Modern role of magnetic resonance and spectroscopy in the imaging of prostate cancer

Recently, a large number of studies have shown that the addition of proton 1H-spectroscopic imaging (1H-MRSI) and dynamic contrast enhanced imaging (DCEMR) to magnetic resonance (MR) could represent a powerful tool for the management of prostate cancer (CaP) in most of its aspects. This combination of MR techniques can substantially sustain the clinical management of patients with CaP at different levels: in particular, (1) in the initial assessment, reducing the need for more extensive biopsies and directing targeted biopsies; (2) in the definition of a biochemical progression after primary therapies, distinguishing between fibrotic reaction and local recurrence from CaP. (C) 2011 Elsevier Inc. All rights reserved

Value of magnetic resonance spectroscopy imaging and dynamic contrast-enhanced imaging for detecting prostate cancer foci in men with prior negative biopsy

Purpose: This study aimed to prospectively analyze the role of magnetic resonance spectroscopy imaging (MRSI) and dynamic-contrast enhancement magnetic resonance (DCEMR) in the detection of prostate tumor foci in patients with persistently elevated prostate-specific antigen levels (in the range of >= 4 ng/mL to <10 ng/mL) and prior negative random trans-rectal ultrasound (TRUS)-guided biopsy. Experimental Design: This was a prospective randomized single-center study. One hundred and eighty eligible cases were included in the study. Patients in group A were submitted to a second random prostate biopsy, whereas patients in group B were submitted to a (1)H-MRSI-DCEMR examination and samples targeted on suspicious areas were associated to the random biopsy. Results: At the second biopsy, a prostate adenocarcinoma histologic diagnosis was found in 22 of 90 cases (24.4%) in group A and in 41 of 90 cases (45.5%) in group B (P = 0.01). On a patient-by-patient basis, MRSI had 92.3% sensitivity, 88.2% specificity, 85.7% positive predictive value (PPV), 93.7% negative predictive value (NPV), and 90% accuracy; DCEMR had 84.6% sensitivity, 82.3% specificity, 78.5% PPV, 87.5% NPV, and 83.3% accuracy; and the association MRSI plus DCEMR had 92.6% sensitivity, 88.8% specificity, 88.7% PPV, 92.7% NPV, and 90.7% accuracy, for predicting prostate cancer detection. Conclusions: The combination of MRSI and DCEMR showed the potential to guide biopsy to cancer foci in patients with previously negative TRUS biopsy. To avoid a potential bias, represented from having taken more samples in group B (mean of cores, 12.17) than in group A (10 cores), in the future a MRSI/DCEMR directed biopsy could be prospectively compared with a saturation biopsy procedure. Clin Cancer Res; 16(6); 1875-83. (C) 2010 AACR

Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 – 16.0%) if 80% of contacts were under active surveillance but depending on assumptions about the ratio of contacts not under active surveillance versus contacts under active surveillance 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 – 87.0% or 1.70 – 80.9%)

Which factors can influence post-operative renal function preservation after nephron-sparing surgery for kidney cancer: a critical review

Introduction: The aim of this article was to compare different surgical approaches to perform nephron-sparing surgery (NSS) in terms of preservation of renal function. Material and methods: We critically reviewed the literature from January 2000 to December 2020 including studies comparing different surgical techniques. Results: A total of 51 studies met the inclusion criteria. Functional outcomes were evalutated in terms of percentual change of estimated glomerular filtration rate (eGFR) and impaired renal function (IRF) on scintigraphy. In cases with a mean age <60 years, the mean decrease in eGFR after NSS was 11.7% and that of IRF 10.0%, whereas higher changes were found in cases with a mean age ≥60 years. For open NSS, the mean eGFR and IRF changes were 15.3% and 21.1%, respectively; using the laparoscopic approach, the mean percentual eGFR and IRF changes were 13.9% and 11.1%, respectively; in robotic cases, the mean eGFR and IRF changes were 10.8% and 13.1%, respectively. In cases performed with global ischemia, the mean eGFR and IRF changes were 12.7% and 15.1%, respectively. Similar results were found distinguishing ischemia time ≤20 and >20 minutes, whereas using the off-clamp technique the mean decreases in eGFR and IRF were only 4.2% and 6%, respectively. Conclusions: Patients' age, tumor size, off-clamp technique, and robot-assisted approach were significant independent predictive factors able to influence renal function changes after NSS. A lower reduction of eGFR and IRF after NSS was reported in patients aged <60 years, submitted to a robot-assisted procedure, and using selective and cold ischemia <20 minutes or an off-clamp technique

Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention ("lockdown") and reductions in individuals' mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies

Influence of operative time and blood loss on surgical margins and functional outcomes for laparoscopic versus robotic-assisted radical prostatectomy: a prospective analysis

