Tuning range-separated DFT functionals for modeling the peak absorption of MEH-PPV polymer in various solvents
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Halsey-Moore, Corell↗
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Perdeuteration of poly[2-methoxy-5-(2′-ethylhexyloxy)-1,4-phenylenevinylene] (d-MEH-PPV): control of microscopic charge-carrier spin–spin coupling and of magnetic-field effects in optoelectronic devices
Replacing all protons on a polymer by deuterium has a dramatic impact on spin-dependent properties of the material in devices.
Stoltzfus, Dani M.↗
Correlation of the Structure with Performance in MEH-PPV/dPS Thin Films Illuminated during Processing
Thin films containing conjugated polymers have been used in a wide array of optoelectronic devices, and much research has focused on the conformation of the conjugated polymer as a key aspect to tuning the performance of the resulting devices. White light exposure has been studied as a post-processing method to alter the film’s morphology and photoluminescence (PL) in systems composed of poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) and polystyrene (PS). To date, there have been few studies that correlate the changes in the depth profile with the PL performance of MEH-PPV/PS films. This study is designed to address this gap in knowledge. Thin films of MEH-PPV/dPS annealed above the glass transition temperatures (T g ) in an illuminated environment led to lower PL than that found in annealed samples that are not illuminated. However, at higher MEH-PPV loading in the blend film, the extent of variation of PL with illumination diminished. Additionally, time-of-flight secondary ion mass spectrometry and small-angle neutron scattering document the three-dimensional morphology of the films under illumination conditions, which are correlated with the changes in PL. Illumination during annealing compressed MEH-PPV-rich layers in the thin film blends at low loadings of MEH-PPV (below 10 wt %) but resulted in significant in-plane phase separation at higher loadings (above 15 wt %). Both changes increase interchain interactions and lower the PL of the illuminated samples. The changes in the depth profile significantly alter the PL of the films, while the in-plane phase separation affected the optoelectronic properties to a lesser degree. This work, therefore, provides insights into how illumination and film composition can be utilized to predictably alter the structure and optoelectronic performance of conjugated polymer blend films.
36 MATERIALS SCIENCE↗
PPV derivative/ZnO nanorods heterojunction: Fabrication, Characterization and Near-UV light sensor development
Highlights: • We have fabricated a PPV-C6/ZnO NRs heterojunction by a simple and low cost method. • We have studied the structural and optical properties of the heterojunction. • I–V characteristics of EGa-In/Si/PPV-C6/ ZnO NRs /graphite devices were analyzed. • Photoelectrical study shows a potential opportunity for UV light sensor development. - Abstract: Poly(1,4-phenylenevinylene) derivative (PPV-C{sub 6}) based solution was spin-coated onto hydrothermally grown and vertically aligned ZnO nanorods (ZnO NRs).The morphological and the optical properties of the PPV-C{sub 6}/ZnO NRs hybrid heterojunction have been studied and shown a penetration of PPV-C{sub 6}into the interspaces between the ZnO NRs with enhanced excitonic dissociation. The current–voltage characteristics in dark and under 395 nm LED illumination have been analyzed. A short-circuit current J{sub sc} of 4691.42 μA/cm{sup 2}, an open-circuit voltage V{sub oc} of 0.46 V giving rise to a responsivity of about 29.32 mA/W have been obtained for the illuminated graphite/PPV-C6/ZnO NRs/Si/EGa-In structure based near UV light sensor showing an enhanced responsivity by a factor of about 200 compared with bare ZnO NRs based one. We have succeeded in the development of low cost near-UV light sensors by simple low temperature hydrothermal method using eco-friendly, low cost and easily fabricated electrodes.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Colloidal cobalt-doped ZnO nanoparticles by microwave-assisted synthesis and their utilization in thin composite layers with MEH-PPV as an electroluminescent material for polymer light emitting diodes
In this study, Co x Zn 1-x O (x = 0.01, 0.05 and 0.1) nanoparticles were prepared by microwave-assisted polyol method from zinc acetate dihydrate and Co(II) acetylacetonate. The reactions were performed in diethylene glycol (DEG) at 250 °C with the use of oleic acid as a surfactant. Resulting nanoparticle (ca. 10 nm) precipitates were washed with methanol and dried or kept as colloidal solutions redispersed in toluene. Colloidal solutions were mixed with the Poly [2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) polymer to produce thin nanocomposite layers with specific optoelectronic properties. The electronic structure in terms of density of states (DOS) of MEH-PPV and MEH-PPV/nanocomposite layers was investigated by recently proposed energy resolved electrochemical impedance spectroscopy method. The MEH-PPV polymer and its nanocomposites with ZnO or Co x Zn 1-x O nanoparticles were used as thin active layers in polymer light emitting diodes (PLED). The nanocomposite layers exhibited optoelectronic properties which were found to be beneficial as the active layer in PLEDs, exhibiting an order of magnitude enhancement in electroluminescence intensity. Finally, a pronounced effect on the opening bias voltage of final devices with Co x Zn 1-x O nanoparticles was also observed.
