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Simple Summary: Prostate cancer bone metastases are a heterogonous disease with heterogeneous therapy-response, not adequately captured by one-dimensional imaging biomarker measurements. DWI and Dixon MRI radiomics analysis may tackle this shortcoming, but technical assessment of repeatability is an essential prerequisite before implementation. In this manuscript we identified whole-body MRI radiomics features in prostate cancer bone disease with good inter- and intra-patient repeatability. These features may be further explored to improve outcome predictions and therapy response assessment in prostate cancer patients. (1) Background: We assessed the test–re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day. Apparent diffusion coefficient (ADC) and relative fat-fraction-percentage (rFF%) maps were calculated. Per study, up to 10 target bone metastases were manually delineated on DWI and Dixon images. All 106 radiomic features included in the Pyradiomics toolbox were derived for each target volume from the ADC and rFF% maps. To account for inter- and intra-patient measurement repeatability, the log-transformed individual target measurements were fitted to a hierarchical model, represented as a Bayesian network. Repeatability measurements, including the intraclass correlation coefficient (ICC), were derived. Feature ICCs were compared with mean ADC and rFF ICCs. (3) Results: A total of 65 DWI and 47 rFF% targets were analysed. There was no significant bias for any features. Pairwise correlation revealed fifteen ADC and fourteen rFF% feature sub-groups, without specific patterns between feature classes. The median intra-patient ICC was generally higher than the inter-patient ICC. Features that describe extremes in voxel values (minimum, maximum, range, skewness, and kurtosis) showed generally lower ICCs. Several mostly shape-based texture features were identified, which showed high inter- and intra-patient ICCs when compared with the mean ADC or mean rFF%, respectively. (4) Conclusions: Pyradiomics texture features of mCRPC bone metastases varied greatly in inter- and intra-patient repeatability. Several features demonstrated good repeatability, allowing for further exploration as diagnostic parameters in mCRPC bone disease. [ABSTRACT FROM AUTHOR]

Simple Summary: Radiotherapy is primordial in the local control strategy for soft tissue sarcomas. A complete response to preoperative RT is associated with a gain in survival. It, therefore, appears useful to identify in an early and non-invasive manner which patients will present such a response profile. During a single NETSARC-center retrospective study, we investigated and identified pre-therapeutic multimodal MRI parameters in line with the histological response (fibrosis and necrosis). These parameters must be prospectively validated in the hope of personalizing STS's local control strategy. Background: RT-induced hyalinization/fibrosis was recently evidenced as a significant independent predictor for complete response to neoadjuvant radiotherapy (RT) and survival in patients with soft tissue sarcoma (STS). Purpose: Non-invasive predictive markers of histologic response after neoadjuvant RT of STS are expected. Materials and Methods: From May 2010 to April 2017, patients with a diagnosis of STS who underwent neoadjuvant RT for limb STS were retrieved from a single center prospective clinical imaging database. Tumor Apparent Diffusion Coefficients (ADC) and areas under the time-intensity perfusion curve (AUC) were compared with the histologic necrosis ratio, fibrosis, and cellularity in post-surgical specimens. Results: We retrieved 29 patients. The median ADC value was 134.3 × 10−3 mm2/s. ADC values positively correlated with the post-treatment tumor necrosis ratio (p = 0.013). Median ADC values were lower in patients with less than 50% necrosis and higher in those with more than 50% (120.3 × 10−3 mm2/s and 202.0 × 10−3 mm2/s, respectively (p = 0.020). ADC values higher than 161 × 10−3 mm2/s presented a 95% sensitivity and a 55% specificity for the identification of tumors with more than 50% tumor necrosis ratio. Tumor-to-muscle AUC ratios were associated with histologic fibrosis (p = 0.036). Conclusions: ADC and perfusion AUC correlated, respectively, with radiation-induced tumor necrosis and fibrosis. [ABSTRACT FROM AUTHOR]

