Cancer Detection Rate Research Articles

Practice list size, workforce composition and performance in English general practice: a latent profile analysis

BackgroundFollowing government calls for General Practices in England to work at scale, some practices have grown in size from traditionally small, General Practitioner (GP)-led organisations to large multidisciplinary enterprises. We assessed the effect of practice list size and workforce composition on practice performance in clinical outcomes and patient experience.MethodsWe linked five practice-level datasets in England to obtain a single dataset of practice workforce, list size, proportion of registered patients ≥ 65 years of age, female-male sex ratio, deprivation, rurality, GP contract type, patient experience of care, and Quality and Outcomes Framework (QOF) and non-QOF clinical processes and outcomes. Latent Profile Analysis (LPA) was used to cluster general practices into groups based on practice list size and workforce composition. Bayesian Information Criterion, Akaike Information Criterion and deliberation within the research team were used to determine the most informative number of groups. One-way ANOVA was used to assess how groups differed on indicator variables and other variables of interest. Linear regression was used to assess the association between practice group and practice performance.ResultsA total of 6024 practices were available for class assignment. We determined that a 3-class grouping provided the most meaningful interpretation; 4494 (74.6%) were classified as ‘Small GP-reliant practices’, 1400 (23.2%) were labelled ‘Medium-size GP-led practices with a multidisciplinary team (MDT) input’ and 131 (2.2%) practices were named ‘Large multidisciplinary practices’. Small GP-reliant practices outperformed larger multidisciplinary practices on all patient-reported indicators except on confidence and trust where medium-size GP-led practices with MDT input appeared to do better. There was no difference in performance between small GP-reliant practices and larger multidisciplinary practices on QOF incentivised indicators except on asthma reviews where medium-size GP-led practices with MDT input performed worse than smaller GP-reliant practices and immunisation coverage where the same group performed better than smaller GP-reliant practices. For non-incentivised indicators, larger multidisciplinary practices had higher cancer detection rates than small GP-reliant practices.ConclusionSmall GP-reliant practices were found to provide better patient reported access, continuity of care, experience and satisfaction with care. Larger multidisciplinary practices appeared to have better cancer detection rates but had no effect on other clinical processes and outcomes. As England moves towards larger multidisciplinary practices efforts should be made to preserve good patient experience.

Validity of central pain processing biomarkers for predicting the occurrence of oncological chronic pain: a study protocol

BackgroundDespite recent improvements in cancer detection and survival rates, managing cancer-related pain remains a significant challenge. Compared to neuropathic and inflammatory pain conditions, cancer pain mechanisms are poorly understood, despite pain being one of the most feared symptoms by cancer patients and significantly impairing their quality of life, daily activities, and social interactions. The objective of this work was to select a panel of biomarkers of central pain processing and modulation and assess their ability to predict chronic pain in patients with cancer using predictive artificial intelligence (AI) algorithms.MethodsWe will perform a prospective longitudinal cohort, multicentric study involving 450 patients with a recent cancer diagnosis. These patients will undergo an in-person assessment at three different time points: pretreatment, 6 months, and 12 months after the first visit. All patients will be assessed through demographic and clinical questionnaires and self-report measures, quantitative sensory testing (QST), and electroencephalography (EEG) evaluations. We will select the variables that best predict the future occurrence of pain using a comprehensive approach that includes clinical, psychosocial, and neurophysiological variables.DiscussionThis study aimed to provide evidence regarding the links between poor pain modulation mechanisms at precancer treatment in patients who will later develop chronic pain and to clarify the role of treatment modality (modulated by age, sex and type of cancer) on pain. As a final output, we expect to develop a predictive tool based on AI that can contribute to the anticipation of the future occurrence of pain and help in therapeutic decision making.

Regression–Based Diagnostic Models for Early Lung Cancer Integrating Conventional Indicators with Tumor Markers

The aim of this research was to develop a lung cancer diagnostic and predictive model that integrates traditional laboratory indicators with tumor markers. This model is intended to facilitate early screening and assist in the process of identifying or detecting lung cancer through a cost-effective, rapid, and convenient approach, ultimately enhancing the early detection rate of lung cancer. A retrospective study was conducted on 66 patients diagnosed with lung cancer and 159 patients with benign pulmonary conditions. Data including general clinical information, conventional laboratory test results, and tumor marker levels were collected. Data analysis was conducted using SPSS 26.0 (Statistical Product and Service Solutions 26.0). The lung cancer diagnosis and prediction model is created using a composite index established through binary logistic regression. The combined diagnostic prediction models, incorporating both traditional indicators and tumor markers, demonstrated a greater area under the curve (AUC) when compared to the diagnostic prediction model based solely on tumor markers and their combination testing. The values of cut-off point, AUC, accuracy, sensitivity, specificity, positive and negative detection rate and accuracy rate are 0.1805, 0.959, 86.67%, 0.955, 0.830, 95.45%, 83.02% and 89.33 respectively and it is shown that the combined diagnostic model display notable efficacy and clinical relevance in aiding the early diagnosis of lung cancer.

