Accuracy For Clinical Use Research Articles

Validation of Serum Tetrahydrocannabinol Assay and Its Clinical Application

Abstract Background The widespread use of marijuana across all age groups in the United States, driven by the legalization of recreational and medical cannabis, has underscored the need for accurate measurement of tetrahydrocannabinol (THC) and its metabolites in blood specimens. This requirement spans both legal and medical contexts, prompting the development of precise diagnostic tools. Methods We developed a high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay, utilizing a straightforward protein precipitation extraction method to quantify THC and its metabolites: THC, 11-OH-THC, THC-COOH, cannabidiol (CBD), and THC-COOH glucuronide. The assay was rigorously validated for precision, linearity, stability, carryover, and quality assurance to ensure its reliability and accuracy for clinical use. Results Precision studies demonstrated a coefficient of variation ranging from 1.7% to 4.9%. The analytical measurement range was established at 1-100 ng/mL for THC, CBD, and 11-OH-THC, 5-500 ng/mL for THC-COOH, and 10-1000 ng/mL for THC glucuronide, accommodating the broad spectrum of THC/metabolite concentrations observed in our patient cohort. Carryover from all analytes were negligible (<0.01%). Sample stability was confirmed for up to two weeks at -20°C and through three freeze-thaw cycles. Despite a median THC concentration of 5 ng/mL in a limited sample size (N=44), high concentrations of THC and its metabolites correlated with trauma-related incidents and a history of polysubstance abuse in emergency department admissions. Conclusions The LC-MS/MS assay offers superior sensitivity and specificity compared to traditional immunoassays for cannabinoid detection, effectively distinguishing between THC and its metabolites. Its implementation will offer an advanced approach for analyzing the prevalence and clinical implications of THC and metabolite levels in various patient populations, including trauma, pediatric patients, and organ transplant candidates.

Automatic quantification of scapular and glenoid morphology from CT scans using deep learning

ObjectivesTo develop and validate an open-source deep learning model for automatically quantifying scapular and glenoid morphology using CT images of normal subjects and patients with glenohumeral osteoarthritis. Materials and MethodsFirst, we used deep learning to segment the scapula from CT images and then to identify the location of 13 landmarks on the scapula, 9 of them to establish a coordinate system unaffected by osteoarthritis-related changes, and the remaining 4 landmarks on the glenoid cavity to determine the glenoid size and orientation in this scapular coordinate system. The glenoid version, glenoid inclination, critical shoulder angle, glenopolar angle, glenoid height, and glenoid width were subsequently measured in this coordinate system. A 5-fold cross-validation was performed to evaluate the performance of this approach on 60 normal/non-osteoarthritic and 56 pathological/osteoarthritic scapulae. ResultsThe Dice similarity coefficient between manual and automatic scapular segmentations exceeded 0.97 in both normal and pathological cases. The average error in automatic scapular and glenoid landmark positioning ranged between 1 and 2.5 mm and was comparable between the automatic method and human raters. The automatic method provided acceptable estimates of glenoid version (R2 = 0.95), glenoid inclination (R2 = 0.93), critical shoulder angle (R2 = 0.95), glenopolar angle (R2 = 0.90), glenoid height (R2 = 0.88) and width (R2 = 0.94). However, a significant difference was found for glenoid inclination between manual and automatic measurements (p < 0.001). ConclusionsThis open-source deep learning model enables the automatic quantification of scapular and glenoid morphology from CT scans of patients with glenohumeral osteoarthritis, with sufficient accuracy for clinical use.

High-accuracy noninvasive continuous glucose monitoring using OCT angiography-purified blood scattering signals in human skin.