Simple Summary: Accurate assessment of the presence and progression of bone metastases will guide individual treatment plans. Sophisticated cross-sectional imaging techniques, such as magnetic resonance diffusion-weighted imaging (DWI), have gained favor due to their superior soft tissue contrast and resolution without the need for ionizing radiation. Many DWIS are available on clinical scanners, which show promise for objective assessment of bone metastases. Background: The purpose of this study is to compare turbo spin echo diffusion-weighted images in radial trajectory (BLADE DWI) with multi-shot echoplanar imaging (RESOLVE DWI) for imaging the metastatic lesion in the pelvic bone to find a correlation between ADC values and standardized uptake values (SUVs) of FDG uptake in PET/CT. The study also seeks to compare the values of metastatic lesions with those of benign bone lesions, specifically red marrow hyperplasia. Methods: The retrospective IRB-approved study included patients with bone metastasis and red marrow hyperplasia in the pelvic bone who underwent 3.0 T MRI with BLADE/RESOLVE DWI sequences and F-18 FDG PET/CT within one month. BVC (best value comparator) was used in determining the nature of bone lesions. Apparent diffusion coefficient (ADC) and standardized uptake value (SUV) were measured by a radiologist and a nuclear medicine physician. MRI image quality was graded with a Likert scale regarding the visualization of the sacroiliac joint, sacral neural foramen, hamstring tendon at ischial tuberosity, and tumor border. Signal-to-noise ratio (SNR) and imaging time were compared between the two DWIs. Mean, peak, and maximum SUVs between metastatic and benign red marrow lesions were compared. SUVs and ADC values were compared. AUROC analyses and cut-off values were obtained for each parameter. Mann–Whitney U, Spearman's rho, and Kolmogorov–Smirnov tests were applied using SPSS. Results: The final study group included 58 bone lesions (19 patients (male: female = 6:13, age 52.5 ± 9.6, forty-four (75.9%) bone metastasis, fourteen (24.1%) benign red marrow hyperplasia). ADCs from BLADE and RESOLVE were significantly higher in bone metastasis than red marrow hyperplasia. BLADE showed higher ADC values, higher anatomical scores, and higher SNR than RESOLVE DWI (p < 0.05). Imaging times were longer for BLADE than RESOLVE (6 min 3 s vs. 3 min 47 s, p < 0.05). There was a poor correlation between ADC values and SUVs (correlation coefficient from 0.04 to 0.31). The AUROC values of BLADE and RESOLVE MRI ranged from 0.892~0.995. Those of PET ranged from 0.877~0.895. The cut-off ADC values between the bone metastasis and red marrow hyperplasia were 355.0, 686.5, 531.0 for BLADE min, max, and average, respectively, and 112.5, 737.0, 273.0 for RESOLVE min, max, and average, respectively. The cut-off SUV values were 1.84, 5.01, and 3.81 for mean, peak, and max values, respectively (p < 0.05). Conclusions: Compared with RESOLVE DWI, BLADE DWI showed improved image quality of pelvic bone MRI in the aspect of anatomical depiction and SNR, higher ADC values, albeit longer imaging time. BLADE and RESOLVE could differentiate bone metastasis and red marrow hyperplasia with quantifiable cut-off values. Further study is necessary to evaluate the discrepancy between the quantifiers between PET and MRI. [ABSTRACT FROM AUTHOR]

Simple Summary: The treatment of malignant liver tumors can be very challenging, especially in cases of metastatic disease. Systemic chemotherapy is most commonly used in such cases. However, liver metastases can also be treated by various interventional treatments including thermal ablation or TACE, depending on the hepatic tumor burden. This prospective, randomized study aims to compare DSM-TACE with Lipiodol + DSM TACE for patients with liver metastases from pancreatic cancer according to the volume and diameter of metastases, ADC values, and survival time of both groups after treatment of three TACE sessions. The treatment response of both cohorts will be assessed using RECIST 1.1. To evaluate and compare the outcome of patients with liver metastases from pancreatic cancer treated by transarterial chemoembolization (TACE) using two different protocols. In this prospective, randomized, single-center trial, patients were randomly assigned to receive TACE therapy either with degradable starch microspheres (DSM) alone or a combination of Lipiodol and DSM. From the initial 58 patients, 26 patients (13 DSM-TACE, 13 Lipiodol + DSM-TACE) who completed 3 TACE treatments at an interval of four weeks were considered for evaluation of tumor responses. Initial and final MRIs were used to evaluate local therapy response by RECIST 1.1; changes in diameter, volume, ADC value, and survival rate were statistically evaluated. The differences between the DSM-TACE and Lipiodol + DSM-TACE were identified for partial response (PR) as 15.4% versus 53.8%, stable disease (SD) as 69.2% versus 46.2%, progressive disease (PD) as 15.4% versus 0%, respectively (p = 0.068). Median overall survival times for DSM-TACE and Lipiodol + DSM-TACE were 20 months (95% CI, 18.1–21.9) and 23 months (95% CI, 13.8–32.2), respectively (p = 0.565). The one-year survival rates for DSM-TACE and Lipiodol + DSM-TACE were 85.4% and 60.4%, the two-year survival rates were 35.9% and 47.7%, and the three-year survival rates were 12% and 30.9%, respectively. The evaluated local therapy response by RECIST 1. was not significantly different between the two studied groups. A longer overall survival time was observed after Lipiodol + DSM-TACE therapy; however, it was not significantly different. [ABSTRACT FROM AUTHOR]

User decision-making concerning critical operations is very important to nuclear power plant (NPP) safety. The NPP interface is the main information source that guides decision-making; thus, a good interface design is essential. Among the interface design factors such as interface complexity, layout and colour, interface complexity (the amount of information in the interface) has the greatest impact on NPP operator decision-making. This paper used the event-related potential (ERP) to evaluate the impact of interface complexity on user decision-making and found interface complexity has a specific range suitable for decision-making. Based on this important finding, a fast and economical method of evaluating NPP interfaces in all design phases was proposed. This method compensates for the shortcomings of traditional methods, such as heuristic evaluation and experimental evaluation, which are inconvenient for evaluating interfaces in initial design phase; it can also be applied to interfaces with similar features in other industrial fields. Practitioner summary: Evaluation of the impact of NPP interface complexity on user decision-making through an ERP experiment revealed a specific range of interface complexity that facilitates user decision-making. Based on this finding, a new, fast and inexpensive interface evaluation method was proposed. Abbreviations: NPP: nuclear power plant, it is a thermal power station in which the heat source is a nuclear reactor; ERP: event-related potential, it is the measured brain response that is the direct result of a specific cognitive, or motor event. [ABSTRACT FROM AUTHOR]