Retrospective analysis of the learning curve in perineal robot-assisted prostate biopsy.

Magnetic resonance imaging-transrectal ultrasound (MRI-TRUS)-fusion biopsy (FBx) of the prostate allows targeted sampling of suspicious lesions within the prostate, identified by multiparametric MRI. Due to its reliable results and feasibility, perineal MRI/TRUS FBx is now the gold standard for prostate cancer (PC) diagnosis. There are various systems for performing FBx on the market, for example, software-based, semirobotic, or robot-assisted platform solutions. Their semiautomated workflow promises high process quality independent of the surgeon's experience. The aim of this study was to analyze how the surgeon's experience influences the cancer detection rate (CDR) via targeted biopsy (TB) and the procedure's duration in robot-assisted FBx. A total of 1716 men who underwent robot-assisted FBx involving a combination of targeted and systematic sampling between October 2015 and April 2022 were analyzed. We extracted data from the patients' electronic medical records retrospectively. Primary endpoints were the CDR by TB and the procedure's duration. For our analysis, surgeons were divided into three levels of experience: ≤20 procedures (little), 21-100 procedures (intermediate), and >100 procedures (high). Statistical analysis was performed via regression analyses and group comparisons. Median age, prostate-specific antigen level, and prostate volume of the cohort were 67 (±7.7) years, 8.13 (±9.4) ng/mL, and 53 (±34.2) mL, respectively. Median duration of the procedure was 26 (±10.9) min. The duration decreased significantly with the surgeon's increasing experience from 35.1 (little experience) to 28.4 (intermediate experience) to 24.0 min (high experience) (p < 0.001). Using TB only, significant PC (sPC) was diagnosed in 872/1758 (49.6%) of the men. The CDR revealed no significant correlation with the surgeon's experience in either group comparison (p = 0.907) or in regression analysis (p = 0.65). While the duration of this procedure decreases with increasing experience, the detection rate of sPC in TB is not significantly associated with the experience of the surgeon performing robot-assisted FBx. This robot-assisted biopsy system's diagnostic accuracy therefore appears to be independent of experience.

Using an artificial intelligence platform to enhance cancer detection rates in primary care.

1560 Background: Patients with cancer who are diagnosed in a primary care setting have the best survival outcomes compared to any other route (e.g. Emergency department, routine referrals, incidental findings etc). This is primarily attributed to detection of cancer at an early stage. In the UK, the Cancer Detection Rate (CDR) metric serves as a measure of this, representing the percentage of cancer diagnoses originating from primary care referral routes. However, detecting cancer presents significant challenges, primarily due to the non-specific nature of cancer presentations, their tendency to overlap with symptoms of other conditions, and their relatively low prevalence. Artificial intelligence (AI) platforms may be able to support this endeavor but are yet to be established. C the Signs is an AI-enabled clinical decision support tool integrated into primary care practices to help clinicians stratify the risk of cancer and advise on which cancer pathway is most appropriate (if at all) for the patient’s presentation and history. Methods: An observational cohort study was undertaken between 1st May 2021 and 31st March 2022 where 35 practices (covering a population of almost 420,000) within the same geographic region in the East of England were offered the use of C the Signs, with the practices opting out as controls. All practices had the same access to referral and cancer diagnostic pathways within the region. The primary end point was to identify if C the Signs had a statistical impact on cancer detection rates in primary care through nationally linked data via Public Health England. Results: In practices utilizing C the Signs the CDR significantly increased from 58.7% in 2020-21 (prior to the implementation of C the Signs) to 66.0% in 2021-22, reflecting a significant increase of 12.3% (p &lt;0.05). In contrast, practices not using C the Signs maintained a stable CDR of 58.4% in both years. There was no statistically significant variance observed in the referral rate between the two groups, indicating no notable increase in diagnostic or referral activities. Conclusions: These findings underscore the importance of integrating cutting-edge technologies into primary care to improve cancer detection rates and facilitate early-stage diagnosis. Implementation of such advancements holds promise for reducing cancer-related mortality rates and enhancing overall patient outcomes.

Deep learning vs traditional breast cancer risk assessment models: Are we offering supplemental services to those who benefit the most?

