Novice Readers Research Articles

Effectiveness of the Basic Education Remediation Kits on Improving the Reading Skills of Novice Readers

Remediation is crucial for strengthening students’ reading abilities, particularly for novice readers aged six to seven. Basic education practitioners must design intervention approaches that address reading and comprehension educational gaps. In response, this paper analyzed the effectiveness of the Basic Education Remediation Kits (BERKs) in improving the reading skills of struggling novice readers by revealing their reading skill level and revealing significant differences in the pre-test and post-test mean scores. The study employed a Quasi-experimental methodology with One-Group Pre-Test Post-Test Design and used purposive sampling as the sampling technique. The pre-/post-test consisted of two parts: 1) letter sounds and syllables and 2) short story with comprehension questions. The data was analyzed using descriptive statistics and paired samples t-tests to determine significant differences between the assessment results and the effectiveness of the remediation kit used. Findings revealed an increase in the students’ mean scores following kit implementation. The paired samples t-test confirmed a statistically significant difference between pretest and post-test scores, further affirming its effectiveness. The kit assists novice readers, particularly those in the early stages of literacy; nevertheless, its effectiveness varies according to reading level; thus, the use of a single teaching strategy may not be equally beneficial to all students. The long-term impact of the remediation kit may be evaluated considering aspects such as intervention duration, teaching pedagogy, and demographics. A group of participants with the same reading level may be used to further assess its efficacy.

Development and Validation of a Contrast-Enhanced US VI-RADS for Evaluating Muscle Invasion in Bladder Cancer.

Background Contrast-enhanced US (CEUS) can be used preoperatively for evaluating muscle invasion in bladder cancer, which is important for determining appropriate treatment. However, diagnostic criteria for assessing this at CEUS have not been standardized. Purpose To develop and validate a CEUS Vesical Imaging Reporting and Data System (VI-RADS) for evaluating muscle invasion in bladder cancer. Materials and Methods This single-center prospective study consecutively enrolled patients with suspected bladder cancer. Participants underwent transabdominal or intracavity CEUS between July 2021 and May 2023. Participants were divided into a training set and a validation set at a 2:1 ratio based on the chronologic order of enrollment. The training set was used to identify major imaging features to include in CEUS VI-RADS, and the likelihood of muscle invasion per category was determined using a pathologic reference standard. The optimal VI-RADS category cutoff for muscle invasion was determined with use of the maximum Youden index. The validation set was assessed by novice and expert readers and used to validate the diagnostic performance and interreader agreement of the developed system. Results Overall, 126 participants (median age, 64 years [IQR, 57-71 years]; 107 male) and 67 participants (median age, 64 years [IQR, 56-69 years]; 49 male) were included in the training and validation set, respectively. In the training set, the optimal CEUS VI-RADS category cutoff for muscle invasion was VI-RADS 4 or higher (Youden index, 0.77). In the validation set, CEUS VI-RADS achieved good performance for both novice and expert readers (area under the receiver operating characteristic curve, 0.80 [95% CI: 0.70, 0.90] vs 0.88 [95% CI: 0.80, 0.97]; P = .09). The interreader agreement regarding the evaluation of CEUS VI-RADS category was 0.77 (95% CI: 0.65, 0.85) for novice readers, 0.87 (95% CI: 0.79, 0.92) for expert readers, and 0.78 (95% CI: 0.70, 0.84) for all readers. Conclusion The developed CEUS VI-RADS showed good performance and interreader agreement for the assessment of muscle invasion in bladder cancer. Chinese Clinical Trial Registry no. ChiCTR2100049435 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Morrell in this issue.

Cortical cognitive processing during reading captured using functional-near infrared spectroscopy

Neuroimaging studies using functional magnetic resonance imaging (fMRI) have provided unparalleled insights into the fundamental neural mechanisms underlying human cognitive processing, such as high-level linguistic processes during reading. Here, we build upon this prior work to capture sentence reading comprehension outside the MRI scanner using functional near infra-red spectroscopy (fNIRS) in a large sample of participants (n = 82). We observed increased task-related hemodynamic responses in prefrontal and temporal cortical regions during sentence-level reading relative to the control condition (a list of non-words), replicating prior fMRI work on cortical recruitment associated with high-level linguistic processing during reading comprehension. These results lay the groundwork towards developing adaptive systems to support novice readers and language learners by targeting the underlying cognitive processes. This work also contributes to bridging the gap between laboratory findings and more real-world applications in the realm of cognitive neuroscience.