Simple Summary: Patients with many advanced cancers develop osteoblastic bone metastases that cannot be assessed by conventional imaging. There is an unmet need for a quantitative imaging technique that can assess the treatment response of osteoblastic metastases to further improve treatment of these patients. This article examines the difference in apparent diffusion coefficient (ADC) values found between viable and nonviable metastases in relation to the variability of repeated measurements as a basis for the potential use of diffusion-weighted MRI (DWI) for treatment response assessment. DWI is based on observing the movement of water molecules, which is often restricted in tumor tissue and is quantified using the ADC. It is shown that viable and nonviable metastases differ significantly in ADC value and that these differences are considerably higher than the variability of repeated measurements. This shows that DWI meets the basic technical requirements for reliable treatment response assessment of osteoblastic metastases. The apparent diffusion coefficient (ADC) is a candidate marker of treatment response in osteoblastic metastases that are not evaluable by morphologic imaging. However, it is unclear whether the ADC meets the basic requirement for reliable treatment response evaluation, namely a low variance of repeated measurements in relation to the differences found between viable and nonviable metastases. The present study addresses this question by analyzing repeated in vivo ADCmedian measurements of 65 osteoblastic metastases in nine patients, as well as phantom measurements. PSMA-PET served as a surrogate for bone metastasis viability. Measures quantifying repeatability were calculated and differences in mean ADC values according to PSMA-PET status were examined. The relative repeatability coefficient %RC of ADCmedian measurements was 5.8% and 12.9% for phantom and in vivo measurements, respectively. ADCmedian values of bone metastases ranged from 595 × 10 − 6 mm 2 / s to 2090 × 10 − 6 mm 2 / s with an average of 63% higher values in nonviable metastases compared with viable metastases (p < 0.001). ADC shows a small repeatability coefficient in relation to the difference in ADC values between viable and nonviable metastases. Therefore, ADC measurements fulfill the technical prerequisite for reliable treatment response evaluation in osteoblastic metastases. [ABSTRACT FROM AUTHOR]

Simple Summary: We hypothesised that change in a magnetic resonance imaging (MRI) biomarker, the apparent diffusion coefficient (ADC) after 14 days of treatment could be a proxy for tumour regression grade (TRG) on pathology. Measurement of the imaging biomarker was standardised across centres. We restricted measurements to liver metastases from colorectal cancer and ensured a standardised chemotherapy approach. We identified and eliminated significant measurement error due to MRI scanner performance. We excluded studies that failed to conform to the imaging protocol or where images contained movement artefact. We ensured stability of the scanners by periodic quality control testing and used a standard, widely used data analysis technique to derive the ADC. Despite these measures, our results showed no significant correlation between ADC and TRG or between ADC and percentage of viable tumour, percentage necrosis, percentage fibrosis or a tumour proliferation index. This may reflect the complex cellular architecture of tumours after treatment. Background: Tumour apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (MRI) is a putative pharmacodynamic/response biomarker but the relationship between drug-induced effects on the ADC and on the underlying pathology has not been adequately defined. Hypothesis: Changes in ADC during early chemotherapy reflect underlying histological markers of tumour response as measured by tumour regression grade (TRG). Methods: Twenty-six patients were enrolled in the study. Baseline, 14 days, and pre-surgery MRI were performed per study protocol. Surgical resection was performed in 23 of the enrolled patients; imaging-pathological correlation was obtained from 39 lesions from 21 patients. Results: There was no evidence of correlation between TRG and ADC changes at day 14 (study primary endpoint), and no significant correlation with other ADC metrics. In scans acquired one week prior to surgery, there was no significant correlation between ADC metrics and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki67 index. Conclusions: Our hypothesis was not supported by the data. The lack of meaningful correlation between change in ADC and TRG is a robust finding which is not explained by variability or small sample size. Change in ADC is not a proxy for TRG in metastatic colorectal cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: After treatment, glioblastoma typically recurs. In some patients with recurrent glioblastoma, bevacizumab improves progression-free survival. The magnetic resonance texture analysis quantifies the macroscopic tissue heterogeneity that is indirectly linked to the microscopic tissue properties. In 33 patients with recurrent glioblastoma who were treated with bevacizumab, we evaluated the predictive value of magnetic resonance texture analysis for survival. Volumes of contrast-enhancing lesions segmented on postcontrast T1-weighted sequences were co-registered with apparent diffusion coefficient maps in order to extract 107 radiomic features. We found that some features derived from texture analysis accurately predicted survival. Identifying pretreatment imaging biomarkers that predict outcomes following bevacizumab therapy for recurrent glioblastoma can be beneficial for selecting patients most likely to benefit from this costly treatment. These promising preliminary results may be a small but significant step toward demonstrating the clinical relevance of radiomic profiles in the treatment of this disease. Purpose: Glioblastoma often recurs after treatment. Bevacizumab increases progression-free survival in some patients with recurrent glioblastoma. Identifying pretreatment predictors of survival can help clinical decision making. Magnetic resonance texture analysis (MRTA) quantifies macroscopic tissue heterogeneity indirectly linked to microscopic tissue properties. We investigated the usefulness of MRTA in predicting survival in patients with recurrent glioblastoma treated with bevacizumab. Methods: We evaluated retrospective longitudinal data from 33 patients (20 men; mean age 56 ± 13 years) who received bevacizumab on the first recurrence of glioblastoma. Volumes of contrast-enhancing lesions segmented on postcontrast T1-weighted sequences were co-registered on apparent diffusion coefficient maps to extract 107 radiomic features. To assess the performance of textural parameters in predicting progression-free survival and overall survival, we used receiver operating characteristic curves, univariate and multivariate regression analysis, and Kaplan–Meier plots. Results: Longer progression-free survival (>6 months) and overall survival (>1 year) were associated with lower values of major axis length (MAL), a lower maximum 2D diameter row (m2Ddr), and higher skewness values. Longer progression-free survival was also associated with higher kurtosis, and longer overall survival with higher elongation values. The model combining MAL, m2Ddr, and skewness best predicted progression-free survival at 6 months (AUC 0.886, 100% sensitivity, 77.8% specificity, 50% PPV, 100% NPV), and the model combining m2Ddr, elongation, and skewness best predicted overall survival (AUC 0.895, 83.3% sensitivity, 85.2% specificity, 55.6% PPV, 95.8% NPV). Conclusions: Our preliminary analyses suggest that in patients with recurrent glioblastoma pretreatment, MRTA helps to predict survival after bevacizumab treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Myxofibrosarcomas (MFS) are malignant soft tissue tumors, frequently located in the extremities. Owing to the infiltrative growth pattern of MFS, neoadjuvant radiotherapy (nRT) is commonly used before surgery to improve local control. Nevertheless, high local recurrence rates are typical in MFS. Data on prognostic factors for poor clinical outcomes are lacking. This retrospective study investigates the prognostic relevance of magnetic resonance imaging (MRI) characteristics before and after nRT in 40 MFS patients. The presence of a vascular pedicle, defined as extra-tumoral vessels at the tumor periphery, was prognostic for both worse disease-free survival (DFS) and overall survival. Additionally, the presence of an infiltrative pattern, referred to as a tail sign, was prognostic for worse DFS. These MRI characteristics could support the identification of patients at risk for poor clinical outcomes after nRT. To improve local control, neoadjuvant radiotherapy (nRT) followed by surgery is the standard of care in myxofibrosarcoma (MFS) because of its infiltrative growth pattern. Nevertheless, local recurrence rates are high. Data on prognostic factors for poor clinical outcomes are lacking. This retrospective study thus investigates the prognostic relevance of magnetic resonance imaging (MRI) characteristics before and after nRT in 40 MFS patients, as well as their association with disease-free survival (DFS) and overall survival (OS). A vascular pedicle, defined as extra-tumoral vessels at the tumor periphery, was observed in 12 patients (30.0%) pre-nRT and remained present post-nRT in all cases. Patients with a vascular pedicle had worse DFS (HR 5.85; 95% CI 1.56–21.90; p = 0.009) and OS (HR 9.58; 95% CI 1.91–48.00; p = 0.006). An infiltrative growth pattern, referred to as a tail sign, was observed in 22 patients (55.0%) pre-nRT and in 19 patients (47.5%) post-nRT, and was associated with worse DFS post-nRT (HR 6.99; 95% CI 1.39–35.35; p = 0.019). The percentage of tumor necrosis estimated by MRI was increased post-nRT, but was not associated with survival outcomes. The presence of a tail sign or vascular pedicle on MRI could support the identification of patients at risk for poor clinical outcomes after nRT. [ABSTRACT FROM AUTHOR]

Simple Summary: Although the extensive use of highly active oncological treatments has led to an increased rate of secondary resections in patients with colorectal liver metastases, it has led to questions regarding the correct surgical management of disappearing liver metastases (DLM) and small residual lesions during chemotherapy. Our study aimed to evaluate the clinical outcome of DLM and small remnant liver metastases (≤10 mm) assessed by means of hepatobiliary contrast-enhanced and diffusion-weighted MR imaging (DW-MRI) in metastatic colorectal cancer patients with first-line chemotherapy treatment in order to support the clinical management and decision-making process for these liver lesions. Our results showed that DLM assessed via hepatobiliary contrast-enhanced and DW-MRI very probably indicate a complete response in patients without chemotherapy-induced sinusoidal obstruction syndrome. In these patients, a follow-up with liver MRI can be considered, and resection should be performed in the case of disease relapse. The surgical removal of small remnants of liver metastases should always be advocated whenever technically possible. We aimed to evaluate the outcome of the disappearance or small remnants of colorectal liver metastases during first-line chemotherapy assessed by hepatobiliary contrast-enhanced and diffusion-weighted MR imaging (DW-MRI). Consecutive patients with at least one disappearing liver metastasis (DLM) or small residual liver metastases (≤10 mm) assessed by hepatobiliary contrast-enhanced and DW-MRI during first-line chemotherapy were included. Liver lesions were categorized into three groups: DLM; residual tiny liver metastases (RTLM) when ≤5 mm; small residual liver metastases (SRLM) when >5mm and ≤10 mm. The outcome of resected liver metastases was assessed in terms of pathological response, whereas lesions left in situ were evaluated in terms of local relapse or progression. Fifty-two outpatients with 265 liver lesions were radiologically reviewed; 185 metastases fulfilled the inclusion criteria: 40 DLM, 82 RTLM and 60 SRLM. We observed a pCR rate of 75% (3/4) in resected DLM and 33% (12/36) of local relapse for DLM left in situ. We observed a risk of relapse of 29% and 57% for RTLM and SRLM left in situ, respectively, and a pCR rate of about 40% overall for resected lesions. DLM assessed via hepatobiliary contrast-enhanced and DW-MRI very probably indicates a complete response. The surgical removal of small remnants of liver metastases should always be advocated whenever technically possible. [ABSTRACT FROM AUTHOR]