1556 Background: Mammography-based deep learning (DL) risk stratification models improve discriminatory accuracy in predicting future breast cancer compared to traditional risk models; however, decisions for and insurance payment of supplemental services such as MRI are driven by traditional scores. The purpose of this study was to compare risk scores and cancer detection rates in patients identified as increased risk by DL vs traditional models in a large screening mammography cohort. Methods: This multisite study included consecutive patients ≥40y undergoing routine bilateral screening mammography from 9/2017 to 1/2022 at five facilities. Tyrer-Cuzick version 8 (TC) and National Cancer Institute Breast Cancer Risk Assessment Tool (BCRAT) 5-year and lifetime models and a DL 5-year model were used to assess risk. The following thresholds were used to define intermediate risk: ≥1.67% for TC and BCRAT 5-year, 2.2 for DL model and high risk: ≥20% for TC and BCRAT lifetime, ≥6.0 for DL model. Patients were included if all risk scores were available. Patient demographics were retrieved from electronic medical records and cancer outcomes through regional tumor registry linkage. The proportion of increased-risk patients and cancer detection rates (CDR [cancers per 1000 women screened]) across models were compared using Pearson’s Chi-square test. Results: 148476 exams in 69464 patients (mean age 58.0y [IQR: 50.0-67.0]) were performed. 81.7% (119386/146075) of exams were in White patients and 18.3% (26689/146075) in races other than White. CDR of those classified as intermediate risk by DL was 7.1 (450/63109) vs 4.7 (320/68545; P&lt;0.001) by TC and 4.2 (300/70831; P&lt;0.001) by BCRAT, and as high risk was 20.6 (305/14772) by DL vs 3.9 (64/16442; P&lt;0.001) by TC and 5.0 (29/5782; P&lt;0.001) by BCRAT. 13.0% (19248/148476) were classified as intermediate risk by DL but not by TC or BCRAT, with a CDR of 6.0 in this cohort. 32.0% (47435/148476) were classified as intermediate risk by TC or BCRAT but not by DL with a CDR of 1.1. 8.5% (12577/148476) were classified as high risk by DL but not by TC or BCRAT with a CDR of 20.8. 11.1% (16451/148476) were classified as high risk by TC or BCRAT but not by DL with a CDR of 1.9. Conclusions: A significant proportion of patients identified as increased risk by DL model are not assessed as increased risk by commonly used risk models, effectively excluding them from accessing potentially life-saving supplemental services. DL scores met the American College of Radiology's acceptable CDR on screening mammography (≥2.5) regardless of traditional scores, however, elevated traditional scores in the absence of elevated DL scores did not meet acceptable standards. Risk assessment guidelines incorporating DL models are necessary to capture patients who benefit the most.

Test-set results can predict participants' development in breast-screen cancer detection: An observational cohort study.

Test-sets are standardized assessments used to evaluate reader performance in breast screening. Understanding how test-set results affect real-world performance can help refine their use as a quality improvement tool. The aim of this study is to explore if mammographic test-set results could identify breast-screening readers who improved their cancer detection in association with test-set training. Test-set results of 41 participants were linked to their annual cancer detection rate change in two periods oriented around their first test-set participation year. Correlation tests and a multiple linear regression model investigated the relationship between each metric in the test-set results and the change in detection rates. Additionally, participants were divided based on their improvement status between the two periods, and Mann-Whitney U test was used to determine if the subgroups differed in their test-set metrics. Test-set records indicated multiple significant correlations with the change in breast cancer detection rate: a moderate positive correlation with sensitivity (0.688, p < 0.001), a moderate negative correlation with specificity (-0.528, p < 0.001), and a low to moderate positive correlation with lesion sensitivity (0.469, p = 0.002), and the number of years screen-reading mammograms (0.365, p = 0.02). In addition, the overall regression was statistically significant (F (2,38) = 18.456 p < 0.001), with an R² of 0.493 (adjusted R² = 0.466) based on sensitivity (F = 27.132, p < 0.001) and specificity (F = 9.78, p = 0.003). Subgrouping the cohort based on the change in cancer detection indicated that the improved group is significantly higher in sensitivity (p < 0.001) and lesion sensitivity (p = 0.02) but lower in specificity (p = 0.003). Sensitivity and specificity are the strongest test-set performance measures to predict the change in breast cancer detection in real-world breast screening settings following test-set participation.

