Pricing and cost-saving potential for deep-learning computer-aided lung nodule detection software in CT lung cancer screening

OBJECTIVE: An increasing number of commercial deep learning computer-aided detection (DL-CAD) systems are available but their cost-saving potential is largely unknown. This study aimed to gain insight into appropriate pricing for DL-CAD in different reading modes to be cost-saving and to determine the potentially most cost-effective reading mode for lung cancer screening.METHODS: In three representative settings, DL-CAD was evaluated as a concurrent, pre-screening, and second reader. Scoping review was performed to estimate radiologist reading time with and without DL-CAD. Hourly cost of radiologist time was collected for the USA (€196), UK (€127), and Poland (€45), and monetary equivalence of saved time was calculated. The minimum number of screening CTs to reach break-even was calculated for one-time investment of €51,616 for DL-CAD.RESULTS: Mean reading time was 162 (95% CI: 111-212) seconds per case without DL-CAD, which decreased by 77 (95% CI: 47-107) and 104 (95% CI: 71-136) seconds for DL-CAD as concurrent and pre-screening reader, respectively, and increased by 33-41 s for DL-CAD as second reader. This translates into €1.0-4.3 per-case cost for concurrent reading and €0.8-5.7 for pre-screening reading in the USA, UK, and Poland. To achieve break-even with a one-time investment, the minimum number of CT scans was 12,300-53,600 for concurrent reader, and 9400-65,000 for pre-screening reader in the three countries.CONCLUSIONS: Given current pricing, DL-CAD must be priced substantially below €6 in a pay-per-case setting or used in a high-workload environment to reach break-even in lung cancer screening. DL-CAD as pre-screening reader shows the largest potential to be cost-saving.CRITICAL RELEVANCE STATEMENT: Deep-learning computer-aided lung nodule detection (DL-CAD) software must be priced substantially below 6 euro in a pay-per-case setting or must be used in high-workload environments with one-time investment in order to achieve break-even. DL-CAD as a pre-screening reader has the greatest cost savings potential.KEY POINTS: • DL-CAD must be substantially below €6 in a pay-per-case setting to reach break-even. • DL-CAD must be used in a high-workload screening environment to achieve break-even. • DL-CAD as a pre-screening reader shows the largest potential to be cost-saving.</p

Quantitative imaging:systematic review of perfusion/flow phantoms

Background: We aimed at reviewing design and realisation of perfusion/flow phantoms for validating quantitative perfusion imaging (PI) applications to encourage best practices. Methods: A systematic search was performed on the Scopus database for “perfusion”, “flow”, and “phantom”, limited to articles written in English published between January 1999 and December 2018. Information on phantom design, used PI and phantom applications was extracted. Results: Of 463 retrieved articles, 397 were rejected after abstract screening and 32 after full-text reading. The 37 accepted articles resulted to address PI simulation in brain (n = 11), myocardial (n = 8), liver (n = 2), tumour (n = 1), finger (n = 1), and non-specific tissue (n = 14), with diverse modalities: ultrasound (n = 11), computed tomography (n = 11), magnetic resonance imaging (n = 17), and positron emission tomography (n = 2). Three phantom designs were described: basic (n = 6), aligned capillary (n = 22), and tissue-filled (n = 12). Microvasculature and tissue perfusion were combined in one compartment (n = 23) or in two separated compartments (n = 17). With the only exception of one study, inter-compartmental fluid exchange could not be controlled. Nine studies compared phantom results with human or animal perfusion data. Only one commercially available perfusion phantom was identified. Conclusion: We provided insights into contemporary phantom approaches to PI, which can be used for ground truth evaluation of quantitative PI applications. Investigators are recommended to verify and validate whether assumptions underlying PI phantom modelling are justified for their intended phantom application

Determinants of Population-Based Cancer Screening Performance at Primary Healthcare Institutions in China

BACKGROUND: For a decade, most population-based cancer screenings in China are performed by primary healthcare institutions. To assess the determinants of performance of primary healthcare institutions in population-based breast, cervical, and colorectal cancer screening in China. METHODS: A total of 262 primary healthcare institutions in Tianjin participated in a survey on cancer screening. The survey consisted of questions on screening tests, the number of staff members and training, the introduction of the screening programs to residents, the invitation of residents, and the number of performed screenings per year. Logistic regression models were used to analyze the determinants of performance of an institution to fulfil the target number of screenings. RESULTS: In 58% and 61% of the institutions between three and nine staff members were dedicated to breast and cervical cancer screening, respectively, whereas in 71% of the institutions ≥10 staff members were dedicated to colorectal cancer screening. On average 60% of institutions fulfilled the target number of breast and cervical cancer screenings, whereas 93% fulfilled the target number for colorectal cancer screening. The determinants of performance were rural districts for breast (OR = 5.16 (95%CI: 2.51-10.63)) and cervical (OR = 4.17 (95%CI: 2.14-8.11)) cancer screenings, and ≥3 staff members dedicated to cervical cancer screening (OR = 2.34 (95%CI: 1.09-5.01)). CONCLUSIONS: Primary healthcare institutions in China perform better in colorectal than in breast and cervical cancer screening, and institutions in rural districts perform better than institutions in urban districts. Increasing the number of staff members on breast and cervical cancer screening could improve the performance of population-based cancer screening