Introduction: The aim of this article was to analyze whether operative time and blood loss during radical prostatectomy (RP) can significantly influence surgical margins (SM) status and post-operative functional outcomes. Material and methods: We prospectively analyzed prostate cancer (PC) patients undergoing RP, using robot-assisted (RARP) or laparoscopic (LRP) procedures. Blood loss was defined using the variation in hemoglobin (Hb, g/dl) values from the day before surgery and no later than 4 hours after surgery. Results: From a whole population of 413 cases considered for RP, 67% underwent LRP and 33.0% RARP. Positive SM (SM+) were found in 33.9% of cases. Mean surgical operative time was 172.3 ±76 min (range 49-485), whereas blood loss was 2.3 ±1.2 g/dl (range 0.3-7.6). Operative time and blood loss at RP were not significantly correlated (r = -0.028275; p = 0.684). SM+ rates significantly (p = 0.002) varied by operative time; a higher SM+ rate was found in cases with an operative time <120 min (41.2%) and >240 min (53.4%). The risk of SM+ significantly increased 1.70 and 1.94 times in cases with an operative time <120 min and >240 min, respectively, independently to the surgical approach. The rate of erectile disfunction (ED) varied from 22.4% to 60.3% between <120 min and >240 min procedures (p = 0.001). According to blood loss, SM+ rates slightly but significantly (p = 0.032) varied; a higher rate of SM+ was found in cases with a Hb variation between 2-4 g/dl (35.9%). Conclusions: Independently to the surgical approach, operative time, more than blood loss at RP, represents a significant variable able to influence SM status and post-operative ED

Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention (“lockdown”) and reductions in individuals’ mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies

Response to COVID-19 in South Korea and implications for lifting stringent interventions

Background After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the US. This has led to substantial interest in their “test, trace, isolate” strategy. However, it is important to understand the epidemiological peculiarities of South Korea’s outbreak and characterise their response before attempting to emulate these measures elsewhere. Methods We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. Results We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI; 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent “lockdown” measures, strong social distancing measures were implemented in high incidence areas and studies measured a considerable national decrease in movement in late-February. Testing capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly however we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact-tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. Conclusions Whilst early adoption of testing and contact-tracing are likely to be important for South Korea’s successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and low number of deaths suggests that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing and isolating cases that are linked to clusters may be more difficult

Report 12: The global impact of COVID-19 and strategies for mitigation and suppression

The world faces a severe and acute public health emergency due to the ongoing COVID-19 global pandemic. How individual countries respond in the coming weeks will be critical in influencing the trajectory of national epidemics. Here we combine data on age-specific contact patterns and COVID-19 severity to project the health impact of the pandemic in 202 countries. We compare predicted mortality impacts in the absence of interventions or spontaneous social distancing with what might be achieved with policies aimed at mitigating or suppressing transmission. Our estimates of mortality and healthcare demand are based on data from China and high-income countries; differences in underlying health conditions and healthcare system capacity will likely result in different patterns in low income settings. We estimate that in the absence of interventions, COVID-19 would have resulted in 7.0 billion infections and 40 million deaths globally this year. Mitigation strategies focussing on shielding the elderly (60% reduction in social contacts) and slowing but not interrupting transmission (40% reduction in social contacts for wider population) could reduce this burden by half, saving 20 million lives, but we predict that even in this scenario, health systems in all countries will be quickly overwhelmed. This effect is likely to be most severe in lower income settings where capacity is lowest: our mitigated scenarios lead to peak demand for critical care beds in a typical low-income setting outstripping supply by a factor of 25, in contrast to a typical high-income setting where this factor is 7. As a result, we anticipate that the true burden in low income settings pursuing mitigation strategies could be substantially higher than reflected in these estimates. Our analysis therefore suggests that healthcare demand can only be kept within manageable levels through the rapid adoption of public health measures (including testing and isolation of cases and wider social distancing measures) to suppress transmission, similar to those being adopted in many countries at the current time. If a suppression strategy is implemented early (at 0.2 deaths per 100,000 population per week) and sustained, then 38.7 million lives could be saved whilst if it is initiated when death numbers are higher (1.6 deaths per 100,000 population per week) then 30.7 million lives could be saved. Delays in implementing strategies to suppress transmission will lead to worse outcomes and fewer lives saved. We do not consider the wider social and economic costs of suppression, which will be high and may be disproportionately so in lower income settings. Moreover, suppression strategies will need to be maintained in some manner until vaccines or effective treatments become available to avoid the risk of later epidemics. Our analysis highlights the challenging decisions faced by all governments in the coming weeks and months, but demonstrates the extent to which rapid, decisive and collective action now could save millions of lives

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff ) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900-38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%-1.21%) to 0.79% (95%CrI: 0.63%-0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%-35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%-10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%-10.2%) and 22.3% (95%CrI: 19.4%-25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission