Sources of microbial contamination in the watershed and coastal zone of Soufriere, St. Lucia.

The Sustainable Development Goal 6 calls for global progress by 2030 in treating domestic wastewater and providing access to adequate sanitation facilities. However, meeting these goals will be a challenge for most Small Island Developing States, including Caribbean island nations. In the nearshore zone of the Soufriere region on the Caribbean island of St. Lucia, there is a history of high levels of bacteria of fecal origin. Possible land-based sources of microbial contamination in the Soufriere Bay include discharges from the Soufriere River and transport of wastewater, including fecal material from the town of Soufriere. This area is an important tourist destination and supports a local fishery. To identify the sources of microbial contamination in Soufriere Bay, a range of monitoring methods were employed in this study. In grab samples of surface water collected from the Soufriere River, counts of total coliforms and Escherichia coli were elevated above water quality guidelines. However, the spikes in concentrations of these indicator organisms in the river did not necessarily coincide with the spikes in the levels of total coliforms and E. coli detected in samples collected on the same dates in Soufriere Bay, indicating that there are other sources of pollution in the Bay besides discharges from the river. Monitoring for chemical indicators of wastewater (i.e., caffeine, sucralose, fluconazole) in the Soufriere River indicated that there are inputs of sewage or human fecal material throughout the watershed. However, analysis of Bacteroidales 16S rRNA genetic markers for fecal bacteria originating from humans, bovine ruminants, or other warm-blooded animals indicated that the majority of microbial contamination in the river was not from humans. Monitoring for chemical indicators of wastewater using passive samplers deployed in Soufriere Bay indicated that there are two "hot spots" of contamination located offshore of economically depressed areas of the town of Soufriere. This study indicates that efforts to control contamination of Soufriere Bay by fecal microorganisms must include management of pollution originating from both sewage and domestic animals in the watershed.

Effects of inner volume field-of-view reduction on myocardial T2 mapping.

BACKGROUND: Inner volume (IV) excitation was explored with respect to scan time reduction of cardiac gated double inversion recovery multi-echo fast spin echo (MEFSE) to measure the transverse relaxation time (T2 ) in the myocardium. METHODS: The IV imaging was achieved by applying orthogonal slice selection for the excitation and refocusing pulses. The T2 map accuracy was investigated using different excitation and refocusing pulses. The performance of IV-MEFSE was compared with MEFSE on phantoms and eight healthy volunteers, acquiring eight echo times in a single breath-hold. RESULTS: Compared with MEFSE, IV-MEFSE allowed a scan time reduction from 26 s to 16 s, but caused a T2 overestimation of approximately 10% due to stimulated echoes. CONCLUSION: IV successfully reduced the scan time to a single breath-hold feasible for many patients and remarkably facilitated the scan prescription, because there was no image aliasing concern. Care should be taken in using IV for T2 mapping because of T2 relaxation time overestimation.

Quantification of muscle fat in patients with low back pain: comparison of multi-echo MR imaging with single-voxel MR spectroscopy.

PURPOSE: To compare lumbar muscle fat-signal fractions derived from three-dimensional dual gradient-echo magnetic resonance (MR) imaging and multiple gradient-echo MR imaging with fractions from single-voxel MR spectroscopy in patients with low back pain. MATERIALS AND METHODS: This prospective study had institutional review board approval, and written informed consent was obtained from all study participants. Fifty-six patients (32 women; mean age, 52 years ± 15 [standard deviation]; age range, 20-79 years) with low back pain underwent standard 1.5-T MR imaging, which was supplemented by dual-echo MR imaging, multi-echo MR imaging, and MR spectroscopy to quantify fatty degeneration of bilateral lumbar multifidus muscles in a region of interest at the intervertebral level of L4 through L5. Fat-signal fractions were determined from signal intensities on fat- and water-only images from both imaging data sets (dual-echo and multi-echo fat-signal fractions without T2* correction) or directly obtained, with additional T2* correction, from multi-echo MR imaging. The results were compared with MR spectroscopic fractions. The Student t test and Bland-Altman plots were used to quantify agreement between fat-signal fractions derived from imaging and from spectroscopy. RESULTS: In total, 102 spectroscopic measurements were obtained bilaterally (46 of 56) or unilaterally (10 of 56). Mean spectroscopic fat-signal fraction was 19.6 ± 11.4 (range, 5.4-63.5). Correlation between spectroscopic and all imaging-based fat-signal fractions was statistically significant (R(2) = 0.87-0.92; all P < .001). Mean dual-echo fat-signal fractions not corrected for T2* and multi-echo fat-signal fractions corrected for T2* significantly differed from spectroscopic fractions (both P < .01), but mean multi-echo fractions not corrected for T2* did not (P = .11). There was a small measurement bias of 0.5% (95% limits of agreement: -6.0%, 7.2%) compared with spectroscopic fractions. CONCLUSION: Large-volume image-based (dual-echo and multi-echo MR imaging) and spectroscopic fat-signal fractions agree well, thus allowing fast and accurate quantification of muscle fat content in patients with low back pain.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages.