Word recognition thresholds in novice readers: exploring when reading and listening comprehension are comparable

AbstractThis study proposes and identifies two levels of word reading at which good comprehenders can obtain a similar understanding of written and spoken narrative texts: The oral-written matching functional and efficient thresholds. These thresholds are compared with the level of word reading over which a relationship between listening comprehension and reading comprehension is evident (a basic word recognition threshold) and with the level after which better word recognition does not result in improvements in reading comprehension (an upper word recognition threshold). The three first thresholds were calculated in a sample of 344 first to third-grade Spanish students who read and listened to two narrative texts of different difficulty and who were assessed on measures of comprehension and word recognition. Listening and reading comprehension were related when participants accurately read more than 73% of pseudowords in a list (basic word recognition threshold). For participants with good listening comprehension, reading comprehension performance matched listening comprehension once a moderate reading speed of ~ 66 decontextualized words per minute was achieved (oral-written matching functional threshold) or when the rate of reading the text was ~ 140 words per minute (oral-written matching efficient threshold). The value of the oral-written matching efficient threshold was, in this study, similar to the upper word recognition threshold identified by prior research. The thresholds calculated in this study delineate a sequence of increasingly challenges to the developing reader, allowing a nuanced description of the initial stages of reading development.

Latar Belakang Perkembangannya dan Urgensi Memahami Qira’at dalam Al Qur’an

Qira'at is a field that studies how to fulfill the sentences of the Koran and the differences based on a person's origin. While a Muqri' is a person who is skilled in qiroat by narrating it by speaking, a person who is an expert in qiroat and has memorized the Qur'an should not be called a Muqri' if he does not speak sequentially about these matters. However, novice readers, also referred to as al-Qari' al-Mubtadi', are people who can explain one to three of the existing qira'at. Apart from that, the seven letters that comprise the Arabic language are Quraish, Huzail, Saqif, Hawazin, Kinanah, Tamim, and Yemen, each of which contains the meaning of the Al-Qur'an. Umar, Abu Bakr, and the Prophet Muhammad read these seven letters. After that, when Mushab Usman was created, the reading of the Koran only consisted of one letter, namely the Quraysh language. According to Ustam, reading the Qur'an with seven letters was only to eliminate the hardships and hardships that existed in the early days, and the need for it has disappeared. By aggregating and homogenizing the population around one letter or one language, the motivation is strong to eliminate elements that differentiate reading. Usman's friends did not agree with this policy. With this agreement, Ijma' occurred, and Usman had carried out great wisdom by publishing the Usmani Al-Qur'an, which united and reassured the people.

Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience.

To compare the diagnostic performance of three readers using BI-RADS and Kaiser score (KS) based on mass and non-mass enhancement (NME) lesions. A total of 630 lesions, 393 malignant and 237 benign, 458 mass and 172 NME, were analyzed. Three radiologists with 3 years, 6 years, and 13 years of experience made diagnoses. 596 cases had diffusion-weighted imaging, and the apparent diffusion coefficient (ADC) was measured. For lesions with ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 as the modified KS +, and the benefit was assessed. When using BI-RADS, AUC was 0.878, 0.915, and 0.941 for mass, and 0.771, 0.838, 0.902 for NME for Reader-1, 2, and 3, respectively, better for mass than for NME. The diagnostic accuracy of KS was improved compared to BI-RADS for less experienced readers. For Reader-1, AUC was increased from 0.878 to 0.916 for mass (p = 0.005) and from 0.771 to 0.822 for NME (p = 0.124). Based on the cut-off value of BI-RADS ≥ 4B and KS ≥ 5 as malignant, the sensitivity of KS by Readers-1 and -2 was significantly higher for both Mass and NME. When ADC was considered to change to modified KS +, the AUC and the accuracy for all three readers were improved, showing higher specificity with slightly degraded sensitivity. The benefit of KS compared to BI-RADS was most noticeable for the less experienced readers in improving sensitivity. Compared to KS, KS + can improve specificity for all three readers. For NME, the KS and KS + criteria need to be further improved. KS provides an intuitive method for diagnosing lesions on breast MRI. BI-RADS and KS face greater difficulties in evaluating NME compared to mass lesions. Adding ADC to the KS can improve specificity with slightly degraded sensitivity. KS provides an intuitive method for interpreting breast lesions on MRI, most helpful for novice readers. KS, compared to BI-RADS, improved sensitivity in both mass and NME groups for less experienced readers. NME lesions were considered during the development of the KS flowchart, but may need to be better defined.