The accuracy of noninvasive continuous glucose monitoring (CGM) through near-infrared scattering is challenged by mixed scattering signals from different compartments, where glucose has a positive correlation with a blood scattering coefficient but a negative correlation with a tissue scattering coefficient. In this study, we developed a high-accuracy noninvasive CGM based on OCT angiography (OCTA)-purified blood scattering signals. The blood optical scattering coefficient (BOC) was initially extracted from the depth attenuation of backscattered light in OCT and then purified by eliminating the scattering signals from the surrounding tissues under the guidance of a 3D OCTA vascular map in human skin. The purified BOC was used to estimate the optical blood glucose concentration (BGC) through a linear calibration. The optical and reference BGC measurements were highly correlated (R = 0.94) without apparent time delay. The mean absolute relative difference was 6.09%. All optical BGC measurements were within the clinically acceptable Zones A + B, with 96.69% falling in Zone A on Parke's error grids. The blood glucose response during OGTT was mapped with a high spatiotemporal resolution of the single vessel and 5 seconds. This noninvasive OCTA-based CGM shows promising accuracy for clinical use. Future research will involve larger sample sizes and diabetic participants to confirm these preliminary findings.

Paper 45: Which Osteochondritis Dissecans Subjects Will Heal Non-Operatively? An Application of Machine Learning Methods to the ROCK Cohort

Paper 45: Which Osteochondritis Dissecans Subjects Will Heal Non-Operatively? An Application of Machine Learning Methods to the ROCK Cohort

European Society of Hypertension recommendations for the validation of cuffless blood pressure measuring devices: European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability.

There is intense effort to develop cuffless blood pressure (BP) measuring devices, and several are already on the market claiming that they provide accurate measurements. These devices are heterogeneous in measurement principle, intended use, functions, and calibration, and have special accuracy issues requiring different validation than classic cuff BP monitors. To date, there are no generally accepted protocols for their validation to ensure adequate accuracy for clinical use. This statement by the European Society of Hypertension (ESH) Working Group on BP Monitoring and Cardiovascular Variability recommends procedures for validating intermittent cuffless BP devices (providing measurements every >30 sec and usually 30-60 min, or upon user initiation), which are most common. Six validation tests are defined for evaluating different aspects of intermittent cuffless devices: static test (absolute BP accuracy); device position test (hydrostatic pressure effect robustness); treatment test (BP decrease accuracy); awake/asleep test (BP change accuracy); exercise test (BP increase accuracy); and recalibration test (cuff calibration stability over time). Not all these tests are required for a given device. The necessary tests depend on whether the device requires individual user calibration, measures automatically or manually, and takes measurements in more than one position. The validation of cuffless BP devices is complex and needs to be tailored according to their functions and calibration. These ESH recommendations present specific, clinically meaningful, and pragmatic validation procedures for different types of intermittent cuffless devices to ensure that only accurate devices will be used in the evaluation and management of hypertension.

Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer

Gastric cancer is one of the most common malignancies. Although some patients benefit from immunotherapy, the majority of patients have unsatisfactory immunotherapy outcomes, and the clinical significance of immune-related genes in gastric cancer remains unknown. We used the single-sample gene set enrichment analysis (ssGSEA) method to evaluate the immune cell content of gastric cancer patients from TCGA and clustered patients based on immune cell scores. The Weighted Correlation Network Analysis (WGCNA) algorithm was used to identify immune subtype-related genes. The patients in TCGA were randomly divided into test 1 and test 2 in a 1:1 ratio, and a machine learning integration process was used to determine the best prognostic signatures in the total cohort. The signatures were then validated in the test 1 and the test 2 cohort. Based on a literature search, we selected 93 previously published prognostic signatures for gastric cancer and compared them with our prognostic signatures. At the single-cell level, the algorithms "Seurat," "SCEVAN", "scissor", and "Cellchat" were used to demonstrate the cell communication disturbance of high-risk cells. WGCNA and univariate Cox regression analysis identified 52 prognosis-related genes, which were subjected to 98 machine-learning integration processes. A prognostic signature consisting of 24 genes was identified using the StepCox[backward] and Enet[alpha = 0.7] machine learning algorithms. This signature demonstrated the best prognostic performance in the overall, test1 and test2 cohort, and outperformed 93 previously published prognostic signatures. Interaction perturbations in cellular communication of high-risk T cells were identified at the single-cell level, which may promote disease progression in patients with gastric cancer. We developed an immune-related prognostic signature with reliable validity and high accuracy for clinical use for predicting the prognosis of patients with gastric cancer.

3D printing and milling accuracy influence full-contour zirconia crown adaptation.

