHODS: We report five cases of colonic perforation that occurred during colonoscopy in an outpatient facility remotely located from our hospital and then referred as an emergency to our institution for endoscopic closure. RESULTS: Bowel preparation was reported to be adequate in all cases. Prior to attempting endoscopic closure of colonic perforation, all patients were in stable clinical condition, early broad-spectrum antibiotic coverage was initiated, and a surgical consult was obtained. All patients had sigmoidoscopy and were found to have sigmoid colon perforations. In three cases, the perforations were closed successfully using an OTSC clip device 14 mm type t. Two patients were found to have greater than 4-cm sigmoid perforations with irregular margins, incompatible with OTSC closure, and were referred for emergency surgery. All patients had an uneventful course following either OTSC closure or surgery. CONCLUSIONS: Based on the characteristics of the five cases and a review of the literature, we suggest a practical approach for undertaking closure of colonic perforations occurring during colonoscopy in the outpatient setting, focusing on clinical criteria to determine eligibility of patients for attempted endoscopic closure and outlining required therapeutic and monitoring steps needed to optimize outcomes.

Risk factors for liver Cancer in HIV endemic areas of Western Kenya.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant cancer of the liver and a leading cause of cancer-related mortality worldwide. Human immunodeficiency virus (HIV) has not been known to have a direct causal relationship with HCC despite independently causing inflammation of the liver. However, little is known on risk factors for HCC patients in an HIV endemic area. The objective of this study was to ascertain the risk factors of HCC and its association with HIV infection. METHODS: This was an un-matched case-control study conducted between June 2015 and June 2016 in Kisumu County Referral Hospital, Kenya. The study enrolled 257 patients with HCC cases and 257 controls. A multivariable logistic regression analysis was used to assess the risk factors for HIV and controlling for exploratory variables. Independent t-test was used to compare means. Exposure variable with values < 0.05 were considered to be statistically significant. RESULTS: HCC cases were more likely to be above 35 years old compared to controls (88.3% vs 23.0%), [aOR =51.6, 95% CI (27.8-95.6), P < 0.001)]. HBV infected patients have higher risk of HCC (47.1% vs 30.4%), [aOR = 3.3; 95% CI (1.7-5.0), P < 0.0001)]. HIV positive patients were more likely to have HCC than HIV negative patients (33.5% vs 10.9%), [aOR =4.3, 95% CI (2.2-8.4)), P < 0.001]. Females have lower risk of HCC than males (32.7 vs 23.7) [aOR = 0.2, 95% CI (0.1-0.4), P < 0.001]. The majority of HCC patients were at the time of diagnosis at stages C (35.1%) and D (48.6%) according to the Barcelona Clinic Liver Clinic (BCLC) criteria. CONCLUSION: Liver cancer was more frequent among adults and subjects co-infected with HBV and HIV. Thus, HIV represents an additional risk factor for liver cancer in this Kenyan population. Regular health screening of HIV and HBV infected subjects may significantly improve the early diagnosis and effective therapy of liver cancer.

Diffusion tensor imaging determines three-dimensional architecture of human cervix: a cross-sectional study.

OBJECTIVE: To determine the microarchitecture of the cervix using high-resolution diffusion tensor (DT) magnetic resonance imaging (MRI). DESIGN: Cross-sectional study. SETTING: Leeds, UK. SAMPLE: Women undergoing hysterectomy for benign pathology. METHODS: Ex-vivo DT-MRI measurements were obtained using a 9.4-T Bruker nuclear magnetic resonance (NMR) spectrometer on seven fixed human cervices obtained at hysterectomy. A deterministic fibre-tracking algorithm was used to indirectly visualise underlying fibre organisation. Inter-regional differences in tissue structure were sought using quantitative measurements of diffusion. MAIN OUTCOME MEASURE: The identification of an occlusive structure in the region corresponding to the internal cervical os. RESULTS: Fibre tracking demonstrated two regions: an outer circular and inner longitudinal layer. The total circumferential tract volume (TV) was greatest in the proximal region of the cervix (TV: proximal, 271 ± 198 mm3 ; middle, 186 ± 119 mm3 ; distal, 38 ± 36 mm3 ). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) measurements were significantly different between regions in all samples (P < 0.0005), indicating greater tract density and organisation towards the internal os. CONCLUSION: Fibre tracking infers a system of dense, well-defined, encircling fibres in the proximal region of the cervix, corresponding to the location of the internal os. These findings may provide evidence of specific anatomic microarchitecture within the cervix able to resist intrauterine forces associated with pregnancy. TWEETABLE ABSTRACT: Diffusion-tensor MRI derived tractography identified well-defined encircling fibres at the internal os.