Development of an algorithm combining blood-based biomarkers, fecal immunochemical test, and age for population-based colorectal cancer screening

Implementation of screening modalities have reduced the burden of colorectal cancer (CRC), but high false positive rates pose a major problem for colonoscopy capacity. We aimed to create a tailored screening algorithm that expands the fecal immunochemical test (FIT) with a blood specimen and current age to improve selection of individuals for diagnostic colonoscopy. In this prospective multi-center study, eight blood-based biomarkers (CEA, Ferritin, hsCRP, HE4, Cyfra21-1, Hepsin, IL-8 and OPG) were investigated in 1,977 FIT positive individuals from the Danish national CRC screening program undergoing follow-up colonoscopy. Specimens were analyzed on ARCHITECT i2000®, ARCHITECT c8000® or Luminex xMAP® machines. FIT analyses and blood-based biomarker data were combined with clinical data (i.e., age and colonoscopy findings) in a cross-validated logistic regression model (algorithm) benchmarked against a model solely using the FIT result (FIT model) applying different cutoffs for FIT positivity. The cohort included individuals with CRC (n = 240), adenomas (n = 938) or no neoplastic lesions (n = 799). The cross-validated algorithm combining the eight biomarkers, quantitative FIT result and age performed superior to the FIT model in discriminating CRC versus non-CRC individuals (AUC 0.77 versus 0.67, p < 0.001). When discriminating individuals with either CRC or high- or medium-risk adenomas versus low-risk adenomas or clean colorectum, the AUCs were 0.68 versus 0.64 for the algorithm and FIT model, respectively. The algorithm presented here can improve patient allocation to colonoscopy, reducing colonoscopy burden without compromising cancer and adenomas detection rates or vice versa.

Childhood Cancer in Cameroon and Kenya: Preliminary findings of an implementation effectiveness study for early detection of childhood cancer.

e23096 Background: Early childhood cancer detection reduces mortality, particularly in LMIC contexts where an improved understanding of early warning signs and symptoms (EWSS) and integration of vital referral pathways into existing health systems are crucial to improved childhood cancer outcomes. Our project seeks to adapt and implement a Ghanaian-developed EWSS intervention for Kenya and Cameroon using implementation science frameworks to move beyond the common but ineffective train-and-hope approach. Cameroon operates on a three-tiered sub-sector health system, with the intermediate level consisting of regional delegations that support districts1. In Kenya a six-tiered health system delivers primary care (1-2), mid-level care (3-4), advanced care with centers of excellence (5-6) 2. Health system contexts will inform implementation planning and execution. Methods: Health system stakeholders convened in each country to launch their EWSS initiative. Two-day meetings were collaboratively led by local stakeholders and the research team, guided by The Implementation Roadmap3, a multi-implementation framework resource. They discussed l) local barriers to childhood cancer detection, 2) referral pathways, 3) leadership and operational implementation teams, 4) sustainable EWSS training, and 4) target settings. Results: Stakeholders endorsed the EWSS program and identified individuals to form implementation teams to plan and execute implementation reflective of health system organization and realities. Both countries engaged in an evidence-based implementation planning process, reviewed EWSS core components and training logistics, and endorsed a sustainable tiered training model targeting clinicians and oncologists across system levels and institutional providers. Training content will be adapted for country, region, and county contexts. Both countries endorsed and identified district childhood cancer champions to facilitate training and coordinate timely referrals. Common implementation barriers identified included high healthcare worker turnover, transportation logistics for in-person training, and remuneration options for trainees. Conclusions: Health system leaders in Kenya and Cameroon endorsed an evidence-based EWSS implementation and sustainment approach and identified adaptations responsive to the health system contexts. Implementation will be locally led to ensure effectiveness, sustainability, and appropriate cultural EWSS adaptation. Moving forward, local implementation teams will work with researcher-facilitators to implement EWSS toward improved cancer detection rates.

Taiwan national lung cancer early detection program for heavy smokers and non-smokers with family history of lung cancer.