To correlate trueness and cement-space characteristics of crowns milled chairside and in the laboratory with those of inkjet 3D-printed crowns, and to assess whether 3D-printing accuracy meets the clinical standard. Thirty crowns were either (1) milled using a chairside Cerec MCXL unit from Cerec Zirconia Mono L (Dentsply Sirona), (2) milled using a LX-O 5-axis (Matsuura Machinery) industrial machine from Initial Zirconia HT (GC), or (3) 3D-printed using an inkjet Carmel 1400 (Xjet) printer (n=10). Crown trueness determined by comparing the original CAD with each visible-light digitized crown was correlated with the 3D cement-space characteristics recorded by micro-CT. Statistics involved Kruskal-Wallis testing and Spearman correlation. Crown trueness at the intaglio marginal area positively correlated with the marginal and axial cement-space characteristics. 3D-printing revealed data in-between those of the two milling systems with undercut values being not statistically different from those recorded for chairside milling and a low overcut level that was statistically similar to that obtained by laboratory milling. Laboratory milling revealed a significantly better marginal accuracy with a consequently lower cement-space thickness. A higher overcut level was recorded for the chairside-milled crowns in the marginal/occlusal thirds, resulting in the significantly highest occlusal cement-space thickness and cement-volume percentage with a cement thickness above 120µm (limit considered as clinically acceptable). No statistical difference in trueness was found for the external crown dimensions. The 3D-printed zirconia crowns provided sufficient manufacturing accuracy for clinical use. Accurate milling and printing of the crown's intaglio marginal area is primordial.

Fecal concentration of Rhodococcus equi determined by quantitative polymerase chain reaction of rectal swab samples to differentiate foals with pneumonia from healthy foals.

BackgroundDiagnostic accuracy of real‐time, quantitative PCR (qPCR) assays to quantify virulent Rhodococcus equi using rectal swab samples has not been systematically evaluated.ObjectiveTo evaluate the accuracy of qPCR of rectal swab samples to differentiate foals with pneumonia from healthy foals of similar age from the same environment.AnimalsOne hundred privately owned foals born in 2021 from 2 farms in New York.MethodsAn incident case‐control study design was used. Rectal swabs were collected from all foals diagnosed with R. equi pneumonia at 2 horse‐breeding farms (n = 47). Eligible pneumonia cases (n = 39) were matched by age to up to 2 healthy (n = 53) control foals; rectal swabs were collected from control foals on the day of diagnosis of the index case. DNA was extracted from fecal swabs and the concentration of virulent R. equi (ie, copy numbers of the virulence‐associated protein A gene [vapA] per 100 ng fecal DNA) was estimated by qPCR.ResultsThe area under the ROC curve for qPCR of fecal swabs was 83.7% (95% CI, 74.9‐92.6). At a threshold of 14 883 copies of vapA per 100 ng fecal DNA, specificity of the assay was 83.0% (95% CI, 71.7‐92.4) and sensitivity was 79.5% (95% CI, 66.7‐92.3).Conclusions and Clinical ImportanceAlthough fecal concentrations of virulent R. equi are significantly higher in pneumonic foals than healthy foals of similar age in the same environment, qPCR of rectal swabs as reported here lacks adequate diagnostic accuracy for clinical use.

Updates in hypertension: new trials, targets and ways of measuring blood pressure.

Several recent trials and observational studies have identified critical areas that can help to improve the management and measurement of blood pressure in patients with hypertension. High-quality trial evidence supports intensive SBP lowering to 110-130 mmHg in older patients, potassium- based salt substitution in patients without chronic kidney disease, and chlorthalidone for the management of hypertension in patients with chronic kidney disease. In addition, population-based studies indicate enormous underdiagnosis of primary aldosteronism as well as greater sustained intensification of antihypertensive therapy in older patients by maximizing medication dosage rather than adding new agents. The prevalence of hypertension is stable worldwide, though is generally improving in high-income countries and worsening in low-income countries. Furthermore, although cuffless blood pressure devices have the potential to improve access to blood pressure measurement, they have not yet demonstrated sufficient accuracy for clinical use. Growing evidence supports intensive blood pressure lowering, sodium reduction, targeted antihypertensive treatment and appropriate screening for secondary hypertension to optimize blood pressure control and reduce the risk of target organ damage from hypertension. Future studies are needed to identify ways to improve our ability to implement these findings in routine clinical practice.