Importance: Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures. Objective: To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages. Design, Setting, and Participants: A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022. Main Outcomes and Measures: A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample. Results: There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample. Conclusions and Relevance: The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

Importance: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear. Objectives: To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system. Design, Setting, and Participants: This multisite, longitudinal prognostic study performed in 7 academic early recognition services in 5 European countries followed up patients with CHR syndromes or ROD and healthy volunteers. The referred sample of 167 patients with CHR syndromes and 167 with ROD was recruited from February 1, 2014, to May 31, 2017, of whom 26 (23 with CHR syndromes and 3 with ROD) developed psychosis. Patients with 18-month follow-up (n = 246) were used for model training and leave-one-site-out cross-validation. The remaining 88 patients with nontransition served as the validation of model specificity. Three hundred thirty-four healthy volunteers provided a normative sample for prognostic signature evaluation. Three independent Swiss projects contributed a further 45 cases with psychosis transition and 600 with nontransition for the external validation of clinical-neurocognitive, sMRI-based, and combined models. Data were analyzed from January 1, 2019, to March 31, 2020. Main Outcomes and Measures: Accuracy and generalizability of prognostic systems. Results: A total of 668 individuals (334 patients and 334 controls) were included in the analysis (mean [SD] age, 25.1 [5.8] years; 354 [53.0%] female and 314 [47.0%] male). Clinicians attained a balanced accuracy of 73.2% by effectively ruling out (specificity, 84.9%) but ineffectively ruling in (sensitivity, 61.5%) psychosis transition. In contrast, algorithms showed high sensitivity (76.0%-88.0%) but low specificity (53.5%-66.8%). A cybernetic risk calculator combining all algorithmic and human components predicted psychosis with a balanced accuracy of 85.5% (sensitivity, 84.6%; specificity, 86.4%). In comparison, an optimal prognostic workflow produced a balanced accuracy of 85.9% (sensitivity, 84.6%; specificity, 87.3%) at a much lower diagnostic burden by sequentially integrating clinical-neurocognitive, expert-based, PRS-based, and sMRI-based risk estimates as needed for the given patient. Findings were supported by good external validation results. Conclusions and Relevance: These findings suggest that psychosis transition can be predicted in a broader risk spectrum by sequentially integrating algorithms' and clinicians' risk estimates. For clinical translation, the proposed workflow should undergo large-scale international validation.

Chronic progressive external ophthalmoplegia: MR spectroscopy and MR diffusion studies in the brain.

OBJECTIVE: The purpose of our study was to show how, despite pathognomonic signs of cerebral involvement in chronic progressive external ophthalmoplegia (CPEO), mitochondrial respiratory chain insufficiency is associated with increased lactate and reduced N-acetylaspartate. CPEO and mitochondrial myopathy are caused by mitochondrial DNA mutations leading to impaired oxidative phosphorylation. Cortical and subcortical metabolites, cerebral diffusivity, and structural MRI were assessed to characterize possible subclinical cerebral pathology in CPEO. SUBJECTS AND METHODS: Ten patients with CPEO (n = 8), mitochondrial myopathy (n = 1), and Kearns-Sayre syndrome (n = 1) and 13 control group volunteers were studied by MRI, both long TE (144) proton MR spectroscopic imaging (1H MRSI), and diffusion-weighted imaging. Relative concentrations of N-acetylaspartate, choline, creatine, and lactate were estimated by Linear Combination of Model Spectra (LCModel) in healthy-appearing white matter, gray matter, and white matter hyperintensities. RESULTS: Of five patients with cortical atrophy, it was moderate in three and severe in two. One patient had severe and four had moderate cerebellar atrophy. Six of 10 patients showed unspecific white matter lesions, whereas the remainder had hyperintensities in the pyramidal tract (n =2) and middle cerebellar peduncle (n = 1) despite clinical signs. No basal ganglia lesions were found. Physiologic metabolite ratios were normal and lactate was absent in supratentorial healthy-appearing cortex and subcortical white matter. Global diffusion histogram metrics revealed no abnormalities. CONCLUSION: Normal spectroscopic imaging in radiologic unaffected brain and healthy global brain parenchymal diffusion findings do not support the hypothesis of a generalized cerebral energy loss in CPEO. Bilateral structural alteration of central motor pathways in two patients without clinical pyramidal signs may, however, reflect subclinical axonal injury in predilection sites in some patients.