8009 Background: Lung cancer incidence in Taiwan has been rising with the epidemiological profiles distinct from Western country. Notably, nonsmoking lung cancers accounts for more than 60% and half of lung cancers were diagnosed in advanced stages. For early detection, a national program is therefore initiated to offer biennial low-dose computed tomography (LDCT) screening for heavy smokers and subjects with lung cancer family history (LCFH). Here, we report basic screening findings, analyze relevant effectiveness in reducing advanced lung cancer, and project the potential benefit of mortality reduction. Methods: Taiwan National Lung Cancer Early Detection Program was launched on July 1, 2022 to offer heavy smokers (30 pack-years) and nonsmokers (including light smokers) with a LCFH aged 45-74 years for female and aged 50-74 years for male. This is a continuous screening program using before and after study design for evaluation. We provided the overall first-year basic screening findings until Dec 31, 2023 and did per protocol analysis of stage II+ cancer reduction in comparison with tumor stage distribution in the year preceding the introduction of the national program. The corresponding findings were presented for subjects with LCFH and heavy smokers. The result for heavy smoker was compared with those per-protocol findings from previous randomized controlled trials. The potential mortality reduction was further projected. Results: A total of 78,000 individuals participated in this program, male 44,381 (56.9%) female 33,619 (43.1%); 31,111 participants (39.9%) were heavy smokers, 43,853 (56.2%) nonsmokers but with a LCFH, and 3,036 (3.9%) had both risk factors. Lung cancer confirmed in 956 subjects by surgery or biopsy, 85.0% were stage 0-1. The lung cancer detection rate was 1.2%. Subjects with a LCFH exhibited a higher detection rate (overall: 1.6%, nonsmokers: 1.7% and light smokers 0.9%) compared to heavy smokers (0.7%) and both (1.1%). Early detection of LDCT led to a statistically significant 77% (51%-89%) of reducing advanced stage of lung cancer, 53% (-3%-78%) reduction for heavy smokers, consistent with the corresponding 36%-64% reduction derived from the NLST trial and the Nelson trial, and 85% (67%-93%) reduction for nonsmokers with a LCFH. The benefit of reducing stage II or severe in conjunction with five-year stage-specific survival rate further projected 55% (10%-78%) of mortality reduction from lung cancer. Conclusions: This is the first large-scale LC screening service enrolling 40% heavy smokers and 60% non-smoker with a LCFH. The potential effectiveness of early detection was demonstrated for both targets. As the results based on per-protocol analysis for heavy smoker were consistent with those of previous evidence-based studies the similar and significant intention-to-treat results as before while waiting for the subsequent follow-up would be expected.

Screening for lung cancer using thin-slice low-dose computed tomography in southwestern China: a population-based real-world study.

Lung cancer is one of the most common malignant tumors threatening human life and health. At present, low-dose computed tomography (LDCT) screening for the high-risk population to achieve early diagnosis and treatment of lung cancer has become the first choice recommended by many authoritative international medical organizations. To further optimize the lung cancer screening method, we conducted a real-world study of LDCT lung cancer screening in a large sample of a healthy physical examination population, comparing differences in lung nodules and lung cancer detection between thin and thick-slice LDCT scanning. A total of 29 296 subjects who underwent low-dose thick-slice CT scanning (5 mm thickness) from January 2015 to December 2015 and 28 058 subjects who underwent low-dose thin-slice CT scanning (1 mm thickness) from January 2018 to December 2018 in West China Hospital were included. The positive detection rate, detection rate of lung cancer, pathological stage of lung cancer, and mortality rate of lung cancer were analyzed and compared between the two groups. The positive rate of LDCT screening in the thin-slice scanning group was significantly higher than that in the thick-slice scanning group (20.1% vs. 14.4%, p < 0.001). In addition, the lung cancer detection rate in the thin-slice LDCT screening positive group was significantly higher than that in the thick-slice scanning group (78.0% vs. 52.9%, p < 0.001). The screening positive rate of low-dose thin-slice CT scanning is higher and more early-stage lung cancer (IA1 stage) can be detected in the screen-positive group.

A novel simplified transperineal prostate biopsy guided by perineal ultrasound.

Prostate biopsies are mainly performed through transrectal or perineal approaches, while ultrasound probes are located in the rectum for guidance. However, reports on the use of perineal ultrasound-guided transperineal prostate biopsy (PG-TPPB) are few. A retrospective case-control study was designed. A total of 111 patients who underwent PG-TPPB from February 2019 to December 2020 were investigated retrospectively. Simultaneously, 188 patients who underwent transrectal prostate biopsy (TRPB) were included as control. The prostate cancer detection rates (PCDR), complication rates, and application values were compared between the 2 groups. The overall PCDR in the PG-TPPB and TRPB groups were 33.3% (37/111) and 39.9% (75/188), respectively (P = .258). There was no significant difference in the PCDR between the 2 groups under each prostate-specific antigen level (all P > .05). The single-needle PCDR in the PG-TPPB and TRPB groups were 21.5% (277/1 287) and 24.0% (513/2 134), respectively (P = .091). The incidence of complications in the PG-TPPB group was significantly lower than that in the TRPB group (8.1% vs 21.3%, P = .003). The PCDRs of PG-TPPB and TRPB were the same. However, the postoperative complication rate of PG-TPPB was significantly lower than that of TRPB. Moreover, PG-TPPB required simpler equipment and did not require enema administration, which is suitable for patients with rectal contraindications. The reports on PG-TPPB are few. Our study indicated that PG-TPPB reduced the postoperative complication rate. Moreover, PG-TPPB required simpler equipment. Importantly, PG-TPPB is suitable for patients with rectal contraindications.

Development and status quo of digestive endoscopy in China: An analysis based on the national census in 2013 and 2020.