The Use of Smartphone Photogrammetry to Digitise Transtibial Sockets: Optimisation of Method and Quantitative Evaluation of Suitability.

The fit of a lower limb prosthetic socket is critical for user comfort and the quality of life of lower limb amputees. Sockets are conventionally produced using hand-crafted patient-based casting techniques. Modern digital techniques offer a host of advantages to the process and ultimately lead to improving the lives of amputees. However, commercially available scanning equipment required is often expensive and proprietary. Smartphone photogrammetry could offer a low cost alternative, but there is no widely accepted imaging technique for prosthetic socket digitisation. Therefore, this paper aims to determine an optimal imaging technique for whole socket photogrammetry and evaluate the resultant scan measurement accuracy. A 3D printed transtibial socket was produced to create digital and physical twins, as reference models. The printed socket was photographed from 360 positions and simplified genetic algorithms were used to design a series of experiments, whereby a collection of photos were processed using Autodesk ReCap. The most fit technique was used to assess accuracy. The accuracy of the socket wall volume, surface area and height were 61.63%, 99.61% and 99.90%, respectively, when compared to the digital reference model. The scanned model had a wall thickness ranging from 2.075 mm at the top to 7.758 mm towards the base of the socket, compared to a consistent thickness of 2.025 mm in the control model. The technique selected did not show sufficient accuracy for clinical application due to the degradation of accuracy nearer to the base of the socket interior. However, using an internal wall thickness estimation, scans may be of sufficient accuracy for clinical use; assuming a uniform wall thickness.

Can deep learning identify normal coronary flow reserve from rubidium myocardial PET perfusion?

Abstract Funding Acknowledgements Type of funding sources: None. Background Impaired vasodilator function is an early manifestation of coronary artery disease (CAD) and may precede angiographic stenosis. Rest and stress myocardial blood flow (MBF) are calculated from dynamic imaging during rest/stress Rubidium (Rb) myocardial PET perfusion. Coronary flow reserve (CFR) equals stress divided by rest MBF. CFR is an independent predictor of cardiac mortality in patients with known or suspected CAD. We evaluated the prediction of CFR from analysis of stress/rest PET images by deep learning (DL) as compared with standard calculation of CFR using supervised learning applied methodology using within a commercial DL training platform. Methods 1036 patients (625 male, 411 female, mean age: 64.3 years old) were studied. Patients underwent Stress/rest Rb PET perfusion, and CFR calculated using MBF software by an expert user. Abnormal CFR was defined as &amp;lt;2.0. The left ventricle myocardium was segmented using standard software. DL was trained using polar distribution of normalized PET uptake at stress and rest, processed stress and rest images were cropped, the stress images were then subtracted from the rest images. DL was trained using 935 subtracted images and tested using the remaining 101 images. DL was trained with supervision to classify images. The image shows examples of subtracted abnormal cases (1a &amp; 1b). Results Using our supervised training methodology, the commercial MBF software platform reported 465 cases as abnormal, with 48 of these were included in the DL test set. The DL platform produced abnormal output classifiers for all the whole test set. DL accurately detected over 70% of abnormal cases. The commercial MBF software reported 571 cases as normal; with 50 of these contributing to the DL test set. DL was accurate in 48.0% of normal cases. Statistical results are shown in the table. Conclusion We have shown the proof of concept that DL algorithms trained with supervision can detect abnormal CFR. Our work shows that further work is needed to develop supervised learning methodology in order to improve accuracy for clinical use. Statistical Results Statistic Value Sensitivity 63.16% Specificity 56.67% + Predictive Value 48.00% - Predictive Value 70.83% Accuracy 59.18% Abstract Figure.