[MR-guided laser-induced thermo-ablation of liver tumors: clinical experiences and therapy control concepts]. / MRT-gestützte laserinduzierte Thermoablation bei Lebertumoren--Klinische Aspekte und Konzept eines Uberwachungssystems.

Minimally-invasive, laser-induced interstitial thermotherapy (LITT) of solid tumors represents a valid alternative to surgical procedures such as tumor resections. Within the framework of a palliative study on 16 patients, a total of 25 metastases in the liver were treated in an open MR system (0.5 T). The intraoperative scanner design allows patient-based navigation, decisive for a safe applicator positioning, as well as temperature monitoring and direct inspection of the therapy result, without need for patient transfer or repositioning. Although the MR thermometry applied in the open scanner assisted LITT monitoring, the current accuracy of temperature data was not sufficient to serve automatic irradiation control. Therefore, an experimental monitoring and control system was developed in a closed MR scanner (1.5 T) featuring a calibrated MR thermometry. The system provides also an interface to the laser system, allowing the automatic off/on switching of the laser power according to preoperatively defined control criteria. The basic functionality of the automatic laser control was successfully demonstrated with laser ablation experiments of liver samples using irradiation parameters close to typical clinical values.

Effect of gold marker seeds on magnetic resonance spectroscopy of the prostate.

PURPOSE: Magnetic resonance stereoscopic imaging (MRSI) of the prostate is an emerging technique that may enhance targeting and assessment in radiotherapy. Current practices in radiotherapy invariably involve image guidance. Gold seed fiducial markers are often used to perform daily prostate localization. If MRSI is to be used in targeting prostate cancer and therapy assessment, the impact of gold seeds on MRSI must be investigated. The purpose of this study was to quantify the effects of gold seeds on the quality of MRSI data acquired in phantom experiments. METHODS AND MATERIALS: A cylindrical plastic phantom with a spherical cavity 10 centimeters in diameter wss filled with water solution containing choline, creatine, and citrate. A gold seed fiducial marker was put near the center of the phantom mounted on a plastic stem. Spectra were acquired at 1.5 Tesla by use of a clinical MRSI sequence. The ratios of choline + creatine to citrate (CC/Ci) were compared in the presence and absence of gold seeds. Spectra in the vicinity of the gold seed were analyzed. RESULTS: The maximum coefficient of variation of CC/Ci induced by the gold seed was found to be 10% in phantom experiments at 1.5 T. CONCLUSION: MRSI can be used in prostate radiotherapy in the presence of gold seed markers. Gold seeds cause small effects (in the order of the standard deviation) on the ratio of the metabolite's CC/Ci in the phantom study done on a 1.5-T scanner. It is expected that gold seed markers will have similar negligible effect on spectra from prostate patients. The maximum of 10% of variation in CC/Ci found in the phantom study also sets a limit on the threshold accuracy of CC/Ci values for deciding whether the tissue characterized by a local spectrum is considered malignant and whether it is a candidate for local boost in radiotherapy dose.

Proton MR spectroscopy of the brain at 3 T: an update.

Proton magnetic resonance spectroscopy ((1)H-MRS) provides specific metabolic information not otherwise observable by any other imaging method. (1)H-MRS of the brain at 3 T is a new tool in the modern neuroradiological armamentarium whose main advantages, with respect to the well-established and technologically advanced 1.5-T (1)H-MRS, include a higher signal-to-noise ratio, with a consequent increase in spatial and temporal resolutions, and better spectral resolution. These advantages allow the acquisition of higher quality and more easily quantifiable spectra in smaller voxels and/or in shorter times, and increase the sensitivity in metabolite detection. However, these advantages may be hampered by intrinsic field-dependent technical issues, such as decreased T(2) signal, chemical shift dispersion errors, J-modulation anomalies, increased magnetic susceptibility, eddy current artifacts, challenges in designing and obtaining appropriate radiofrequency coils, magnetic field instability and safety hazards. All these limitations have been tackled by manufacturers and researchers and have received one or more solutions. Furthermore, advanced (1)H-MRS techniques, such as specific spectral editing, fast (1)H-MRS imaging and diffusion tensor (1)H-MRS imaging, have been successfully implemented at 3 T. However, easier and more robust implementations of these techniques are still needed before they can become more widely used and undertake most of the clinical and research (1)H-MRS applications.