Technique and practice of digestive endoscopy are undergoing speedy development all over the world. This study aimed to evaluate its status quo and development in China. All hospitals performing digestive endoscopy in mainland China participated in the national census in 2013 and 2020. Retrospective data of hospitals, endoscopists, volumes, and qualities were collected via an online structured questionnaire, and its accuracy and rationality were verified by logical tests and manual reviews. Data from other countries were used to compare with that of China. From 2012 to 2019, the number of hospitals performing digestive endoscopy increased from 6,128 to 7,470 (1.22-fold), in which primary healthcare played a minor role. The median hospitals per 100,000 inhabitants per provincial region increased from 0.49 (IQR, 0.39-0.57) to 0.55 (IQR, 0.49-0.63). The endoscopists increased from 26,203 to 39,638 (1.51-fold), but their average workload even expanded. Overall volume increased from 28.8 million to 44.5 million (1.55-fold), and most types of endoscopic procedures recorded a high growth rate. Contrastingly, the specific utilization rates were low and paled in comparison with some developed countries. Nationwide, regional utilization rates showed a significant correlation with GDP per capita (P <0.001). Overall qualities of digestive endoscopy were excellent, but certain results of quality indicators posed a huge challenge, such as the detection rates of adenoma and early cancers. Impressive progress has been made in digestive endoscopy with rapidly expanding economy in China. However, primary healthcare, utilization rates, and income-related inequality of regional services were needed to be improved to promote public health better.

Is annual screening by fecal immunochemical test necessary after a recent colonoscopy?

The population-based colorectal cancer screening guidelines in Japan recommend an annual fecal immunochemical test (FIT). However, there is no consensus on the need for annual FIT screening for patients who recently performed a total colonoscopy (TCS). Therefore, we evaluated the repeated TCS results for patients with positive FIT after a recent TCS to assess the necessity of an annual FIT. We reviewed patients with positive FIT in opportunistic screening from April 2017 to March 2022. The patients were divided into two groups: those who had undergone TCS within the previous 5 years (previous TCS group) and those who had not (non-previous TCS group). We compared the detection rates of advanced neoplasia and colorectal cancer between the two groups. Of 671 patients, 151 had received TCS within 5 years and 520 had not. The detection rates of advanced neoplasia in the previous TCS and non-previous TCS groups were 4.6% and 12.1%, respectively (p < 0.01), and the colorectal cancer detection rates were 0.7% and 1.5%, respectively (no significant difference). The adenoma detection rates were 33.8% in the previous TCS group and 40.0% in the non-previous TCS group (no significant difference). Only a few patients were diagnosed with advanced neoplasia among the patients with FIT positive after a recent TCS. For patients with adenomatous lesions on previous TCS, repeated TCS should be performed according to the surveillance program without an annual FIT. The need for an annual FIT for patients without adenomatous lesions on previous TCS should be prospectively assessed in the future.

Storz professional image enhancement system (SPECTRA A) enhancing detection of carcinoma urinary bladder by white light cystoscopy

BackgroundSPECTRA A filters red light from white light through software to create contrast for better tissue visualization and light penetration. We aim to find whether the detection rate of bladder cancer is enhanced by SPECTRA A in adjunct to White Light Cystoscopy (WLC).MethodsThis was a prospective observational study among 66 patients in the Department of Urology and Kidney Transplant Surgery, Tribhuvan University Teaching Hospital. All patients undergoing TURBT for suspected/diagnosed bladder tumor were evaluated with WL, followed by SPECTRA A mode, and findings were recorded using visual bladder mapping. Resection of the tumor was done on WL, margins were again reevaluated using SPECTRA A mode, and a biopsy was taken in cases of suspicious findings confirmed on SPECTRA A. Tumor detection rate (sensitivity), extra lesion detection, false positive rate, and margin status were evaluated through 2 × 2 tables, McNemar chi-square test on patient level as well as lesion level.ResultsA total of 64 patients were included in the study. The mean age was 62.20 ± 13.98 with a sex ratio of M:F 4.3:1. SPECTRA A and WL had a detection rate of 95.33% and 78.80% (p = 0.001), respectively, and positive biopsy of detected lesions was 78.8% and 84.13% (p = 0.041), respectively, for SPECTRA A and WL. The false positive rate of SPECTRA A and WL was 21.19% and 15.86% (p = 0.006), respectively, whereas the false negative rate was 4% and 19.2% (p = 0.001), respectively. The number of extra lesions detected by SPECTRA A was 39, out of which 29 were histologically proven tumors.ConclusionSPECTRA A enhances the detection rate of bladder cancer when used with WL. We can increase the detection of bladder cancer by using a combination of white light and SPECTRA A.

Diagnostic performance of regional systematic biopsy for prostate cancer stratified by PI-RADS and histologic zones.