A need to simplify informed consent documents in cancer clinical trials. A position paper of the ARCAD Group.

Background: In respect of the principle of autonomy and the right of self-determination, obtaining an informed consent of potential participants before their inclusion in a study is a fundamental ethical obligation. The variations in national laws, regulations, and cultures contribute to complex informed consent documents for patients participating in clinical trials. Currently, only few ethics committees seem willing to address the complexity and the length of these documents and to request investigators and sponsors to revise them in a way to make them understandable for potential participants. The purpose of this work is to focus on the written information in the informed consent documentation for drug development clinical trials and suggests (i) to distinguish between necessary and not essential information, (ii) to define the optimal format allowing the best legibility of those documents. Methods: The Aide et Recherche en Cancérologie Digestive (ARCAD) Group, an international scientific committee involving oncologists from all over the world, addressed these issues and developed and uniformly accepted a simplified informed consent documentation for future clinical research. Results: A simplified form of informed consent with the leading part of 1200-1800 words containing all of the key information necessary to meet ethical and regulatory requirements and 'relevant supportive information appendix' of 2000-3000 words is provided. Conclusions: This position paper, on the basis of the ARCAD Group experts discussions, proposes our informed consent model and the rationale for its content.

How health-related quality of life assessment should be used in advanced colorectal cancer clinical trials.

Traditionally, the efficacy of cancer treatment in patients with advance or metastatic disease in clinical studies has been studied using overall survival and more recently tumor-based end points such as progression-free survival, measurements of response to treatment. However, these seem not to be the relevant clinical end points in current situation if such end points were no validated as surrogate of overall survival to demonstrate the clinical efficacy. Appropriate, meaningful, primary patient-oriented and patient-reported end points that adequately measure the effects of new therapeutic interventions are then crucial for the advancement of clinical research in metastatic colorectal cancer to complement the results of tumor-based end points. Health-related quality of life (HRQoL) is effectively an evaluation of quality of life and its relationship with health over time. HRQoL includes the patient report at least of the way a disease or its treatment affects its physical, emotional and social well-being. Over the past few years, several phase III trials in a variety of solid cancers have assessed the incremental value of HRQoL in addition to the traditional end points of tumor response and survival results. HRQoL could provide not only complementary clinical data to the primary outcomes, but also more precise predictive and prognostic value. This end point is useful for both clinicians and patients in order to achieve the dogma of precision medicine. The present article examines the use of HRQoL in phase III metastatic colorectal cancer clinical trials, outlines the importance of HRQoL assessment methods, analysis, and results presentation. Moreover, it discusses the relevance of including HRQoL as a primary/co-primary end point to support the progression-free survival results and to assess efficacy of treatment in the advanced disease setting.

Predicted vitamin D status and colon cancer recurrence and mortality in CALGB 89803 (Alliance).