Perspectives on technology: Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability.

To explore the topic of Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability, including a discussion of major sources, mitigation approaches, and future directions. A narrative review of PI-RADS interobserver variability. PI-RADS was developed in 2012 to set technical standards for prostate magnetic resonance imaging (MRI), reduce interobserver variability at interpretation, and improve diagnostic accuracy in the MRI-directed diagnostic pathway for detection of clinically significant prostate cancer. While PI-RADS has been validated in selected research cohorts with prostate cancer imaging experts, subsequent prospective studies in routine clinical practice demonstrate wide variability in diagnostic performance. Radiologist and biopsy operator experience are the most important contributing drivers of high-quality care among multiple interrelated factors including variability in MRI hardware and technique, image quality, and population and patient-specific factors such as prostate cancer disease prevalence. Iterative improvements in PI-RADS have helped flatten the curve for novice readers and reduce variability. Innovations in image quality reporting, administrative and organisational workflows, and artificial intelligence hold promise in improving variability even further. Continued research into PI-RADS is needed to facilitate benchmark creation, reader certification, and independent accreditation, which are systems-level interventions needed to uphold and maintain high-quality prostate MRI across entire populations.

Жанровые дефиниции в современной читательской литературной критике

The article studies definitions of genre that exist in mass readers’ minds and appear in their book reviews. While readers’ literary criticism and other forms of online-communication per se are now beginning to draw scientific interest, the problem of genre in fiction book reviews written by readers has been underinvestigated. Non-professional literary critics have a rather vague idea of literary genres that often lacks logic and does not comply with traditional hierarchy of genres. Readers try to fit the text they have read into a genre system they understand, but if it does not fit they create or coin a new genre definition that reflects their own understanding of the text, how they define its subject matter and what the text made them think about. In the minds of novice readers genre definition is closely related to the plot and their personal opinion of the book. Genre criteria analysis is often overlooked or seems arbitrary, oftentimes readers use the first genre definition that comes to their minds, i.e. a socially-agreed-upon definition, a convenient definition, a general definition, or a definition that has been widely used lately (for example, in the movie or book advertisements). Using their own reading experience, reviewers create their own reader’s glossary, in which literary movement is intertwined with their own estimation of the book quality, stylistic devices are mixed up with the author’s individual writing style, and reader’s emotional response becomes a genre criterion.

Morphological density and reading comprehension in Hebrew novice readers

Morphological density and reading comprehension in Hebrew novice readers

Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers

Although regional wall motion abnormality (RWMA) detection is foundational to transthoracic echocardiography, current methods are prone to interobserver variability. We aimed to develop a deep learning (DL) model for RWMA assessment and compare it to expert and novice readers. We used 15,746 transthoracic echocardiography studies-including 25,529 apical videos-which were split into training, validation, and test datasets. A convolutional neural network was trained and validated using apical 2-, 3-, and 4-chamber videos to predict the presence of RWMA in 7 regions defined by coronary perfusion territories, using the ground truth derived from clinical transthoracic echocardiography reports. Within the test cohort, DL model accuracy was compared to 6 expert and 3 novice readers using F1 score evaluation, with the ground truth of RWMA defined by expert readers. Significance between the DL model and novices was assessed using the permutation test. Within the test cohort, the DL model accurately identified any RWMA with an area under the curve of 0.96 (0.92-0.98). The mean F1 scores of the experts and the DL model were numerically similar for 6 of 7 regions: anterior (86 vs 84), anterolateral (80 vs 74), inferolateral (83 vs 87), inferoseptal (86 vs 86), apical (88 vs 87), inferior (79 vs 81), and any RWMA (90 vs 94), respectively, while in the anteroseptal region, the F1 score of the DL model was lower than the experts (75 vs 89). Using F1 scores, the DL model outperformed both novices 1 (P=.002) and 2 (P=.02) for the detection of any RWMA. Deep learning provides accurate detection of RWMA, which was comparable to experts and outperformed a majority of novices. Deep learning may improve the efficiency of RWMA assessment and serve as a teaching tool for novices.