36 MATERIALS SCIENCE↗
Side chain dynamics in semiconducting polymer MEH-PPV
We report that the characteristic nanoscale dynamics of the alkyl side groups in the light-emitting polymer poly[2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] have been investigated using quasi-elastic neutron scattering (QENS). The measurements were taken below the polymer's glass transition (T ≤ T g ≃ 353 K), where the main backbone is in a rigid state and does not contribute to the broadening of the QENS signal. An analytical diffusion model consisting of a static term and two dynamical components, characterizing the flexible side groups, provide an excellent fit to the experimental data. The two observed dynamical processes are all localized in character, with no meaningful dependence on temperature. The faster process, with characteristic timescale of ~18 ps at room temperature (RT), can be linked to the average mobility of the terminal protons of the alkyl chain, while the slower process, with characteristic timescale of ~170 ps at RT, to those protons at the other end of the alkyl chain, closest to the backbone. Lastlyl, while the fraction of mobile protons contributing to the QENS signal increases with increasing temperature, the characteristic timescale and confining volume within which the protons are able to move locally depend chiefly on the polymer conformational state.
36 MATERIALS SCIENCE↗
Population-based assessment of the national comprehensive cancer network recommendations for baseline imaging of hepatocellular carcinoma
This analysis aims to evaluate the performance characteristics of alternative baseline imaging thresholds in a cohort of hepatocellular carcinoma (HCC) patients from the Surveillance, Epidemiology, and End Results (SEER) database. HCC patients within the SEER database (2010–2015) who had complete information on clinical T and N stages as well as complete information on metastatic sites were eligible for the current study. Various performance characteristics associated with baseline imaging were investigated, including specificity, sensitivity, positive likelihood ratio (LR), negative LR, number needed to investigate (NNI), negative predictive value (NPV), positive predictive value (PPV), and accuracy. A total of 27,201 HCC patients were included. Based on current recommendations that advocate for the use of cross-sectional chest imaging in all newly diagnosed cases of HCC, these recommendations would yield a PPV of 5.0% for the detection of lung metastases. This would translate to an NNI of 20.0. When T1N0 patients were excluded from routine chest or bone imaging, this resulted in a PPV of 6.8% for the identification of lung metastases and an NNI of 14.7. Likewise, this translated to a PPV of 4.6% for the identification of bone metastases and an NNI of 21.7. Similarly, when patients with T1N0 disease and normal alpha-fetoprotein (AFP) were excluded from routine imaging, this resulted in a PPV of 5.6% for the identification of lung metastases and an NNI of 17.8. Also, this translated to a PPV of 3.8% for the identification of bone metastases and an NNI of 26.3. The current study suggests that the omission of routine baseline chest imaging may be considered in selected patients with asymptomatic early-stage HCC and normal AFP.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Stability of Fe-bearing hydrous phases and element partitioning in the system MgO–Al 2 O 3 –Fe 2 O 3 –SiO 2 –H 2 O in Earth’s lowermost mantle
We performed high pressure–temperature ( P-T ) experiments on a model composition of hydrous subducted slabs in the MgO–Al 2 O 3 –Fe 2 O 3 –SiO 2 –H 2 O system using laser-heated diamond anvil cells. The phase assemblages were characterized combining in-situ synchrotron X-ray diffraction and ex-situ transmission electron microscope techniques. The hydrous δ-phase AlOOH–FeOOH–MgSiO 2 (OH) 2 –SiO 2 coexists with bridgmanite (Bdg), post-perovskite (pPv), or both in a broad P-T range of 104–126 GPa and 1750–2500 K. The hydrous pyrite-type FeOOHx phase was observed in-situ over a P-T range of 112–123 GPa and 1750–2300 K, coexisting with the pPv phase. Chemical analysis on recovered samples showed that considerable amount of Fe 2 O 2 (OH) 2 (8–13 mol%) and SiO 2 (9–13 mol%) in the δ-phase does not reduce its thermal stability compared to the Al-endmember, indicating that the Fe-bearing δ-phase can transport water to the lowermost mantle along the mantle geotherm. In this hydrous system, we observed that Al depletion in both the Bdg and pPv phases can significantly reduce the width of the Bdg to pPv transition in contrast to a wide two-phase coexistence region in a dry Al-rich system. Meanwhile, the Fe enrichment in the pPv phase relative to the coexisting Bdg phase lowers the transition pressure to the depth of the D" discontinuity. Accordingly, the depth and thickness of the Bdg to pPv transition in subducted basaltic crustal materials can explain the seismically detected D" discontinuity. Partial melting could be triggered by dehydration of the Fe-bearing hydrous phases due to a steep temperature gradient at the core mantle boundary (CMB), and therefore the ultralow-velocity zones (ULVZs) might be the regions where partial melting occurs at the lowermost mantle.