Improving the Students\u27 Writing Competence in a Second Language Acquisition Through the Implementation of Lesson Study

Writing is the most difficult skill for second language learners. It can be seen, for example, they always make ageneralization, simplification, less of knowing vocabularies, punctuation, spelling, and grammar. This paper will describe improving the students\u27 writing competence in second language acquisition through the implementation of lesson study in faculty of language education of Indraprasta PGRI University of Jakarta. This research uses qualitative approach and the data taken from the students who are studying writing in the class. In applying lesson study, lecturer model explains about the materials based on the syllabus of the subject. The students are also given tasks in their groups. The observers watch and write about the students and assist them. After doing this, the observers discuss about the class with the lecturer model. By doing the implementation of Lesson Study, the students can work in group together, the class is so inspiring, they feel satisfied with the explanation of the lecturer model and havegood impact to improve the students\u27 writing competence

Coronary calcium scores on dual-source photon-counting computed tomography:an adapted Agatston methodology aimed at radiation dose reduction

OBJECTIVES: The aim of this study was to determine mono-energetic (monoE) level-specific photon-counting CT (PCCT) Agatston thresholds, to yield monoE level independent Agatston scores validated with a dynamic cardiac phantom. Also, we examined the potential of dose reduction for PCCT coronary artery calcium (CAC) studies, when reconstructed at low monoE levels. METHODS: Theoretical CAC monoE thresholds were calculated with data from the National Institute of Standards and Technology (NIST) database. Artificial CAC with three densities were moved in an anthropomorphic thorax phantom at 0 and 60-75 bpm, and scanned at full and 50% dose on a first-generation dual-source PCCT. For all densities, Agatston scores and maximum CT numbers were determined. Agatston scores were compared with the reference at full dose and 70 keV monoE level; deviations (95% confidence interval) < 10% were deemed to be clinically not-relevant. RESULTS: Averaged over all monoE levels, measured CT numbers deviated from theoretical CT numbers by 6%, 13%, and - 4% for low-, medium-, and high-density CAC, respectively. At 50% reduced dose and 60-75 bpm, Agatston score deviations were non-relevant for 60 to 100 keV and 60 to 120 keV for medium- and high-density CAC, respectively. CONCLUSION: MonoE level-specific Agatston score thresholds resulted in similar scores as in standard reconstructions at 70 keV. PCCT allows for a potential dose reduction of 50% for CAC scoring using low monoE reconstructions for medium- and high-density CAC. KEY POINTS: • Mono-energy level-specific Agatston thresholds allow for reproducible coronary artery calcium quantification on mono-energetic images. • Increased calcium contrast-to-noise ratio at reduced mono-energy levels allows for coronary artery calcium quantification at 50% reduced radiation dose for medium- and high-density calcifications

Reproducibility of coronary artery calcium quantification on dual-source CT and dual-source photon-counting CT:a dynamic phantom study

To systematically compare coronary artery calcium (CAC) quantification between conventional computed tomography (CT) and photon-counting CT (PCCT) at different virtual monoenergetic (monoE) levels for different heart rates. A dynamic (heart rates of 0,  75 bpm) anthropomorphic phantom with three calcification densities was scanned using routine clinical CAC protocols with CT and PCCT. In addition to the standard clinical protocol of 70 keV, PCCT images were reconstructed at monoE levels of 72, 74, and 76 keV. CAC was quantified using Agatston, volume, and mass scores. Agatston scores 95% confidence intervals (CI) were calculated and compared between PCCT and CT. Volume and mass scores were compared with physical quantities. For all CAC densities, routine clinical protocol Agatston scores of static CAC were higher for PCCT compared to CT. At < 60 bpm, Agatston scores at 74 and 76 keV reconstructions were reproducible (overlapping CI) for PCCT and CT. Increased heart rates yielded different Agatston scores for PCCT in comparison with CT, for all monoE levels. Low density CAC volume scores showed the largest deviation from physical volume, with mean deviations of 59% and 77% for CT and PCCT, respectively. Overall, mass scores underestimated physical mass by 10%, 38%, and 59% for low, medium, and high density CAC, respectively. PCCT allows for reproducible Agatston scores for dynamic CAC (< 60 bpm) when reconstructed at monoE levels of 74 or 76 keV, regardless of CAC density. Deviations from physical volume and mass were, in general, large for both CT and PCCT