Abstract 7386: Multi-plane rectal tumor segmentation on pre-treatment MRI via human-in-the-loop deep learning

Abstract Introduction: Precise segmentation of rectal tumors on pre-treatment MRI is critical for in vivo clinical staging and treatment selection. While automated deep learning models can help alleviate laborious manual annotation, these require significant expertise and time commitment. Towards addressing these issues, we present initial results of an integrated human-in-the-loop refinement learning model for semi-automated segmentation of rectal tumors across multiple acquisition planes (axial, coronal) on pre-treatment MRI scans. Methods: This retrospective study accrued baseline MRI scans from rectal cancer patients at four different institutions. A deep learning (DL) nnUNet tumor segmentation model was first trained on both axial plane and coronal plane T2w MRIs from two institutions, with segregated training and internal validation cohorts based on available radiologist annotations. The DL model outputs tumor delineations on both axial and coronal MRI scans in a separate human-in-the-loop (HITL) optimization cohort. Two rounds of HITL refinement learning were then conducted, where in each round model-generated segmentations were refined by two novice radiology readers. Refined annotations were then used to re-optimize the nnUnet model to yield final tumor segmentations. Model-generated segmentations were evaluated before HITL as well as after each round of HITL against “ground truth” radiologist annotations obtained for an external validation cohort, with performance quantified via dice similarity coefficient (DSC) as well as time taken for human annotation of MRIs. Statistical significance was determined via Wilcoxon rank-sum testing. Results: A total of 381 MRI scans from 231 rectal cancer patients were considered. After one round of HITL refinement, DL-based segmentations yielded the best overall performance on the external validation cohort (N=20, two institutions) for both axial (DSC = 0.76) and coronal scans (DSC=0.75). A second round of HITL refinement did not yield significantly different model performance. By comparison, the pre-HITL DL segmentation model yielded significantly worse performance on both axial (DSC=0.60, p=0.0362) and coronal (DSC=0.62, p=0.0186) MRI scans. HITL refinement for rectal tumor annotation was also found to significantly improve reader efficiency by requiring only 18 minutes/scan compared to manual “ground truth” de novo annotations which took up to 38 minutes/scan (p<0.001). Conclusion: Human-in-the-loop deep learning models can help generate accurate rectal tumor segmentations on pre-treatment MRI scans across both axial and coronal acquisition planes. Improvements to model generalizability, model efficacy, and reader efficiency suggest the potential for HITL-based semi-automated segmentation schemes for other medical imaging tasks. Citation Format: Michael Kong, Thomas DeSilvio, Leo Bao, Brennan Flannery, Benjamin N. Parker, Stephen Tang, Gregory O'Connor, Amit Gupta, Emily Steinhagen, Andrei S. Purysko, Eric L. Marderstein, Aaron Carroll, Marka Crittenden, Michael Gough, Kristina Young, Satish E. Viswanath. Multi-plane rectal tumor segmentation on pre-treatment MRI via human-in-the-loop deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7386.

Herbal- and Dietary-Supplement-Induced Liver Injury: A Review of the Recent Literature

Herbal-induced liver injury (HILI) continues to increase in prevalence each year due to the ongoing popularity of herbal supplements and complementary and alternative medicines. A detailed literature review of case reports and clinical studies published from March 2021 to March 2023 was performed. We discuss the epidemiology and diagnosis of HILI as well as the current and proposed laws and regulations. The 2021 ACG guidelines and 2022 AASLD practice guidelines for the diagnosis and management of drug and herbal-induced liver injury are discussed. We describe updates to previously reported etiologies of HILI such as ayurveda, ashwagandha, turmeric, kratom, green tea extract, and garcinia cambogia. Newly described supplements resulting in HILI, such as tinospora cordifolia, horse chestnut, alkaline water, and more, are described. We discuss newly and previously identified hepatoprotective herbal supplements as they have been reported in the study of animal models and human liver cells. This review suggests the need for ongoing research on the causes and mechanisms of HILI to ensure its proper diagnosis, prevention, and treatment in the future. The goal of this review is to provide novice and expert readers with knowledge regarding the possible etiologies of HILI and a general overview.