Needle artifact characteristics and insertion accuracy using a 1.2 T open MRI scanner: A phantom study

PurposeTo evaluate the characteristics of needle artifacts and the accuracy of needle insertion using a 1.2 Tesla open magnetic resonance imaging (MRI) system in a phantom. Materials and methodsFirst, the apparent width of the needle on the MRI and the needle tip position error of 16- and 18-gauge MRI-compatible introducer needles and a 17-gauge cryoneedle were examined with different needle angles (0°, 30°, 45°, 60°, and 90°) to the main magnetic field (B0), sequence types (balanced steady-state acquisition with rewound gradient echo [BASG] and T2-weighted fast spin echo [FSE] sequence), and frequency encoding directions. Second, the accuracy of needle insertion was evaluated after 10 MRI fluoroscopy-guided insertions in a phantom. ResultsThe apparent needle widths was larger when the angle of the needle axis relative to B0 was larger. The needles appeared larger on BASG than on T2-weighted FSE images, with the largest apparent widths of 16-, 17-, and 18-gauge needles of 14.3, 11.6, and 11.0mm, respectively. The apparent needle tip position was always more distal than the actual position on BASG images, with the largest longitudinal error of 4.0mm. Meanwhile, the 16- and 18-gauge needle tips appeared more proximal on T2-weighted FSE images with right-to-left frequency encoding direction. The mean accuracy of MRI fluoroscopy-guided needle insertion was 3.1mm. ConclusionThese experiments clarify the characteristics of needle artifacts in a 1.2 Tesla open MRI. With this system, the MRI fluoroscopy-guided needle insertion demonstrated an acceptable accuracy for clinical use.

Experimental verification the electron return effect around spherical air cavities for the MR-Linac using Monte Carlo calculation.

Dose deposition around unplanned air cavities during magnetic resonance-guided radiotherapy (MRgRT) is influenced by the electron return effect (ERE). This is clinically relevant for gas forming close to or inside organs at risk (OARs) that lie in the path of a single beam, for example, intestinal track during pelvic treatment. This work aims to verify Monte Carlo calculations that predict the dosimetric effects of ERE around air cavities. For this, we use GafChromic EBT3 film inside poly-methyl methacrylate (PMMA) -air phantoms. Four PMMA phantoms were produced. Three of the phantoms contained centrally located spherical air cavities (0.5, 3.5, 7.5cm diameter), and one phantom contained no air. The phantoms were split to sandwich GafChromic EBT3 film in the center. The phantoms were irradiated on an Elekta Unity system using a single 10×10cm2 7-MV photon beam under the influence of a 1.5-T transverse magnetic field. The measurements were replicated using the Elekta Monaco treatment planning system (TPS). Gamma analysis with pass criteria 3%/3mm was used to compare the measured and calculated dose distributions. We also consider 3%/2mm, 2%/3mm, and 2%/2mm pass criteria for interest. The gamma analysis showed that >95% of the points agreed between the TPS-calculated and measured dose distributions, using 3%/3mm criteria. The phantom containing the largest air cavity had the lowest agreement, with most of the disagreeing points lying inside the air cavity (dose to air region). The dose effects due to ERE around spherical air cavities are being calculated in the TPS with sufficient accuracy for clinical use.

Development and Clinical Validation of a Multiplex Gene Fusion Assay.

The detection of gene fusion events is important for the diagnosis and management of malignancies. In this study, we describe the validation of a next-generation sequencing assay for multiplex detection of gene fusions. Based on previously described gene fusion events that occur in pediatric oncology, a custom anchored multiplex next-generation sequencing assay was designed to target 93 genes. A total of 24 previously characterized specimens were examined. Twenty specimens had 1 or more previously described fusion events, and 4 specimens were negative for fusion events. The accuracy across specimens was 100% (20 of 20 specimens). The analytical sensitivity and specificity were both 100%. Interday reproducibility for fusion events was 94%; in comparison, intraday reproducibility was 90%. This multiple-gene fusion assay demonstrated appropriate sensitivity, specificity, and accuracy for clinical use. We anticipate that this assay will improve the diagnosis and management of patients with pediatric solid tumors.