58 GEOSCIENCES↗
A systematic review of validated suicide outcome classification in observational studies
Abstract Background Suicidal outcomes, including ideation, attempt, and completed suicide, are an important drug safety issue, though few epidemiological studies address the accuracy of suicidal outcome ascertainment. Our primary objective was to evaluate validated methods for suicidal outcome classification in electronic health care database studies. Methods We performed a systematic review of PubMed and EMBASE to identify studies that validated methods for suicidal outcome classification published 1 January 1990 to 15 March 2016. Abstracts and full texts were screened by two reviewers using prespecified criteria. Sensitivity, specificity, and predictive value for suicidal outcomes were extracted by two reviewers. Methods followed PRISMA-P guidelines, PROSPERO Protocol: 2016: CRD42016042794. Results We identified 2202 citations, of which 34 validated the accuracy of measuring suicidal outcomes using International Classification of Diseases (ICD) codes or algorithms, chart review or vital records. ICD E-codes (E950-9) for suicide attempt had 2–19% sensitivity, and 83–100% positive predictive value (PPV). ICD algorithms that included events with ‘uncertain’ intent had 4–70% PPV. The three best-performing algorithms had 74–92% PPV, with improved sensitivity compared with E-codes. Read code algorithms had 14–68% sensitivity and 0–56% PPV. Studies estimated 19–80% sensitivity for chart review, and 41–97% sensitivity and 100% PPV for vital records. Conclusions Pharmacoepidemiological studies measuring suicidal outcomes often use methodologies with poor sensitivity or predictive value or both, which may result in underestimation of associations between drugs and suicidal behaviour. Studies should validate outcomes or use a previously validated algorithm with high PPV and acceptable sensitivity in an appropriate population and data source.