INTERNATIONAL CRITERIA EKG COMPARISON STUDY

https://youtu.be/4jm0uzAQNm8 BACKGROUND There has been an evolution of athlete specific Electrocardiogram (EKG) criteria over the years, resulting in improved specificity and lower false positive rates, starting with the European Society of Cardiology 2005 guidelines and most recently with the current 2017 International Recommendations. The consistency of EKG interpretation with the 2017 International Criteria have been compared between various groups, including local and specialized center physicians. Whether novice EKG interpreters (undergraduate/graduate students) can be taught to accurately interpret athletes’ EKGs with the 2017 International Criteria has not been extensively studied. This study seeks to assess the accuracy and variability of novice EKG interpreters, compared to cardiologist interpretations and expert readers. METHODS Three novice EKG interpreters (undergraduate exercise science students) were trained in interpreting EKGs of athletes with the 2017 International Criteria during one semester under the instruction of an expert reader. During an annual high school, sports screening day 1350 EKGs were collected and assigned a corresponding number. The on-site cardiologists evaluated the EKGs in real-time and classified as “normal” or “abnormal” according to the International Criteria. Following the sports physical day, three novice EKG interpreters (students), a cardiologist and a Clinical Exercise Physiology Professor (expert reader) were asked separately to classify the same EKGs as “normal or “abnormal” according to the International Criteria. All readers were blinded to the initial classifications made by the cardiologist during the sports physical event. Information regarding the athlete's age, gender, race/ethnicity, and sport was provided on the EKGs. We assessed the agreement between the cardiologist, expert reader and students in interpreting EKGs using Fleiss' kappa analysis. RESULTS 1350 athlete EKGs (males = 879; females = 471, age (mean + SD) 15.09 + 1.3y) including 37 (2.7%) abnormal cases were reviewed. The inter-rater agreement between novice readers, expert reader, and physicians in classifying an EKG as abnormal was good (k = 0.7, p < .001). CONCLUSION This study demonstrated that novice EKG readers could correctly classify EKGs based on the International Criteria as “normal and abnormal” to identify athletes at high risk of acute cardiovascular events

Precision of four calcified structures for age estimation of Black Carp

AbstractObjectiveBlack Carp Mylopharyngodon piceus is an emerging invasive species in North America with an expanding population in the Mississippi River basin. Current aging methods use a suite of structures for age estimation, and a single structure is needed to minimize processing time, to maximize consistency of age and growth measurements, and to allow for back‐calculation of individual fish length at age.MethodsIn total, 236 Black Carp were collected throughout the year from 2017 to 2019 through incidental captures by commercial fishers and biologists. In a subsample, 119 Black Carp from 429 to 1268 mm total length were compared for the precision of annuli counts by two experienced readers for the two anterior pectoral fin rays, the anterior dorsal fin ray, sectioned vertebrae, and lapilli otoliths based on percent exact agreement (PA), percent agreement within 1 year (PA ± 1), coefficient of variation (CV), and bubble plots. Consensus annuli counts were compared by PA and CV between structures. We applied annuli counts, as opposed to age, as fish were collected during all seasons and structures were examined independently by readers without knowledge of capture date.ResultVertebrae and dorsal rays had the highest PA between readers. Dorsal ray had the lowest CV and higher PA ± 1. Pectoral rays and lapilli otoliths had the lowest PA. Between‐structure consensus annuli counts indicated that pectoral rays and the dorsal ray annuli counts were the most similar (PA >70% and CV <12) and lapilli otoliths were the most dissimilar (PA >35% and CV >24). Reader‐reported confidence was highest for vertebrae, then in decreasing order, dorsal ray, pectoral rays, and lapilli otoliths. Lumens were present in all fin rays with only minor effects observed on annuli counts, aside from the anterior‐most pectoral fin ray, in which lumens obscured the presence of one or more potential annuli in 61% of structures.ConclusionThe dorsal ray had the highest agreement between readers, with agreement with ±1 year at 98%; the structure can be efficiently extracted and processed, and the structure's morphology and growth pattern are conducive to aging older fish. Vertebrae had high agreement between readers, but a systematic pattern of double bands in vertebrae increased the between‐reader variation in older fish as the interannual growth pattern compressed the viewable area; this was identified by readers based on aging criteria and highlights the need for training novice readers. Validation of annual growth in the tested suite of structures is still needed.

Inter-reader variability of imaging biomarkers for therapeutic response in pancreatic ductal adenocarcinoma.