BACKGROUND: Observational studies suggest that higher levels of 25-hydroxyvitamin D3 (25(OH)D) are associated with a reduced risk of colorectal cancer and improved survival of colorectal cancer patients. However, the influence of vitamin D status on cancer recurrence and survival of patients with stage III colon cancer is unknown. PATIENTS AND METHODS: We prospectively examined the influence of post-diagnosis predicted plasma 25(OH)D on outcome among 1016 patients with stage III colon cancer who were enrolled in a National Cancer Institute-sponsored adjuvant therapy trial (CALGB 89803). Predicted 25(OH)D scores were computed using validated regression models. We examined the influence of predicted 25(OH)D scores on cancer recurrence and mortality (disease-free survival; DFS) using Cox proportional hazards. RESULTS: Patients in the highest quintile of predicted 25(OH)D score had an adjusted hazard ratio (HR) for colon cancer recurrence or mortality (DFS) of 0.62 (95% confidence interval [CI], 0.44-0.86), compared with those in the lowest quintile (Ptrend = 0.005). Higher predicted 25(OH)D score was also associated with a significant improvement in recurrence-free survival and overall survival (Ptrend = 0.01 and 0.0004, respectively). The benefit associated with higher predicted 25(OH)D score appeared consistent across predictors of cancer outcome and strata of molecular tumor characteristics, including microsatellite instability and KRAS, BRAF, PIK3CA, and TP53 mutation status. CONCLUSION: Higher predicted 25(OH)D levels after a diagnosis of stage III colon cancer may be associated with decreased recurrence and improved survival. Clinical trials assessing the benefit of vitamin D supplementation in the adjuvant setting are warranted. CLINICALTRIALS.GOV IDENTIFIER: NCT00003835.

ESMO consensus guidelines for the management of patients with metastatic colorectal cancer.

Colorectal cancer (CRC) is one of the most common malignancies in Western countries. Over the last 20 years, and the last decade in particular, the clinical outcome for patients with metastatic CRC (mCRC) has improved greatly due not only to an increase in the number of patients being referred for and undergoing surgical resection of their localised metastatic disease but also to a more strategic approach to the delivery of systemic therapy and an expansion in the use of ablative techniques. This reflects the increase in the number of patients that are being managed within a multidisciplinary team environment and specialist cancer centres, and the emergence over the same time period not only of improved imaging techniques but also prognostic and predictive molecular markers. Treatment decisions for patients with mCRC must be evidence-based. Thus, these ESMO consensus guidelines have been developed based on the current available evidence to provide a series of evidence-based recommendations to assist in the treatment and management of patients with mCRC in this rapidly evolving treatment setting.

Attitudinal barriers to participation in oncology clinical trials: factor analysis and correlates of barriers.

Patient participation in cancer clinical trials is low. Little is known about attitudinal barriers to participation, particularly among patients who may be offered a trial during an imminent initial oncology consult. The aims of the present study were to confirm the presence of proposed subscales of a recently developed cancer clinical trial attitudinal barriers measure, describe the most common cancer clinical trials attitudinal barriers, and evaluate socio-demographic, medical and financial factors associated with attitudinal barriers. A total of 1256 patients completed a survey assessing demographic factors, perceived financial burden, prior trial participation and attitudinal barriers to clinical trials participation. Results of a factor analysis did not confirm the presence of the proposed four attitudinal barriers subscale/factors. Rather, a single factor represented the best fit to the data. The most highly-rated barriers were fear of side-effects, worry about health insurance and efficacy concerns. Results suggested that less educated patients, patients with non-metastatic disease, patients with no previous oncology clinical trial participation, and patients reporting greater perceived financial burden from cancer care were associated with higher barriers. These patients may need extra attention in terms of decisional support. Overall, patients with fewer personal resources (education, financial issues) report more attitudinal barriers and should be targeted for additional decisional support.

Temsirolimus combined with sorafenib in hepatocellular carcinoma: a phase I dose-finding trial with pharmacokinetic and biomarker correlates.