Swain, Richard S.↗
Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT
Purpose: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses. Methods: With institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution’s pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes. Results: We analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8–14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0–13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%. Conclusions: The best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Diagnostic performance of magnetic resonance cholangiopancreatography (MRCP) versus endoscopic retrograde cholangiopancreatography (ERCP) in the pediatric population: a clinical effectiveness study
Purpose: To determine the diagnostic performance of magnetic resonance cholangiopancreatography (MRCP) for detecting biliary and pancreatic abnormalities in a pediatric population, using endoscopic retrograde cholangiopancreatography (ERCP) as the reference standard. Materials and methods: Institutional review board approval with a waiver of informed consent was obtained for this retrospective investigation. Records from the Cincinnati Children’s Hospital Medical Center, Division of Gastroenterology and Department of Radiology were used to identify patients aged ≤ 18 years who had undergone both ERCP and MRCP within a 4-week interval between January 2013 and May 2017. Biliary and pancreatic duct findings were documented for each modality to determine the diagnostic performance of MRCP (with 95% confidence intervals), using ERCP as the reference standard. Results: 54 patients met inclusion criteria. Mean patient age at time of ERCP was 10.4 ± 4.9 years, and 25 (46%) were male. Mean interval between ERCP and MRCP was 11.2 ± 9.7 days. For detection of any abnormality (n = 99 ERCP findings), MRCP had a sensitivity of 76.8% (67.5–84.0%) and a positive predictive value (PPV) of 81.7% (72.7–88.3%). MRCP was 75.7% (59.9–86.6%) sensitive, with a PPV of 84.9% (69.1–93.4%) for biliary findings (n = 37) and 73.5% (59.7–83.8%) sensitive, with a PPV of 78.3% (64.4–87.7%) for pancreatic findings (n = 49). For pancreatobiliary abnormalities (n = 13), MRCP had a sensitivity of 92.3% (66.7–99.6%) and a PPV of 85.7% (60.1–97.5%). Conclusion: In clinical practice, MRCP is moderately sensitive for biliary and pancreatic abnormalities, with false-negative and false-positive examinations being relatively common.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Possibility to Use Hydrothermally Synthesized CuFeS{sub 2} Nanocomposite as an Acceptor in Hybrid Solar Cell
Here we have approached the plausible use of CuFeS{sub 2} nanocomposite as an acceptor in organic–inorganic hybrid solar cell. To produce CuFeS{sub 2} nanocomposite, hydrothermal strategy was employed. The room-temperature XRD pattern approves the synthesized material as CuFeS{sub 2} with no phase impurity (JCPDS Card no: 37-0471). The elemental composition of the material was analyzed from the TEM-EDX data. The obtained selected area electron diffraction (SAED) planes harmonized with the XRD pattern of the synthesized product. Optical band gap (4.14 eV) of the composite from UV–Vis analysis depicts that the synthesized material is belonging to wide band gap semiconductor family. The HOMO (− 6.97 eV) and LUMO (− 2.93 eV) positions from electrochemical study reveal that there is a possibility of electron transfer from MEH-PPV to CuFeS{sub 2}. The optical absorption and photoluminescence spectra of MEH-PPV:CuFeS{sub 2} (donor:acceptor) composite were recorded sequentially by varying weight ratios. The monotonic blue shifting of the absorption peak position indicated the interaction between donor and acceptor materials. The possibility of electron transfer from donor (MEH-PPV) to acceptor (CuFeS{sub 2}) was approved with photoluminescence analysis. Subsequently, we have fabricated a hybrid solar cell by incorporating CuFeS{sub 2} nanocomposite with MEH-PPV in open atmosphere and obtained 0.3% power conversion efficiency.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Uniform two-dimensional square assemblies from conjugated block copolymers driven by π–π interactions with controllable sizes
Two-dimensional (2-D) micro- and nano- architectures are attractive because of their unique properties caused by their ultrathin and flat morphologies. However, the formation of 2-D supramolecular highly symmetrical structures with considerable control is still a major challenge. Here, we presented a simple approach for the preparation of regular and homogeneous 2-D fluorescent square noncrystallization micelles with conjugated diblock copolymers PPV 12 -b-P2VP n through a process of dissolving-cooling-aging. The scale of the formed micelles could be controlled by the ratio of PPV/P2VP blocks and the concentration of the solution. The forming process of the platelet square micelles was analyzed by UV-Vis, DLS and SLS, while the molecular arrangement was characterized by GIXD. The results revealed that the micelles of PPV 12 -b-P2VP n initially form 1-D structures and then grow into 2-D structures in solution, and the growth is driven by intermolecular π-π interactions with the PPV 12 blocks. The formation of 2-D square micelles is induced by herringbone arrangement of the molecules, which is closely related to the presence of the branched alkyl chains attached to conjugated PPV 12 cores.
36 MATERIALS SCIENCE↗
Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters
Purpose: To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI). Materials and methods: Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D{sub t}), pseudo-diffusion (D{sub p}), perfusion fraction (f{sub p})] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed. Results: Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D{sub p} and mean value of VARPRO D{sub p} pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D{sub p} mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment). Conclusion: SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F{sub p} mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Seismic anisotropy, dominant slip systems and phase transitions in the lowermost mantle
SUMMARY The presence of seismic anisotropy at the base of the Earth's mantle is well established, but there is no consensus on the deformation mechanisms in lower mantle minerals that could explain it. Strong anisotropy in magnesium post-perovskite (pPv) has been invoked, but different studies disagree on the dominant slip systems at play. Here, we aim to further constrain this by implementing the most recent results from atomistic models and high-pressure deformation experiments, coupled with a realistic composition and a 3-D geodynamic model, to compare the resulting deformation-induced anisotropy with seismic observations of the lowermost mantle. We account for forward and reverse phase transitions from bridgmanite (Pv) to pPv. We find that pPv with either dominant (001) or (010) slip can both explain the seismically observed anisotropy in colder regions where downwellings turn to horizontal flow, but only a model with dominant (001) slip matches seismic observations at the root of hotter large-scale upwellings. Allowing for partial melt does not change these conclusions, while it significantly increases the strength of anisotropy and reduces shear and compressional velocities at the base of upwellings.