Evaluation of the RayStation electron Monte Carlo dose calculation algorithm

The aim of this work was to evaluate the accuracy of the RayStation treatment planning system electron Monte Carlo algorithm against measured data for a range of clinically relevant scenarios. This was done by comparing measured percentage depth dose data (PDD) in water, profiles at oblique incidence and with heterogeneities in the beam path, and output factor data and that generated using the RayStation treatment planning system Monte Carlo VMC++ based calculation algorithm. While electron treatments are widely employed in the radiotherapy setting accurate modelling is challenging (TPS) in the presence of patient being both heterogeneous and nonrectangular. Watertank-based measurements were made on a Varian TrueBeam linear accelerator covering electron beam energies 6 to 18 MeV. These included both normal and oblique incidence, heterogeneous geometries, and irregular shaped cut-outs. The measured geometries were replicated in RayStation and the Monte Carlo dose calculation engine used to generate dosimetric data for comparison against measurement in what were considered clinically relevant settings. Water-based PDDs and profile comparisons showed excellent agreement for all electron beam energies. Profiles measured with oblique beam incidence demonstrated acceptable agreement to the treatment planning system calculations although the correspondence worsened as the angle increased with the planning system overestimating the dose in the shoulder region. Profile measurements under inhomogeneities were generally good. The planning system had a tendency to overestimate dose under the heterogeneity and also demonstrated a broader penumbra than measurement. Of the 170 different output factors calculated in RayStation over the range of electron energies commissioned, 141 were within ± 3% of measured values and 164 within ± 5%. Four of the 6 comparisons beyond 5% were at 18 MeV and all had a cut-out edge within 3 cm of the beam central axis/measurement point. The RayStation implementation of a VMC++ electron Monte Carlo dose calculation algorithm shows good agreement with measured data for a range of scenarios studied and represented sufficient accuracy for clinical use.

Kinetic characterization of Cas9 enzymes.

Bacterial adaptive immune systems employ clustered regularly interspaced short palindromic repeats (CRISPR) along with their CRISPR-associated genes (Cas) to form CRISPR RNA (crRNA)-guided surveillance complexes, which target foreign nucleic acids for destruction. Cas9 is unique in that it is composed of a single polypeptide that utilizes both a crRNA and a trans-activating crRNA (tracrRNA) or a single guide RNA to create double-stranded breaks in sequences complementary to the RNA via the HNH and RuvC nuclease domains. Cas9 has become a revolutionary tool for gene-editing applications. Here, we describe methods for studying the cleavage activities of Cas9. We describe protocols for rapid quench-flow and stopped-flow kinetics and interpretation of the results. The protocols detailed here will be paramount for understanding the mechanistic basis for specificity of this enzyme, especially in efforts to improve accuracy for clinical use.

Clinical Intervention Using NGS-Based Kinase Domain Mutation Testing in CML Patients