To explore the diagnostic performance of targeted biopsy (TB) combined with regional systematic biopsy (RSB) in patients with different Prostate Imaging Reporting and Data System (PI-RADS) and histologic zones for prostate lesions. This retrospective study included 1301 patients who underwent multiparametric MRI followed by combined MRI/US fusion-guided TB+systematic biopsy (SB) between January 2019 and October 2022. RSB was defined as the four perilesional SB cores adjacent to an MRI-positive lesion. Cancer detection rates were calculated for TB + SB, TB, SB, and TB + RSB, while the McNemar test was utilized for multiple comparisons among them. Subgroup analyses were performed based on different Pl-RADS and histologic zones. Of 1301 included participants (median age, 68 years; interquartile range, 63-74 years), 16,104 total biopsy cores were performed. TB + RSB detected clinically significant prostate cancer in 70.9% (922/1301) of patients, which was significantly higher than TB (67.4%, p < 0.001) or SB (67.5%, p < 0.001) but similar to TB + SB (71.0%, p = 0.50). Compared with TB + SB, TB + RSB required fewer median biopsy cores (6.3 vs. 12.4, p < 0.001) and had a higher proportion of positive cores (56.3% vs. 39.0%, p < 0.001). Subgroup analysis showed that TB had outstanding sensitivity for detecting PI-RADS 5 lesions in the PZ. Compared with TB + SB, TB + RSB achieved a similar clinically significant prostate cancer detection rate while requiring fewer biopsy cores and exhibiting higher diagnostic efficiency. For MRI-positive prostate lesions, targeted biopsy combined with regional systematic biopsy could serve as an alternative diagnostic approach to targeted biopsy combined with systematic biopsy. The scheme of prostate biopsy needs to be optimized. Regional systematic biopsy decreases the total number of cores taken. Targeted biopsies combined with regional systematic biopsies improve prostate diagnostic efficiency.

Comparison of Effective Imaging Modalities for Detecting Gastric Neoplasms: A Randomized 3-Arm Phase II Trial.

The early detection of gastric neoplasms (GNs) leads to favorable treatment outcomes. The latest endoscopic system, EVIS X1, includes third-generation narrow-band imaging (3G-NBI), texture and color enhancement imaging (TXI), and high-definition white-light imaging (WLI). Therefore, this randomized phase II trial aimed to identify the most promising imaging modality for GN detection using 3G-NBI and TXI. Patients with scheduled surveillance endoscopy after a history of esophageal cancer or GN or preoperative endoscopy for known esophageal cancer or GN were randomly assigned to the 3G-NBI, TXI, or WLI groups. Endoscopic observations were performed to detect new GN lesions, and all suspected lesions were biopsied. The primary endpoint was the GN detection rate during primary observation. Secondary endpoints were the rate of missed GNs, early gastric cancer detection rate, and positive predictive value for a GN diagnosis. The decision rule had a higher GN detection rate between 3G-NBI and TXI, outperforming WLI by >1.0%. Finally, 901 patients were enrolled and assigned to the 3G-NBI, TXI, and WLI groups (300, 300, and 301 patients, respectively). GN detection rates in the 3G-NBI, TXI, and WLI groups were 7.3, 5.0, and 5.6%, respectively. The rates of missed GNs were 1.0, 0.7, and 1.0%, the detection rates of early gastric cancer were 5.7, 4.0, and 5.6%, and the positive predictive values for the diagnosis of GN were 36.5, 21.3, and 36.8% in the 3G-NBI, TXI, and WLI groups, respectively. Compared with TXI and WLI, 3G-NBI is a more promising modality for GN detection.

Transperineal 3-Core Magnetic Resonance Imaging Ultrasound Fusion Targeted Plus Laterally 6-Core Systematic Biopsy in Prostate Cancer Diagnosis