Simple Summary: Neoadjuvant systemic therapy (NAST) is given before surgery to reduce tumor burden in patients with triple-negative breast cancer (TNBC), which is an aggressive breast cancer subtype that accounts for approximately 30% of breast cancer-related mortalities. Unfortunately, approximately 50% of TNBC patients do not respond to NAST and develop distant spread within 5 years. Reliable clinical methods are needed to determine non-responders to NAST in order to avoid the severe toxicity of ineffective regimens and offer novel targeted treatments. The purpose of this study was to investigate functional tumor volume measured from dynamic contrast-enhanced MRI for early assessment of NAST response in TNBC. Our study demonstrated the potential of functional tumor volume, evaluated as early as after 2 and 4 cycles of NAST, to serve as a non-invasive biomarker for the prediction of treatment response in TNBC patients. Early assessment of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) is critical for patient care in order to avoid the unnecessary toxicity of an ineffective treatment. We assessed functional tumor volumes (FTVs) from dynamic contrast-enhanced (DCE) MRI after 2 cycles (C2) and 4 cycles (C4) of NAST as predictors of response in TNBC. A group of 100 patients with stage I-III TNBC who underwent DCE MRI at baseline, C2, and C4 were included in this study. Tumors were segmented on DCE images of 1 min and 2.5 min post-injection. FTVs were measured using the optimized percentage enhancement (PE) and signal enhancement ratio (SER) thresholds. The Mann–Whitney test was used to compare the performance of the FTVs at C2 and C4. Of the 100 patients, 49 (49%) had a pathologic complete response (pCR) and 51 (51%) had a non-pCR. The maximum area under the receiving operating characteristic curve (AUC) for predicting the treatment response was 0.84 (p < 0.001) for FTV at C4 followed by FTV at C2 (AUC = 0.82, p < 0.001). The FTV measured at baseline was not able to discriminate pCR from non-pCR. FTVs measured on DCE MRI at C2, as well as at C4, of NAST can potentially predict pCR and non-pCR in TNBC patients. [ABSTRACT FROM AUTHOR]

Simple Summary: Achieving pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer (BC) is crucial, as pCR is a surrogate marker for survival. However, only 10–30% of patients achieve it. It is therefore essential to develop tools that enable to accurately predict response. Recently, different studies have demonstrated the feasibility of applying machine learning approaches to non-invasively predict pCR before NAC administration from magnetic resonance imaging (MRI) data. Some of those models are based on radiomics, an emerging field that allows the automated extraction of clinically relevant information from radiologic images. However, the research is still at an early stage and further data are needed. Here, we determine whether the combination of imaging data (radiomic features and perfusion/diffusion imaging biomarkers) extracted from multiparametric MRIs and clinical variables can improve pCR prediction to NAC compared to models only including imaging or clinical data, potentially avoiding unnecessary treatment and delays to surgery. Background: Most breast cancer (BC) patients fail to achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). The aim of this study was to evaluate whether imaging features (perfusion/diffusion imaging biomarkers + radiomic features) extracted from pre-treatment multiparametric (mp)MRIs were able to predict, alone or in combination with clinical data, pCR to NAC. Methods: Patients with stage II-III BC receiving NAC and undergoing breast mpMRI were retrospectively evaluated. Imaging features were extracted from mpMRIs performed before NAC. Three different machine learning models based on imaging features, clinical data or imaging features + clinical data were trained to predict pCR. Confusion matrices and performance metrics were obtained to assess model performance. Statistical analyses were conducted to evaluate differences between responders and non-responders. Results: Fifty-eight patients (median [range] age, 52 [45–58] years) were included, of whom 12 showed pCR. The combined model improved pCR prediction compared to clinical and imaging models, yielding 91.5% of accuracy with no false positive cases and only 17% false negative results. Changes in different parameters between responders and non-responders suggested a possible increase in vascularity and reduced tumour heterogeneity in patients with pCR, with the percentile 25th of time-to-peak (TTP), a classical perfusion parameter, being able to discriminate both groups in a 75% of the cases. Conclusions: A combination of mpMRI-derived imaging features and clinical variables was able to successfully predict pCR to NAC. Specific patient profiles according to tumour vascularity and heterogeneity might explain pCR differences, where TTP could emerge as a putative surrogate marker for pCR. [ABSTRACT FROM AUTHOR]

Simple Summary: For personalized treatment of metastatic spinal cord compression (MSCC), a patient's remaining lifespan plays an important role, which can be estimated using prognostic factors. This study used data from 190 patients with poor or intermediate survival prognoses previously included in prospective trials to evaluate the prognostic role of preclinical markers including hemoglobin, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lactate dehydrogenase (LDH), and c-reactive protein (CRP) plus clinical factors. On univariate analyses, NLR, LDH, CRP, and clinical factors tumor type, ambulatory status, and sphincter function were significantly associated with survival. On multivariate analysis, LDH, CRP, tumor type, and ambulatory status proved to be independent predictors of survival. In addition to clinical factors, preclinical markers may support physicians to estimate survival prognoses and contribute to the treatment personalization of patients with MSCC. For optimal personalization of treatment for metastatic spinal cord compression (MSCC), the patient's survival prognosis should be considered. Estimation of survival can be facilitated by prognostic factors. This study investigated the prognostic value of pre-treatment preclinical markers, namely hemoglobin, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lactate dehydrogenase (LDH), and c-reactive protein (CRP), in 190 patients from two prospective trials who had poor or intermediate survival prognoses and were irradiated for MSCC with motor deficits. In addition, clinical factors including radiation regimen, age, gender, tumor type, interval from tumor diagnosis to MSCC, number of affected vertebrae, visceral metastases, other bone metastases, time developing motor deficits, ambulatory status, sensory function, and sphincter function were evaluated. On univariate analyses, NLR (p = 0.033), LDH (p < 0.001), CRP (p < 0.001), tumor type (p < 0.001), pre-radiotherapy ambulatory status (p < 0.001), and sphincter function (p = 0.011) were significant. In the subsequent Cox regression analysis, LDH (p = 0.007), CRP (p = 0.047), tumor type (p = 0.003), and ambulatory status (p = 0.010) maintained significance. In addition to clinical factors, preclinical markers may help in estimating the survival of patients irradiated for MSCC. Additional prospective trials are warranted. [ABSTRACT FROM AUTHOR]

Aims:Workforce entry is a key transition period. It offers an ideal, but under-utilised opportunity to implement intervention strategies to prevent mental health and substance use problems among young people. A brief psychological wellbeing and substance use intervention targeting a high-risk group – apprentice chefs – was undertaken to explore this opportunity.Method:A RCT design (N = 71) was used. The intervention group received two face-to-face sessions, and controls received five related information sheets during the first 2 weeks of training, with 4-month follow-up.Results:These apprentices were a high-risk group for alcohol and other drug harm and poor psychological wellbeing. At T1, 70% of the participants had AUDIT scores indicating problem drinking; 28% had used cannabis and 18% had used amphetamines in the last 12 months; and 24% had high K10 scores. At T2, the intervention group had significantly reduced risky alcohol use (p = 0.008), improved psychological distress (p = 0.045) and ability to talk with supervisors about work issues (p = 0.001) and cope with work stress (p = 0.001) and verbal abuse (p = 0.005), compared to the control group.Conclusions:Brief tailored interventions, delivered in an occupational training environment, have potential to reduce substance use risk and enhance young workers’ psychological wellbeing. [ABSTRACT FROM PUBLISHER]

Imagery can improve sport performance, although its efficacy is mediated by the ease with which athletes can generate images. Establishing techniques that improve this imagery ability factor is desirable to enhance the effectiveness of imagery interventions. Twenty-seven club-level female golfers were assigned to imagery, action observation, or physical practice training groups (n= 9). Changes in image generation ease were assessed using the Revised Movement Imagery Questionnaire over an 8-week period. Imagery and action observation training were both effective in improving aspects of imagery ability. Action observation can provide sport psychologists with an effective tool for improving visual imagery ability in athletes. [ABSTRACT FROM AUTHOR]

Aims To examine changes in illicit drug consumption between peak holiday season (23 December-3 January) in Australia and a control period two months later in a coastal urban area, an inland semi-rural area and an island populated predominantly by vacationers during holidays. Design Analysis of representative daily composite wastewater samples collected from the inlet of the major wastewater treatment plant in each area. Setting Three wastewater treatment plants. Participants Wastewater treatment plants serviced approximately 350 000 persons in the urban area, 120 000 in the semi-rural area and 1100-2400 on the island. Measurements Drug residues were analysed using liquid chromatography coupled to a tandem mass spectrometer. Per capita drug consumption was estimated. Changes in drug use were quantified using Hedges' g. Findings During the holidays, cannabis consumption in the semi-rural area declined (g = −2.8) as did methamphetamine (−0.8), whereas cocaine (+1.5) and ecstasy (+1.6) use increased. In the urban area, consumption of all drugs increased during holidays (cannabis +1.6, cocaine +1.2, ecstasy +0.8 and methamphetamine +0.3). In the vacation area, methamphetamine (+0.7), ecstasy (+0.7) and cocaine (+1.1) use increased, but cannabis (−0.5) use decreased during holiday periods. Conclusions While the peak holiday season in Australia is perceived as a period of increased drug use, this is not uniform across all drugs and areas. Substantial declines in drug use in the semi-rural area contrasted with substantial increases in urban and vacation areas. Per capita drug consumption in the vacation area was equivalent to that in the urban area, implying that these locations merit particular attention for drug use monitoring and harm minimisation measures. [ABSTRACT FROM AUTHOR]