BACKGROUND: Based upon preclinical evidence for improved antitumor activity in combination, this phase I study investigated the maximum-tolerated dose (MTD), safety, activity, pharmacokinetics (PK), and biomarkers of the mammalian target of rapamycin inhibitor, temsirolimus, combined with sorafenib in hepatocellular carcinoma (HCC). PATIENTS AND METHODS: Patients with incurable HCC and Child Pugh score ≤B7 were treated with sorafenib plus temsirolimus by 3 + 3 design. The dose-limiting toxicity (DLT) interval was 28 days. The response was assessed every two cycles. PK of temsirolimus was measured in a cohort at MTD. RESULTS: Twenty-five patients were enrolled. The MTD was temsirolimus 10 mg weekly plus sorafenib 200 mg twice daily. Among 18 patients at MTD, DLT included grade 3 hand-foot skin reaction (HFSR) and grade 3 thrombocytopenia. Grade 3 or 4 related adverse events at MTD included hypophosphatemia (33%), infection (22%), thrombocytopenia (17%), HFSR (11%), and fatigue (11%). With sorafenib, temsirolimus clearance was more rapid (P < 0.05). Two patients (8%) had a confirmed partial response (PR); 15 (60%) had stable disease (SD). Alpha-fetoprotein (AFP) declined ≥50% in 60% assessable patients. CONCLUSION: The MTD of sorafenib plus temsirolimus in HCC was lower than in other tumor types. HCC-specific phase I studies are necessary. The observed efficacy warrants further study.

Impact of epoetin alfa on left ventricular structure, function, and pressure volume relations as assessed by cardiac magnetic resonance: the heart failure preserved ejection fraction (HFPEF) anemia trial.

Anemia, a common comorbidity in older adults with heart failure and a preserved ejection fraction (HFPEF), is associated with worse outcomes. The authors quantified the effect of anemia treatment on left ventricular (LV) structure and function as measured by cardiac magnetic resonance (CMR) imaging. A prospective, randomized single-blind clinical trial (NCT NCT00286182) comparing the safety and efficacy of epoetin alfa vs placebo for 24 weeks in which a subgroup (n=22) had cardiac magnetic resonance imaging (MRI) at baseline and after 3 and 6 months to evaluate changes in cardiac structure and function. Pressure volume (PV) indices were derived from MRI measures of ventricular volume coupled with sphygmomanometer-measured pressure and Doppler estimates of filling pressure. The end-systolic and end-diastolic PV relations and the area between them as a function of end-diastolic pressure, the isovolumic PV area (PVAiso), were calculated. Patients (75±10 years, 64% women) with HFPEF (EF=63%±15%) with an average hemoglobin of 10.3±1.1 gm/dL were treated with epoetin alfa using a dose-adjusted algorithm that increased hemoglobin compared with placebo (P<.0001). As compared with baseline, there were no significant changes in end-diastolic (-7±8 mL vs -3±8 mL, P=.81) or end-systolic (-0.4±2 mL vs -0.7±5 mL, P=.96) volumes at 6-month follow-up between epoetin alfa compared with placebo. LV function as measured based on EF (-1.5%±1.6% vs -2.6%±3.3%, P=.91) and pressure volume indices (PVAiso-EDP at 30 mm Hg, -5071±4308 vs -1662±4140, P=.58) did not differ between epoetin alfa and placebo. Administration of epoetin alfa to older adult patients with HFPEF resulted in a significant increase in hemoglobin, without evident change in LV structure, function, or pressure volume relationships as measured quantitatively using CMR imaging.

The diagnosis and management of gastric cancer: expert discussion and recommendations from the 12th ESMO/World Congress on Gastrointestinal Cancer, Barcelona, 2010.

Well-recognized experts in the field of gastric cancer discussed during the 12th European Society Medical Oncology (ESMO)/World Congress Gastrointestinal Cancer (WCGIC) in Barcelona many important and controversial topics on the diagnosis and management of patients with gastric cancer. This article summarizes the recommendations and expert opinion on gastric cancer. It discusses and reflects on the regional differences in the incidence and care of gastric cancer, the definition of gastro-esophageal junction and its implication for treatment strategies and presents the latest recommendations in the staging and treatment of primary and metastatic gastric cancer. Recognition is given to the need for larger and well-designed clinical trials to answer many open questions.