700 Background: Indeterminate borders of pancreatic ductal adenocarcinoma (PDAC) can impair reliability of lesion annotation in imaging assessment of therapeutic response (TR) after neoadjuvant chemotherapy (NAT). Previous work showed that longitudinal image registration algorithms can track treatment-related changes and produce quantitative imaging biomarkers (QIB) for TR that predict overall (OS) and recurrence-free survival (RFS). We compare inter-reader agreements of these biomarkers against conventional RECIST and tumor volume QIB. Methods: N=30 patients enrolled in a Phase II clinical trial comparing outcomes of a NAT regimen were retrospectively analyzed. In baseline and restaging CT, whole pancreas and tumor segmentations and tumor diameters were annotated by 2 expert attending radiologists and 2 novice radiology fellows. For each reader, percent change in tumor diameter (RECIST score), percent change in tumor volume (ΔV), and difference in ratio of tumor burden to pancreas volume (ΔB) were computed as QIB for TR across the NAT interval via two approaches: image registration of the baseline tumor region of interest, and direct segmentation of the PDAC lesion in baseline and restaging images. Inter-reader agreements of RECIST, ΔV, and ΔB QIB from both approaches were compared via concordance correlation coefficient (CCC). Associations with OS and RFS were compared over 5-year follow-up via Harrell’s C-index. Results: Among expert radiologists, RECIST score CCC was 0.77 [95% CI: 0.59-0.88], whereas image registration QIB CCC values were significantly higher (ΔV: 0.95 [0.90-0.98], p=0.002; ΔB: 0.93 [0.86-0.97], p=0.014). ΔV and ΔB QIB measured by direct tumor segmentation had significantly lower CCC than by image registration (p<0.001). Among novice readers, image registration QIB (ΔV: 0.83 [0.67-0.91], ΔB: 0.70 [0.48-0.84]) produced higher agreement than RECIST (0.26 [-0.17-0.61]; p=0.002 and p=0.035), with CCC more similar to expert readers. While image registration QIB did not differ from RECIST in association with RFS, registration-based QIB predicted OS with significantly higher C-index (ΔV: 0.58 [0.56-0.60], p<0.001; ΔB: 0.64 [0.62-0.66], p<0.001) than RECIST (0.50 [0.45-0.55]) among experts. Conclusions: Longitudinal registration of the pancreas yields more consistent QIB for PDAC TR with stronger association to OS outcomes than RECIST. These registration-based QIB aim to advance PDAC management by improving patient-specific discrimination of TR after NAT. [Table: see text]

Liquid Nuclear Magnetic Resonance (NMR) Spectroscopy in Transition—From Structure Elucidation to Multi-Analysis Method

As early as 1946, Felix Bloch and Edward Mills Purcell detected nuclear magnetic resonance signals, earning themselves the Nobel Prize in 1952. The same year saw the launch of the first commercial nuclear magnetic resonance (NMR) spectrometer. Since then, NMR has experienced significant progress in various fields of application. While in the 1970s NMR spectroscopy was solely employed for determining the structure and purity of synthesis products in the chemical field, it gradually gained popularity in the medical field for the investigation and rendering of images of human organs. Since then, the technique has developed significantly in terms of stability, reproducibility, and sensitivity, thereby forming the foundation for high-resolution imaging, the automation or standardization of analytical procedures, and the application of chemometric methods, particularly in relation to identifying food adulteration. This review objectively assesses the current state of implementing liquid NMR in the food, cosmetics, and pharmaceutical industries. Liquid NMR has transitioned from a structural elucidation tool to a widely recognized, multi-analytical method that incorporates multivariate techniques. The illustrations and sources provided aim to enhance novice readers’ understanding of this topic.

Eye Motion Tracking for Medical Image Interpretation Training.

The significance of Eye Motion Tracking in aiding learners in training search patterns, pattern recognition, and efficiently using their gaze in terms of time and scanning distribution has been highlighted in the USAF Pilot Training Next initiative. The innovation described further builds on this concept in the realm of medical imaging and the provision of real-time feedback of eye direction and gaze duration. This real-time indicator enables the trainer to adapt verbal queueing of the trainee in a personalized manner to improve knowledge transfer, and to increase the confidence of the trainer and trainee in the competency of the trainee. The initial experiment data set included bone radiographs, digital subtraction angiograms, and computed tomography images. Preliminary results and formative feedback from participants was encouraging with expert viewers able to use Eye Motion Tracking to successfully guide novice readers through search and gaze protocol patterns of the medical images.

Deep Learning-assisted Diagnosis of Breast Lesions on US Images: A Multivendor, Multicenter Study.

