Registration-based biomarkers for neoadjuvant treatment response of pancreatic cancer via longitudinal image registration.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) frequently presents as hypo- or iso-dense masses with poor contrast delineation from surrounding parenchyma, which decreases reproducibility of manual dimensional measurements obtained during conventional radiographic assessment of treatment response. Longitudinal registration between pre- and post-treatment images may produce imaging biomarkers that more reliably quantify treatment response across serial imaging. Approach: Thirty patients who prospectively underwent a neoadjuvant chemotherapy regimen as part of a clinical trial were retrospectively analyzed in this study. Two image registration methods were applied to quantitatively assess longitudinal changes in tumor volume and tumor burden across the neoadjuvant treatment interval. Longitudinal registration errors of the pancreas were characterized, and registration-based treatment response measures were correlated to overall survival (OS) and recurrence-free survival (RFS) outcomes over 5-year follow-up. Corresponding biomarker assessments via manual tumor segmentation, the standardized response evaluation criteria in solid tumors (RECIST), and pathological examination of post-resection tissue samples were analyzed as clinical comparators. Results: Average target registration errors were 2.56±2.45 mm for a biomechanical image registration algorithm and 4.15±3.63 mm for a diffeomorphic intensity-based algorithm, corresponding to 1-2 times voxel resolution. Cox proportional hazards analysis showed that registration-derived changes in tumor burden were significant predictors of OS and RFS, while none of the alternative comparators, including manual tumor segmentation, RECIST, or pathological variables were associated with consequential hazard ratios. Additional ROC analysis at 1-, 2-, 3-, and 5-year follow-up revealed that registration-derived changes in tumor burden between pre- and post-treatment imaging were better long-term predictors for OS and RFS than the clinical comparators. Conclusions: Volumetric changes measured by longitudinal deformable image registration may yield imaging biomarkers to discriminate neoadjuvant treatment response in ill-defined tumors characteristic of PDAC. Registration-based biomarkers may help to overcome visual limits of radiographic evaluation to improve clinical outcome prediction and inform treatment selection.

Experiences of early graduate medical students working in New York hospitals during the COVID-19 pandemic: a mixed methods study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic presented the world with a sudden need for additional medical professionals. Senior medical students were identified as potential workers and many worldwide graduated early to serve as Junior Physicians in hospitals. The authors sought to identify factors that informed the decision to work, describe experiences in this capacity, and elucidate benefits for trainees. METHODS: The investigators conducted a mixed-methods observational cohort study of early medical graduates eligible to work as Junior Physicians at two New York medical centers in April/May 2020 during an initial surge in COVID-19 hospitalizations. Graduates were surveyed, and a sample of Junior Physicians participated in a focus group. Survey responses of those who worked were compared to those who did not. Focus group responses were transcribed, coded, and thematically analyzed. RESULTS: Fifty-nine graduates completed the study methods and 39 worked as Junior Physicians. Primary reasons for working included duty to help (39 [100%]), financial incentive (32 [82%]), desire to learn about pandemic response (25 [64%]), and educational incentive (24 [62%]). All had direct contact with COVID-19 patients, believed working was beneficial to their medical training, and were glad they worked. None contracted a symptomatic infection while working. Compared with non-Junior Physicians, Junior Physicians reported increased comfort levels in completing medical intern-level actions like transitions of care functions, such as writing transfer notes (P < 0.01), writing discharge orders (P = 0.01), and providing verbal sign out (P = 0.05), and they reported more comfort in managing COVID-19 patients. Sixteen themes emerged from the focus group and were placed into four categories: development of skills, patient care, safety, and wellness. CONCLUSIONS: Senior medical students chose to work as Junior Physicians for both personal and educational reasons. Experiences were beneficial to trainees and can inform future innovations in medical education.

Kankanet: An artificial neural network-based object detection smartphone application and mobile microscope as a point-of-care diagnostic aid for soil-transmitted helminthiases.