58 GEOSCIENCES↗
Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide–MHC Binding Predictions
The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell–based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., Kd < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell–based vaccines.
60 APPLIED LIFE SCIENCES↗
Assessment of PI-RADS v2 categories ≥ 3 for diagnosis of clinically significant prostate cancer
Purpose: To assess the diagnostic accuracy of PI-RADS v2 categories ≥ 3 to detect clinically significant prostate cancer (csPCa) against histopathology of Transperineal Mapping Biopsy (TPMB). Materials and methods: IRB-approved retrospective cohort study included 47 men who had 3.0 T multi-parametric MRI (mpMRI) and TPMB of prostate. Two radiologists independently evaluated T2, DWI, ADC map, and DCE images using PI-RADS v2 categories. A third radiologist served as tie-breaker. PI-RADS v2 score (PS) ≥ 3 lesions were correlated with 3D model of TPMB (3DTPMB) results based on prostate sectors. Two groups of csPCa status were separately analyzed for accuracy measures at lesion and person levels: Group 1 with GS (Gleason Score) ≥ 7 and group 2 with tumor volume ≥ 0.5 cc. Inter-rater reliability for PS and MR lexicon was calculated. Results: Forty-seven patients with 3DTPMB had at least one lesion with PS ≥ 3 on mpMRI. PS of 5 had high PPV and high specificity of 100% at the lesion and person levels. Sensitivity of a PS ≥ 3 was 68.27% for group 1 and was 48.39% for group 2. Specificity was 93.56% for group 1 and was 95.53% for group 2. At the person level, sensitivity of PS ≥ 3 was 81.25% for group 1 and was 82.35% for group 2. Specificity was 32.26% for group 1 and was 53.85% for group 2. Conclusion: PI-RADS v2 category of 5 had high PPV and specificity; however, combined PS ≥ 3 had mixed performance in detection of csPCa.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Morphological predictors for lymph node metastases on computed tomography in colon cancer
Introduction/Background: The aim of the study was to assess morphological predictors for lymph node metastases (Stage III disease) in colon cancer on computed tomography. Methods and materials: Ninety-four patients with histology-proven colon cancer (adenocarcinoma) who underwent elective primary curative resection between the years 2012 and 2014 were included. Contrast-enhanced CT examinations were independently reviewed by two blinded observers regarding tumor location, depth of tumor invasion, and presence of lymph node metastases. Ocular presence of internal heterogeneity and presence of irregular outer border were used as morphological criteria for lymph node involvement. Protocol-based histopathology after curative surgery served as reference standard. Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values, and accuracy for each morphological criterion for prediction of stage III disease were calculated. Inter-observer agreement was compared using Kappa statistics. Results: According to histopathology, 59 patients were staged as I–II disease and 35 patients were staged as stage III disease. The presence of internal heterogeneity in a lymph node on CT resulted in moderate sensitivity (66–77%) but high specificity (95–95%) for prediction of Stage III disease by both observers. The presence of irregular outer border also resulted in poor sensitivity (49–54%) but high specificity (97–97%). The combination of either internal heterogeneity and/or irregular outer border per patient resulted in a moderate sensitivity (67–77%) and high specificity (95–95%), PPV (89–96%), and NPV (84–88%). Inter-observer agreement (Cohens Kappa) was 0.72. Consensus reading for the combined criteria resulted in sensitivity and specificity of 69% and 100%, respectively. Conclusion: Using morphological criteria for lymph node metastases on CT examination in patients with colon cancer results in high specificity but moderate sensitivity in predicting stage III disease.
62 RADIOLOGY AND NUCLEAR MEDICINE↗