To evaluate the diagnostic performance of a deep learning (DL) model for breast US across four hospitals and assess its value to readers with different levels of experience. In this retrospective study, a dual attention-based convolutional neural network was built and validated to discriminate malignant tumors from benign tumors by using B-mode and color Doppler US images (n = 45 909, March 2011-August 2018), acquired with 42 types of US machines, of 9895 pathologic analysis-confirmed breast lesions in 8797 patients (27 men and 8770 women; mean age, 47 years ± 12 [SD]). With and without assistance from the DL model, three novice readers with less than 5 years of US experience and two experienced readers with 8 and 18 years of US experience, respectively, interpreted 1024 randomly selected lesions. Differences in the areas under the receiver operating characteristic curves (AUCs) were tested using the DeLong test. The DL model using both B-mode and color Doppler US images demonstrated expert-level performance at the lesion level, with an AUC of 0.94 (95% CI: 0.92, 0.95) for the internal set. In external datasets, the AUCs were 0.92 (95% CI: 0.90, 0.94) for hospital 1, 0.91 (95% CI: 0.89, 0.94) for hospital 2, and 0.96 (95% CI: 0.94, 0.98) for hospital 3. DL assistance led to improved AUCs (P < .001) for one experienced and three novice radiologists and improved interobserver agreement. The average false-positive rate was reduced by 7.6% (P = .08). The DL model may help radiologists, especially novice readers, improve accuracy and interobserver agreement of breast tumor diagnosis using US.Keywords: Ultrasound, Breast, Diagnosis, Breast Cancer, Deep Learning, Ultrasonography Supplemental material is available for this article. © RSNA, 2023.

Diacritic priming in novice readers of diacritics.

Recent masked priming studies investigating the recognition of letters with diacritics with native readers of the script have consistently yielded an asymmetric pattern of priming such that a base-letter prime without the diacritic speeds up the recognition of the letter with a diacritic almost as much as an identity prime, but not vice versa (e.g., á-Á ≦ a-Á, but a-A ≪á-A). Here we tested English readers unfamiliar with diacritics in a letter match task using Japanese kana and the vowel letters of the Latin alphabet, and found the asymmetry was reduced to a negligible level (á-Á ≦ a-Á, and a-A ≦ á-A) (Experiments 1 and 2). However, the diacritic novices showed the asymmetric pattern of priming like the diacritic experts when the task condition explicitly required the letters with and without diacritics to be distinguished (Experiments 3 and 4). These results are explained in terms of how expertise moderates an early letter identification process in interpreting a visual feature as noise, or a signal diagnostic of letter identity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Bridging the experience gap in prostate multiparametric magnetic resonance imaging using artificial intelligence: A prospective multi-reader comparison study on inter-reader agreement in PI-RADS v2.1, image quality and reporting time between novice and expert readers

PurposeThe aim of the study was to determine the impact of using a semi-automatic commercially available AI-assisted software (Quantib® Prostate) on inter-reader agreement in PI-RADS scoring at different PI-QUAL ratings and grades of reader confidence and on reporting times among novice readers in multiparametric prostate MRI. MethodsA prospective observational study, with a final cohort of 200 patients undergoing mpMRI scans, was performed at our institution. An expert fellowship-trained urogenital radiologist interpreted all 200 scans based on PI-RADS v2.1. The scans were divided into four equal batches of 50 patients. Four independent readers evaluated each batch with and without the use of AI-assisted software, blinded to expert and individual reports. Dedicated training sessions were held before and after each batch. Image quality rated according to PI-QUAL and reporting times were recorded. Readers’ confidence was also evaluated. A final evaluation of the first batch was conducted at the end of the study to assess for any changes in performance. ResultsThe overall kappa coefficient differences in PI-RADS scoring agreement without and with Quantib® were 0.673 to 0.736 for Reader 1, 0.628 to 0.483 for Reader 2, 0.603 to 0.292 for Reader 3 and 0.586 to 0.613 for Reader 4. Using PI-RADS ≥ 4 as cut-off for biopsy, the AUCs with AI ranged from 0.799 (95 % CI: 0.743, 0.856) to 0.820 (95 % CI: 0.765, 0.874). Inter-reader agreements at different PI-QUAL scores were higher with the use of Quantib, particularly for readers 1 and 4, with Kappa coefficient values showing moderate to slight agreement. ConclusionQuantib® Prostate could potentially be useful in improving inter-reader agreement among less experienced to completely novice readers if used as a supplement to PACS.