Kinase domain (KD) mutations in the BCR-ABL1 gene are associated with resistance to tyrosine kinase inhibitors (TKI) in chronic myeloid leukemia (CML). Next-generation Sequencing (NGS) allows detection of low-level KD mutations (<20% VAF), although the detection of true low level KD mutation can be challenging. We have previously reported an improved single round PCR based NGS method to ensure higher accuracy for clinical use (Kizilors et al. ASH 2015). To implement this improved assay in our routine clinical setting, we obtained ISO 15189 accreditation for NGS based BCR-ABL1 KD mutation detection.We have previously shown the clinical significance of low-level KD mutation by NGS. However our study, along with previous studies, was retrospective. Since August 2014, we have been using NGS-based assay (in replacement of Sanger sequencing) for clinical intervention, allowing us to study the clinical relevance of low level mutations and monitor the kinetics of mutated clones.We herein report the outcome of patients in whom clinical intervention was made based on NGS KD mutation screening and monitoring.We analyzed the outcome of 340 consecutive Chronic Phase CML patients treated with first-line TKI at our institution and within our network (imatinib 235, nilotinib 49, dasatinib 10, unknown 46), of whom 70.42% achieved CCyR with first-line TKI. NGS-based KD mutation testing was done retrospectively until January 2014, and prospectively from that date.Overall, a mutation was found in 41(12.05%) patients at a median time of 14 months (range, diagnosis to 156 months). Twenty five different mutations were identified, including T315I (n=9), M244V (n=8), F317L (n=8) and E255K (n=6). Of 41 patients with mutated clone, 27 were found to have a mutation conferring resistance to the ongoing TKI treatment (defined as ‘clinically relevant’ mutation). In 8 patients, the mutation was sensitive to the TKI treatment received (M244V in 6 patients, M351T in one patient on imatinib and an E255V in one patient on dasatinib), two patients with intermediate resistance to the treatment received (H396R and E355G) and four patients with mutations of unknown clinical significance (Q252R, E450K and E450G). Of the 27 patients with clinically relevant mutations, 8 patients were part of our initial retrospective NGS screening study, of whom 3 had clinical intervention based on Sanger Sequencing results.From August 2014, clinical intervention was made based on KD mutations found by NGS. Eighteen patients had their TKI treatment changed because of mutations found to confer resistance to their ongoing TKI (including 2 with unknown clinical significance), of whom 14 had single mutation (F317L, n=3; T315I, n=2; Y253H, n=1; F359V, n=1; L248V, n=1; G250E, n=1; F311L, n=1; E459G, n=1; E450K, n=1; F359I, n=1; E450G, n=1). Four patients had multiple mutations, including two patients who developed mutations sequentially.Of the 18 patients who had clinical intervention, the first detection of the KD mutation was at a low-level in 13 patients.Response to change of TKI was seen in 12 patients, of whom 11 achieved a stable MR3, and one patient with a 2.2 log reduction in BCR-ABL transcript levels. One patient proceeded to allogeneic HSCT and four patients did not show significant response at last follow up. Finally, one patient had a low level Y253H mutation detected while on nilotinib which initially reduced after TKI change and then subsequently increased while gaining an additional T315I at the time of Blastic Phase transformation. Response to combining chemotherapy and ponatinib was seen with the achievement of sustained MR3 until allogeneic HSCT.Kinetics of mutated clone(s) was monitored post TKI change and all patients who responded experienced a reduction in their clone size. Among 12 patients who responded to TKI change, 3 had multiple mutations. One patient had a low level E255K mutation at 4% at 3 months despite achieving CCyR on nilotinib and subsequently developed an additional T315I mutation after 15 months upon loss of CCyR. This patient achieved a sustained MR3 upon switch to ponatinib with concomitant drop in the T315I clone size.To our knowledge, this is the first report of clinical intervention using NGS based KD mutation detection in the management of CML patients. Our findings suggest that NGS may improve clinical decision-making in these patients. A prospective clinical study using NGS (acronym CALLS) is currently ongoing in the UK. DisclosuresKizilors:Incyte: Honoraria, Research Funding. Harrington:BMS: Research Funding. Pagliuca:Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gentium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Mufti:Celgene: Research Funding. De Lavallade:Incyte: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

Accuracy of Dental Replica Models Using Photopolymer Materials in Additive Manufacturing: In Vitro Three-Dimensional Evaluation.

PurposeTo evaluate the accuracy (trueness and precision) of dental replica models produced by using photopolymer materials in additive manufacturing.Materials and MethodsA complete arch model was scanned using an extraoral scanner (Identica Blue) and established as reference. For the control group, 10 stone models were acquired through the conventional method from the reference model. For the experimental groups, digital data were acquired using an intraoral scanner (CEREC Omnicam), and 10 stereolithographic apparatus (SLA) models and 10 PolyJet models were made. All models were scanned with an extraoral scanner. Three‐dimensional analysis software was used to measure differences between the 3D scanned images in root mean square values. The ISO‐5725‐1 specification was followed to measure trueness and precision between two 3D scanned data. Trueness was calculated by overlapping scanned data with the reference model and precision by performing pairwise intragroup comparisons. Also the ratio of region out of tolerance (> ±50 μm) was measured. One‐way ANOVA and Tukey's post hoc analysis were applied.ResultsThere was no statistically significant difference in trueness between the stone and the SLA models (p > 0.05). Dental replica models using photopolymer materials showed statistically significantly better precision than that of the stone model (p < 0.05). Regarding tolerance, no statistically significant difference was observed between the stone and the SLA models (p > 0.05).ConclusionsAlthough the dental replica models using photopolymer materials did not show better trueness than the conventional stone models, there was no significant difference between the SLA and the stone models. Concerning precision, dental replica models using photopolymer materials presented better results than that of the conventional stone models. In sum, dental replica models using photopolymer materials showed sufficient accuracy for clinical use.

Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 IEEE Trans. Image Process. 19 2444–55, Litjens et al 2014 IEEE Trans. Med. Imaging 33 1083–92, Liu et al 2013 SPIE Medical Imaging (International Society for Optics and Photonics) p 86701G, Moradi et al 2012 J. Magn. Reson. Imaging 35 1403–13, Niaf et al 2014 IEEE Trans. Image Process. 23 979–91, Niaf et al 2012 Phys. Med. Biol. 57 3833, Peng et al 2013a SPIE Medical Imaging (International Society for Optics and Photonics) p 86701H, Peng et al 2013b Radiology 267 787–96, Wang et al 2014 BioMed. Res. Int. 2014). This paper presents an automated method based on multimodal convolutional neural networks (CNNs) for two PCa diagnostic tasks: (1) distinguishing between cancerous and noncancerous tissues and (2) distinguishing between clinically significant (CS) and indolent PCa. Specifically, our multimodal CNNs effectively fuse apparent diffusion coefficients (ADCs) and T2-weighted MP-MRI images (T2WIs). To effectively fuse ADCs and T2WIs we design a new similarity loss function to enforce consistent features being extracted from both ADCs and T2WIs. The similarity loss is combined with the conventional classification loss functions and integrated into the back-propagation procedure of CNN training. The similarity loss enables better fusion results than existing methods as the feature learning processes of both modalities are mutually guided, jointly facilitating CNN to ‘see’ the true visual patterns of PCa. The classification results of multimodal CNNs are further combined with the results based on handcrafted features using a support vector machine classifier. To achieve a satisfactory accuracy for clinical use, we comprehensively investigate three critical factors which could greatly affect the performance of our multimodal CNNs but have not been carefully studied previously. (1) Given limited training data, how can these be augmented in sufficient numbers and variety for fine-tuning deep CNN networks for PCa diagnosis? (2) How can multimodal MP-MRI information be effectively combined in CNNs? (3) What is the impact of different CNN architectures on the accuracy of PCa diagnosis? Experimental results on extensive clinical data from 364 patients with a total of 463 PCa lesions and 450 identified noncancerous image patches demonstrate that our system can achieve a sensitivity of 89.85% and a specificity of 95.83% for distinguishing cancer from noncancerous tissues and a sensitivity of 100% and a specificity of 76.92% for distinguishing indolent PCa from CS PCa. This result is significantly superior to the state-of-the-art method relying on handcrafted features.

Corticospinal excitability predicts antidepressant response to rTMS

Repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (DLPFC) is a treatment option for patients with medication-resistant major depressive disorder (MDD). However, antidepressant response is variable and there are currently no response predictors with sufficient accuracy for clinical use. Here we report on results of an observational open-label study to determine whether the modulatory effect of 10 Hz motor cortex (MC) rTMS is predictive of the antidepressant effect of 10 Hz DLPFC rTMS. Fifty-one medication-resistant MDD patients were enrolled for a 10-day treatment course of DLPFC rTMS and antidepressant response was assessed according to post-treatment reduction of the 17-item Hamilton Rating Scale for Depression score. Prior to treatment, we assessed the modulation of motor evoked potential (MEP) amplitude by MC rTMS. We measured MEP's to single pulse TMS using surface electromyography, before and after MC rTMS, and calculated MEP modulation as the change of mean MEP amplitude after MC rTMS. MEP modulation proved to be a robust predictor of reduction of clinician-rated depression severity following the course of DLPFC rTMS: larger MC rTMS-induced increase of corticospinal excitability anticipated a better antidepressant response. These findings suggest that MC rTMS-induced modulation of corticospinal excitability warrants further evaluation as a potential predictive biomarker of antidepressant response to left DLPFC 10 Hz rTMS, and could inform future developments of rTMS to treat depression.Disclosure of interestThe authors have not supplied their declaration of competing interest.