BACKGROUND: Endemic areas for soil-transmitted helminthiases often lack the tools and trained personnel necessary for point-of-care diagnosis. This study pilots the use of smartphone microscopy and an artificial neural network-based (ANN) object detection application named Kankanet to address those two needs. METHODOLOGY/PRINCIPAL FINDINGS: A smartphone was equipped with a USB Video Class (UVC) microscope attachment and Kankanet, which was trained to recognize eggs of Ascaris lumbricoides, Trichuris trichiura, and hookworm using a dataset of 2,078 images. It was evaluated for interpretive accuracy based on 185 new images. Fecal samples were processed using Kato-Katz (KK), spontaneous sedimentation technique in tube (SSTT), and Merthiolate-Iodine-Formaldehyde (MIF) techniques. UVC imaging and ANN interpretation of these slides was compared to parasitologist interpretation of standard microscopy.Relative to a gold standard defined as any positive result from parasitologist reading of KK, SSTT, and MIF preparations through standard microscopy, parasitologists reading UVC imaging of SSTT achieved a comparable sensitivity (82.9%) and specificity (97.1%) in A. lumbricoides to standard KK interpretation (97.0% sensitivity, 96.0% specificity). The UVC could not accurately image T. trichiura or hookworm. Though Kankanet interpretation was not quite as sensitive as parasitologist interpretation, it still achieved high sensitivity for A. lumbricoides and hookworm (69.6% and 71.4%, respectively). Kankanet showed high sensitivity for T. trichiura in microscope images (100.0%), but low in UVC images (50.0%). CONCLUSIONS/SIGNIFICANCE: The UVC achieved comparable sensitivity to standard microscopy with only A. lumbricoides. With further improvement of image resolution and magnification, UVC shows promise as a point-of-care imaging tool. In addition to smartphone microscopy, ANN-based object detection can be developed as a diagnostic aid. Though trained with a limited dataset, Kankanet accurately interprets both standard microscope and low-quality UVC images. Kankanet may achieve sensitivity comparable to parasitologists with continued expansion of the image database and improvement of machine learning technology.

Preoperative risk prediction for intraductal papillary mucinous neoplasms by quantitative CT image analysis.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are radiographically identifiable potential precursor lesions of pancreatic adenocarcinoma. While resection is recommended when main duct dilation is present, management of branch duct IPMN (BD-IPMN) remains controversial. This study sought to evaluate whether preoperative quantitative imaging features of BD-IPMNs could distinguish low-risk disease (low- and intermediate-grade dysplasia) from high-risk disease (high-grade dysplasia and invasive carcinoma). METHODS: Patients who underwent resection between 2005 and 2015 with pathologically proven BD-IPMN and a preoperative CT scan were included in the study. Quantitative image features were extracted using texture analysis and a novel quantitative mural nodularity feature developed for the study. Significant features on univariate analysis were combined with clinical variables to build a multivariate prediction model. RESULTS: Within the study group of 103 patients, 76 (74%) had low-risk disease and 27 (26%) had high-risk disease. Quantitative imaging features were prognostic of low-vs. high-risk disease. The model based only on clinical variables achieved an AUC of 0.67 and 0.79 with the addition of quantitative imaging features. CONCLUSION: Quantitative image analysis of BD-IPMNs is a novel method that may enable risk stratification. External validation may provide a reliable non-invasive prognostic tool for clinicians.

CT radiomics to predict high-risk intraductal papillary mucinous neoplasms of the pancreas.

PURPOSE: Intraductal papillary mucinous neoplasms (IPMNs) are radiographically visible precursor lesions of pancreatic cancer. Despite standard criteria for assessing risk, only 18% of cysts are malignant at resection. Thus, a large number of patients undergo unnecessary invasive surgery for benign disease. The ability to identify IPMNs with low or high risk of transforming into invasive cancer would optimize patient selection and improve surgical decision-making. The purpose of this study was to investigate quantitative CT imaging features as markers for objective assessment of IPMN risk. METHODS: This retrospective study analyzed pancreatic cyst and parenchyma regions extracted from CT scans in 103 patients to predict IPMN risk. Patients who underwent resection between 2005 and 2015 with pathologically proven branch duct (BD)-IPMN and a preoperative CT scan were included in the study. Expert pathologists categorized IPMNs as low or high risk following resection as part of routine clinical care. We extracted new radiographically inspired features as well as standard texture features and designed prediction models for the categorization of high- and low-risk IPMNs. Five clinical variables were also combined with imaging features to design prediction models. RESULTS: Using images from 103 patients and tenfold cross-validation technique, the novel radiographically inspired imaging features achieved an area under the receiver operating characteristic curve (AUC) of 0.77, demonstrating their predictive power. The combination of these features with clinical variables obtained the best performance (AUC = 0.81). CONCLUSION: The present study demonstrates that features extracted from pretreatment CT images can predict the risk of IPMN. Development of a preoperative model to discriminate between low-risk and high-risk IPMN will improve surgical decision-making.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