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening

BACKGROUND: Artificial intelligence (AI)-based automatic lung nodule detection system improves the detection rate of nodules. It is important to evaluate the clinical value of AI system by comparing AI-assisted nodule detection with actu-al radiology reports. OBJECTIVE: To compare the detection rate of lung nodules between the actual radiology reports and AI-assisted reading in lung cancer CT screening. METHODS: Participants in chest CT screening from November to December 2019 were retrospectively included. In the real-world radiologist observation, 14 residents and 15 radiologists participated to finalize radiology reports. In AI-assisted reading, one resident and one radiologist reevaluated all subjects with the assistance of an AI system to lo-cate and measure the detected lung nodules. A reading panel determined the type and number of detected lung nodules between these two methods. RESULTS: In 860 participants (57±7 years), the reading panel confirmed 250 patients with >1 solid nodule, while radiolo-gists observed 131, lower than 247 by AI-assisted reading (p1 non-solid nodule, whereas radiologist observation identified 28, lower than 110 by AI-assisted reading (p<0.001). The accuracy and sensitivity of radiologist observation for solid nodules were 86.2% and 52.4%, lower than 99.1% and 98.8% by AI-assisted reading, respectively. These metrics were 90.4% and 25.2% for non-solid nodules, lower than 98.8% and 99.1% by AI-assisted reading, respectively. CONCLUSION: Comparing with the actual radiology reports, AI-assisted reading greatly improves the accuracy and sensi-tivity of nodule detection in chest CT, which benefits lung nodule detection, especially for non-solid nodules

Analisis Kesalahan Berbahasa Indonesia Dalam Karangan Eksposisi Siswa Sekolah Menengah Atas

: The purpose of this research is : (1) to describes the error of Indonesian language in exposition text by the students at class X of SMA Negeri in Karanganyar in the academic year 2011/2012; (2) causes of error, and (3) the effort which is done by the teacher and student to solve the error. This research is a qualitative descriptive research with a sample student text SMA Negeri 1 Karanganyar and SMA Negeri Kebakkramat. The sampling technique used was purposive sampling. Data collection techniques used were in-depth interviews and document analysis. Data analysis technique used is the interactive analytical model that includes four components, namely data collection, data reduction, data presentation, and verification. The conclusions of this study are as follows. Firstly, the linguistic elements of language errors that often occur in the student text is divided into four errors : spelling error, diction, sentence, and paragraph. Secondly, language errors that often occur in a student text exposition caused by several factors, among others: is inadequate of language mastery, lack of examples by the teachers, the influence of foreign language, lack of writing peactice, and lack of writing time. Thirdly, the efforts have been made to minimize errors include: improving students\u27 language mastery, having more practices in writing, implementing appropriate correction technique, and implementing a process approach to teaching writing

Supplementary data for a model-based health economic evaluation on lung cancer screening with low-dose computed tomography in a high-risk population

This supplementary data is supportive to the research article entitled ‘Cost-effectiveness of lung cancer screening with low-dose computed tomography (LDCT) in heavy smokers: A micro-simulation modelling study’ (Yihui Du et al. 2020). This supplementary contains a description of the model input and the related model output data that were not included in the research article. The input data used for the tumour growth model and the self-detected tumour size model are provided. The output data of this article include the data used for cost-effectiveness analysis of lung cancer LDCT screening with the Dutch and international discount rates, the data of the sensitivity analysis, and the data of the model validation

Dose Reduction in Coronary Artery Calcium Scoring Using Mono-Energetic Images from Reduced Tube Voltage Dual-Source Photon-Counting CT Data:A Dynamic Phantom Study

In order to assess coronary artery calcium (CAC) quantification reproducibility for photon-counting computed tomography (PCCT) at reduced tube potential, an anthropomorphic thorax phantom with low-, medium-, and high-density CAC inserts was scanned with PCCT (NAEOTOM Alpha, Siemens Healthineers) at two heart rates: 0 and 60–75 beats per minute (bpm). Five imaging protocols were used: 120 kVp standard dose (IQ level 16, reference), 90 kVp at standard (IQ level 16), 75% and 45% dose and tin-filtered 100 kVp at standard dose (IQ level 16). Each scan was repeated five times. Images were reconstructed using monoE reconstruction at 70 keV. For each heart rate, CAC values, quantified as Agatston scores, were compared with the reference, whereby deviations >10% were deemed clinically relevant. Reference protocol radiation dose (as volumetric CT dose index) was 4.06 mGy. Radiation dose was reduced by 27%, 44%, 67%, and 46% for the 90 kVp standard dose, 90 kVp 75% dose, 90 kVp 45% dose, and Sn100 standard dose protocol, respectively. For the low-density CAC, all reduced tube current protocols resulted in clinically relevant differences with the reference. For the medium- and high-density CAC, the implemented 90 kVp protocols and heart rates revealed no clinically relevant differences in Agatston score based on 95% confidence intervals. In conclusion, PCCT allows for reproducible Agatston scores at a reduced tube voltage of 90 kVp with radiation dose reductions up to 67% for medium- and high-density CAC