Simple Summary: Among various types of head and neck cancers, nasopharyngeal carcinoma (NPC) has a distinct epidemiology and prognosis. Tumor recurrence in NPC poses significant clinical challenges and identifying novel prognostic biomarkers is crucial. Imaging biomarkers derived from positron emission tomography (PET) and magnetic resonance imaging (MRI) reflect different biological facets of tumors. However, whether pretreatment PET and MRI imaging biomarkers can complement each other in the survival prediction of NPC patients has not been determined. This prospective study aimed to analyze the prognostic value of imaging biomarkers derived from pretreatment MRI and PET in NPC. The model integrating the MRI perfusion markers with PET metabolic parameter demonstrated higher prognostic performance than the traditional staging system and individual model with either MRI or PET alone. A staging work-up for NPC including both functional MRI and PET parameters may provide clinicians with supplementary prognostic information in addition to morphologic assessment of tumor extent. We prospectively investigated the prognostic value of imaging parameters for nasopharyngeal carcinoma (NPC) using dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging (DWI), and 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography (18F-FDG PET)/computed tomography (CT). Patients with stage III–IVb NPC underwent F-FDG PET/CT, DCE-MRI, and DWI before treatment. Kaplan-Meier and Cox-regression analyses were used to assess associations of PET and MRI imaging biomarkers with overall survival (OS) and recurrence-free survival (RFS). We used independent prognosticators to establish prognostic models; model performance was examined using Harrell's concordance index (c-index). Sixty-one patients were available for analysis, as 13 patients died and 20 experienced recurrence. Total lesion glycolysis (TLG) (p = 0.002) from PET/CT and the initial area under the curve (iAUC) (p = 0.036) from DCE-MRI were identified as independent prognosticators of OS; Epstein-Barr virus (EBV) DNA (p = 0.027), the extracellular volume fraction (Ve) (p = 0.027) from DCE-MRI, and TLG/iAUC (p = 0.025) were significant predictors of RFS. The c-indices of the prognostic models incorporating TLG + iAUC in predicting OS and incorporating EBV DNA + Ve + TLG/iAUC in predicting RFS were 0.79 and 0.76, respectively. These were significantly higher than the corresponding c-indices of the TNM staging system (p = 0.047 and 0.025, respectively); they were also higher than those of models with only MRI or PET biomarkers. In conclusion, the combination of pretreatment DCE-MRI and 18F-FDG PET/CT imaging biomarkers helps survival prediction in advanced NPC. Integrating MRI perfusion with PET metabolism and plasma EBV information may aid clinicians in planning the optimal personalized management strategy. [ABSTRACT FROM AUTHOR]

Simple Summary: Confirming whether a breast lesion is benign or malignant usually involves an invasive tissue sample with an image-guided breast biopsy, which may cause substantial inconvenience to the patient. The purpose of this study was to investigate whether imaging biomarkers obtained from noninvasive dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast can help differentiate benign from malignant lesions and characterize breast cancers to the same extent as a biopsy. In a sample of 37 patients with suspicious findings on mammography or ultrasound, we found that the radiologists' diagnostic accuracy was improved when subjective Breast Imaging-Reporting and Data System (BI-RADS) evaluation was augmented with the use of pharmacokinetic markers. This study serves as a starting point for future collaborative research with the potential of providing valuable noninvasive tools for improved breast cancer diagnosis. The purpose of this study was to investigate whether ultra-high-field dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast at 7T using quantitative pharmacokinetic (PK) analysis can differentiate between benign and malignant breast tumors for improved breast cancer diagnosis and to predict molecular subtypes, histologic grade, and proliferation rate in breast cancer. In this prospective study, 37 patients with 43 lesions suspicious on mammography or ultrasound underwent bilateral DCE-MRI of the breast at 7T. PK parameters (KTrans, kep, Ve) were evaluated with two region of interest (ROI) approaches (2D whole-tumor ROI or 2D 10 mm standardized ROI) manually drawn by two readers (senior reader, R1, and R2) independently. Histopathology served as the reference standard. PK parameters differentiated benign and malignant lesions (n = 16, 27, respectively) with good accuracy (AUCs = 0.655–0.762). The addition of quantitative PK analysis to subjective BI-RADS classification improved breast cancer detection from 88.4% to 97.7% for R1 and 86.04% to 97.67% for R2. Different ROI approaches did not influence diagnostic accuracy for both readers. Except for KTrans for whole-tumor ROI for R2, none of the PK parameters were valuable to predict molecular subtypes, histologic grade, or proliferation rate in breast cancer. In conclusion, PK-enhanced BI-RADS is promising for the noninvasive differentiation of benign and malignant breast tumors. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer is currently the fifth leading cause of death in men worldwide. To personalize and guide treatment in prostate cancer, identification of druggable genomic alterations is of major importance. Prostate cancer often metastasizes solely or predominantly to the bones, with molecular analyses on bone biopsies challenging due to technical difficulties to identify and obtain biopsies from high tumor cell containing locations. In our retrospective analysis, we showed a significantly higher success rate in patients where biopsy location was selected by a prior PSMA PET-CT compared to solely CT or MRI. CT-guided biopsies in locations with low Hounsfield units (HUs) and deviation of HUs were associated with a higher proportion of successful histological and molecular biopsies. Based on these results, we designed a simple prediction model for daily clinical practice to increase the success rate of bone biopsies for molecular analyses in prostate cancer to guide precision medicine. Developing and optimizing targeted therapies in metastatic castration-resistant prostate cancer (mCRPC) necessitates molecular characterization. Obtaining sufficient tumor material for molecular characterization has been challenging. We aimed to identify clinical and imaging variables of imaging-guided bone biopsies in metastatic prostate cancer patients that associate with tumor yield and success in obtaining molecular results, and to design a predictive model: Clinical and imaging data were collected retrospectively from patients with prostate cancer who underwent a bone biopsy for histological and molecular characterization. Clinical characteristics, imaging modalities and imaging variables, were associated with successful biopsy results. In our study, we included a total of 110 bone biopsies. Histological conformation was possible in 84 of all biopsies, of which, in 73 of the 84, successful molecular characterization was performed. Prior use of PSMA PET-CT resulted in higher success rates in histological and molecular successful biopsies compared to CT or MRI. Evaluation of spine biopsies showed more often successful results compared to other locations for both histological and molecular biopsies (p = 0.027 and p = 0.012, respectively). Low Hounsfield units (HUs) and deviation (Dev), taken at CT-guidance, were associated with histological successful biopsies (p = 0.025 and p = 0.023, respectively) and with molecular successful biopsies (p = 0.010 and p = 0.006, respectively). A prediction tool combining low HUs and low Dev resulted in significantly more successful biopsies, histological and molecular (p = 0.023 and p = 0.007, respectively). Based on these results, we concluded that site selection for metastatic tissue biopsies with prior PSMA PET-CT imaging improves the chance of a successful biopsy. Further optimization can be achieved at CT-guidance, by selection of low HU and low Dev lesions. A prediction tool is provided to increase the success rate of bone biopsies in mCRPC patients, which can easily be implemented in daily practice. [ABSTRACT FROM AUTHOR]