IntroductionIt is important to explore strategies reducing the number of SB cores taken to minimize biopsy-related morbidity and patient's discomfort during biopsy. This study aims to optimize prostate biopsy procedures by reducing the number of systematic biopsy (SB) cores while preserving cancer detection rates in the era of combined biopsy. Patients and MethodsWe prospectively recruited patients with ≥1 magnetic resonance imaging (MRI) lesions and they underwent transperineal combined 12-core SB+3-core targeted prostate biopsy (TB, reference standard). New strategy was defined as a laterally 6-core SB+3-core TB. Patients were served as their own control. Detection rates for overall prostate cancer (PCa) and clinically significant PCa (csPCa) were compared among the standard SB, MRI-TB, 6-core SB +3-core TB, and reference standard. Pathology consistency was assessed using the Kappa test. ResultsA total of 204 men were included, of which 111 (54.41%) and 92 (45.10%) harbored overall PCa and csPCa. Referenced combined biopsy detected significantly 6.86% (P = .0005) or 4.90% (P = .0044) more csPCa than performing only SB or 3-core TB, but was comparable to the new biopsy strategy. (45.10% vs. 43.14%, P = .1336) Similar results persisted when limiting patients in biopsy-naïve men or stratified by Prostate Imaging Reporting and Data System scores, PSAD, and index lesion parameters. Additionally, performing 6-core SB+3-core TB demonstrated high consistency with reference standard in grade group distribution (Kappa coefficient: 0.952 for all, 0.961 for biopsy-naïve men) and achieved superior sensitivity of 95.7% (All: 95% CI: 89.2%-99.8%) and 96.9% (Biopsy-naïve: 95% CI: 91.1%-99.7%), respectively. ConclusionsThe 6-core SB+3-core TB approach maintains expected detection rates while reducing the total core count, offering a promising alternative to the reference standard, which may help to tailor transperineal combined biopsy procedures.

Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics

ObjectiveDeep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the diagnostic quality of reconstructed images.Materials and methodsA retrospective multisite study of 1535 patients assessed biparametric prostate MRI between 2016 and 2020. Likely clinically significant prostate cancer (csPCa) lesions (PI-RADS ≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document} 4) were delineated by expert radiologists. T2-weighted scans were retrospectively undersampled, simulating accelerated protocols. DL reconstruction (DLRecon) and diagnostic DL detection (DLDetect) were developed. The effect on the partial area under (pAUC), the Free-Response Operating Characteristic (FROC) curve, and the structural similarity (SSIM) were compared as metrics for diagnostic and visual quality, respectively. DLDetect was validated with a reader concordance analysis. Statistical analysis included Wilcoxon, permutation, and Cohen’s kappa tests for visual quality, diagnostic performance, and reader concordance.ResultsDLRecon improved visual quality at 4- and 8-fold (R4, R8) subsampling rates, with SSIM (range: −1 to 1) improved to 0.78 ± 0.02 (p < 0.001) and 0.67 ± 0.03 (p < 0.001) from 0.68 ± 0.03 and 0.51 ± 0.03, respectively. However, diagnostic performance at R4 showed a pAUC FROC of 1.33 (CI 1.28–1.39) for DL and 1.29 (CI 1.23–1.35) for naive reconstructions, both significantly lower than fully sampled pAUC of 1.58 (DL: p = 0.024, naïve: p = 0.02). Similar trends were noted for R8.ConclusionDL reconstruction produces visually appealing images but may reduce diagnostic accuracy. Incorporating diagnostic AI into the assessment framework offers a clinically relevant metric essential for adopting reconstruction models into clinical practice.Clinical relevance statementIn clinical settings, caution is warranted when using DL reconstruction for MRI scans. While it recovered visual quality, it failed to match the prostate cancer detection rates observed in scans not subjected to acceleration and DL reconstruction.

Clinically Significant Prostate Cancer Detection Following Transrectal and Transperineal Biopsy: Results of the Prostate Biopsy Efficacy and Complications Randomized Clinical Trial.

The comparative effectiveness of transrectal and transperineal prostate biopsy in detecting clinically significant prostate cancer is not well understood. We conducted a randomized clinical trial to determine whether transperineal biopsy improves the detection of clinically significant prostate cancer. Of the 840 men randomized, 93% were White, 44% had a previous biopsy, with a median age of 66 years and median PSA density of 0.14. Of these, 384 underwent transrectal and 398 underwent transperineal prostate biopsy. Prebiopsy prostate MRI was performed in 96% of men. Grade Group ≥ 2 prostate cancer was classified as clinically significant. Odds ratios were calculated using logistic regression to evaluate the effect of biopsy procedures on cancer detection rates. The detection rates of clinically significant prostate cancer were 47.1% and 43.2% (odds ratio 1.17; 95% CI, 0.88-1.55) for transrectal and transperineal biopsy, respectively. Age, PSA density, clinical stage and Prostate Imaging Reporting and Data System score were associated with the diagnosis of clinically significant cancer, whereas history of previous biopsy, anterior tumors, and biopsy procedure (transrectal or transperineal) were not. Clinically significant cancer detection rates in biopsy-naïve men undergoing MRI-targeted transrectal or transperineal biopsy were 59% and 62%, respectively. The overall cancer detection rates following transrectal and transperineal biopsy were 72.1% and 70.4%, respectively. There was no significant difference noted in the detection of clinically significant prostate cancer following transrectal or transperineal prostate biopsy. Urologists may utilize either biopsy procedure that best suits their patients' needs and practice setting.