BACKGROUND: Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. METHODS: A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. RESULTS: A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. CONCLUSION: We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers in the United States with a five-year survival rate of 7.2% for all stages. Although surgical resection is the only curative treatment, currently we are unable to differentiate between resectable patients with occult metastatic disease from those with potentially curable disease. Identification of patients with poor prognosis via early classification would help in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant therapy. PDAC ranges in appearance from homogeneously isoattenuating masses to heterogeneously hypovascular tumors on CT images; hence, we hypothesize that heterogeneity reflects underlying differences at the histologic or genetic level and will therefore correlate with patient outcome. We quantify heterogeneity of PDAC with texture analysis to predict 2-year survival. Using fuzzy minimum-redundancy maximum-relevance feature selection and a naive Bayes classifier, the proposed features achieve an area under receiver operating characteristic curve (AUC) of 0.90 and accuracy (Ac) of 82.86% with the leave-one-image-out technique and an AUC of 0.80 and Ac of 75.0% with three-fold cross-validation. We conclude that texture analysis can be used to quantify heterogeneity in CT images to accurately predict 2-year survival in patients with pancreatic cancer. From these data, we infer differences in the biological evolution of pancreatic cancer subtypes measurable in imaging and identify opportunities for optimized patient selection for therapy.

Goal-Directed Fluid Therapy Using Stroke Volume Variation for Resuscitation after Low Central Venous Pressure-Assisted Liver Resection: A Randomized Clinical Trial.

BACKGROUND: The optimal perioperative fluid resuscitation strategy for liver resections remains undefined. Goal-directed therapy (GDT) embodies a number of physiologic strategies to achieve an ideal fluid balance and avoid the consequences of over- or under-resuscitation. STUDY DESIGN: In a prospective randomized trial, patients undergoing liver resection were randomized to GDT using stroke volume variation as an end point or to standard perioperative resuscitation. Primary outcomes measure was 30-day morbidity. RESULTS: Between 2012 and 2014, one hundred and thirty-five patients were randomized (GDT: n = 69; standard perioperative resuscitation: n = 66). Median age was 57 years and 56% were male. Metastatic disease comprised 81% of patients. Overall (35% GDT vs 36% standard perioperative resuscitation; p = 0.86) and grade 3 morbidity (28% GDT vs 18% standard perioperative resuscitation; p = 0.22) were equivalent. Patients in the GDT arm received less intraoperative fluid (mean 2.0 L GDT vs 2.9 L standard perioperative resuscitation; p < 0.001). Perioperative transfusions were required in 4% (6% GDT vs 2% standard perioperative resuscitation; p = 0.37) and boluses in the postanesthesia care unit were administered to 24% (29% GDT vs 20% standard perioperative resuscitation; p = 0.23). Mortality rate was 1% (2 of 135 patients; both in GDT). On multivariable analysis, male sex, age, combined procedures, higher intraoperative fluid volume, and fluid boluses in the postanesthesia care unit were associated with higher 30-day morbidity. CONCLUSIONS: Stroke volume variation-guided GDT is safe in patients undergoing liver resection and led to less intraoperative fluid. Although the incidence of postoperative complications was similar in both arms, lower intraoperative resuscitation volume was independently associated with decreased postoperative morbidity in the entire cohort. Future studies should target extensive resections and identify patients receiving large resuscitation volumes, as this population is more likely to benefit from this technique.

Renal function after low central venous pressure-assisted liver resection: assessment of 2116 cases.

OBJECTIVES: Low central venous pressure (LCVP)-assisted hepatectomy is associated with decreased blood loss and lower transfusion rates. Concerns about its impact on renal function have prevented widespread application. This study was conducted to review the dynamics of renal function after LCVP-assisted hepatectomy. METHODS: A retrospective analysis of a prospective surgical database was carried out. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation. The RIFLE (risk-injury-failure-loss-end-stage) criteria were used to define postoperative biochemical acute kidney injury (bAKI). Occurrences of clinically relevant AKI (cAKI) were identified in the study center postoperative database. RESULTS: During the period 2003-2012, 2116 LCVP-assisted hepatectomies were performed. The median patient age was 61 years [interquartile range (IQR): 51-70 years] and 51% of patients were male. The median number of resected segments was two; resections involved from one to four segments. Median estimated blood loss was 300 ml (IQR: 200-600 ml). Rates of morbidity and 90-day mortality were 21% and 2%, respectively. Low baseline eGFR (<90 ml/min) was seen in 84% of patients; 29% of patients had eGFR of <30 ml/min. Postoperative bAKI was seen in 17% (n = 350) of patients. Biochemical AKI with low eGFR was seen in 336 patients, representing 16% of the whole cohort; 13% of patients had been at risk, 2% experienced injury and 1% experienced failure. Kidney function had normalized at discharge in 159 of these patients. Nine patients (<1%) developed postoperative cAKI. CONCLUSIONS: The majority of patients in the study cohort had low baseline eGFR. Biochemical alterations in eGFR are transient in the vast majority of patients after LCVP-assisted hepatectomy and their clinical impact is limited. The present data suggest that clinically relevant renal dysfunction is a very uncommon event in patients undergoing LCVP-assisted liver resection.