Simple Summary: Imaging derived parameters can provide data on tumor phenotype as well as cancer microenvironment. Radiomics has recently shown potential in realizing personalized medicine. The aim of the manuscript is to detect RAS mutation in colorectal liver metastasis by Diffusion-Weighted Magnetic Resonance Imaging (DWI-MRI) - and Diffusion Kurtosis imaging (DKI)-derived parameters. We demonstrated that DKI derived parameters allows to detect RAS mutation in liver metastasis. Objectives: To detect RAS mutation in colorectal liver metastasis by Diffusion-Weighted Magnetic Resonance Imaging (DWI-MRI) - and Diffusion Kurtosis imaging (DKI)-derived parameters. Methods: In total, 106 liver metastasis (60 metastases with RAS mutation) in 52 patients were included in this retrospective study. Diffusion and perfusion parameters were derived by DWI (apparent diffusion coefficient (ADC), basal signal (S0), pseudo-diffusion coefficient (DP), perfusion fraction (FP) and tissue diffusivity (DT)) and DKI data (mean of diffusion coefficient (MD) and mean of diffusional Kurtosis (MK)). Wilcoxon–Mann–Whitney U tests for non-parametric variables and receiver operating characteristic (ROC) analyses were calculated with area under ROC curve (AUC). Moreover, pattern recognition approaches (linear classifier, support vector machine, k-nearest neighbours, decision tree), with features selection methods and a leave-one-out cross validation approach, were considered. Results: A significant discrimination between the group with RAS mutation and the group without RAS mutation was obtained by the standard deviation value of MK (MK STD), by the mean value of MD, and by that of FP. The best results were reached by MK STD with an AUC of 0.80 (sensitivity of 72%, specificity of 85%, accuracy of 79%) using a cut-off of 203.90 × 10−3, and by the mean value of MD with AUC of 0.80 (sensitivity of 84%, specificity of 73%, accuracy of 77%) using a cut-off of 1694.30 mm2/s × 10−6. Considering all extracted features or the predictors obtained by the features selection method (the mean value of S0, the standard deviation value of MK, FP and of DT), the tested pattern recognition approaches did not determine an increase in diagnostic accuracy to detect RAS mutation (AUC of 0.73 and 0.69, respectively). Conclusions: Diffusion-Weighted imaging and Diffusion Kurtosis imaging could be used to detect the RAS mutation in liver metastasis. The standard deviation value of MK and the mean value of MD were the more accurate parameters in the RAS mutation detection, with an AUC of 0.80. [ABSTRACT FROM AUTHOR]

Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at recurrence, at 2 months and 4 months before recurrence, and at 1 month after radiation therapy. The diffusion maps and T1 images were deformably registered longitudinally. The recurrent tumor was manually segmented on the T1-weighted image and then applied to the diffusion maps at each time point to collect mean FA, diffusivities, and neurite density index (NDI) values, respectively. Group analysis of variance showed significant changes in FA (p = 0.01) and NDI (p = 0.0015) over time. Pairwise t tests also revealed that FA and NDI at 2 months before recurrence were 11.2% and 6.4% lower than those at 1 month after radiation therapy (p < 0.05), respectively. Changes in FA and NDI were observed 2 months before recurrence, suggesting that progressive microstructural changes and neurite density loss may be detectable before tumor detection in anatomical MR images. FA and NDI may serve as non-contrast MR-based biomarkers for detecting subclinical tumors. [ABSTRACT FROM AUTHOR]