Cholangiocarcinoma imaging: from diagnosis to response assessment.

Cholangiocarcinoma (CCA), a highly aggressive primary liver cancer arising from the bile duct epithelium, represents a substantial proportion of hepatobiliary malignancies, posing formidable challenges in diagnosis and treatment. Notably, the global incidence of intrahepatic CCA has seen a rise, necessitating a critical examination of diagnostic and management strategies, especially due to presence of close imaging mimics such as hepatocellular carcinoma (HCC) and combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA). Hence, it is imperative to understand the role of various imaging modalities such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), elucidating their strengths, and limitations in diagnostic precision and staging accuracy. Beyond conventional approaches, there is emerging significance of functional imaging tools including positron emission tomography (PET)-CT and diffusion-weighted (DW)-MRI, providing pivotal insights into diagnosis, therapeutic assessment, and prognostic evaluation. This comprehensive review explores the risk factors, classification, clinical features, and role of imaging in the holistic spectrum of diagnosis, staging, management, and restaging for CCA, hence serving as a valuable resource for radiologists evaluating CCA.

Blood MALT1 expression could help predict treatment outcomes in psoriasis patients, especially in those receiving biologics.

INTRODUCTION: Mucosa-associated lymphoid tissue 1 (MALT1) modulates T helper cell differentiation, pro-inflammatory cytokine production, and epidermal hyperplasia to participate in the pathology of psoriasis. This study aimed to explore the correlation of blood MALT1 with treatment outcomes in psoriasis patients. METHODS: MALT1 was detected in peripheral blood mononuclear cells by reverse transcription-quantitative polymerase chain reaction in 210 psoriasis patients before starting or converting to a new therapy, 50 disease controls, and 50 healthy controls. The psoriasis area severity index (PASI) score was evaluated at month (M)1, M3, and M6 in psoriasis patients. RESULTS: MALT1 was increased in psoriasis patients versus disease controls and healthy controls (both p < .001); and positively related to body mass index (p = .019) and PASI score (p < .001) in psoriasis patients. PASI75 rate at M1, M3, and M6 was 22.9%, 46.2%, and 71.0%, respectively; while PASI90 rate at M1, M3, and M6 was 3.8%, 29.0%, and 50.5%, respectively, in psoriasis patients. PASI75/90 rates at M1, M3, and M6 were increased in psoriasis patients receiving biologics versus those without (all p < .05). Pretreatment MALT1 was higher in psoriasis patients who achieved PASI75 (p = .001) and PASI90 (p < .001) at M6 compared to those who did not achieve that. Subgroup analyses discovered that pretreatment MALT1 had a stronger ability to predict PASI75 and 90 realizations in psoriasis patients receiving biologics (area under the curve [AUC]: 0.723 and 0.808) versus those without (AUC: 0.594 and 0.675). CONCLUSION: Blood MALT1 measurement may assist in predicting outcomes in psoriasis patients, especially in those receiving biologics.

Sociodemographic, clinical and treatment characteristics of current rapid-cycling bipolar disorder: a multicenter Chinese study.

BACKGROUND: Rapid cycling bipolar disorder (RCBD), characterized by four or more episodes per year, is a complex subtype of bipolar disorder (BD) with poorly understood characteristics. METHOD: This multicenter, observational, longitudinal cohort study enrolled 520 BD patients across seven psychiatric institutions in China from January 2013 to January 2014. Participants were divided into RCBD and non-RCBD (NRCBD) groups based on the frequency of mood episodes in the preceding year. Data collection utilized a standardized form, supplemented by a medical record review, focusing on sociodemographic, clinical, and treatment characteristics. Statistical analysis involved independent samples t-tests, Kruskal-Wallis H tests, Chi-square or Fisher's exact tests, with Bonferroni correction applied to account for multiple comparisons, and multivariable logistic regression to identify characteristics associated with RCBD. RESULTS: Among the BD cohort, 9.4% were identified as current RCBD. Compared to NRCBD, RCBD patients had a shorter duration from the first psychiatric consultation to the diagnosis of BD, a reduced duration of their longest period of euthymia, a lower proportion of lifetime hospitalization history due to BD, and less use of electroconvulsive therapy (ECT) within the last 12 months. Additionally, they presented higher baseline scores on the Mood Disorder Questionnaire (MDQ) and the Brief 16-item Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR16). However, after applying the Bonferroni correction, these differences were not statistically significant. Multivariable logistic regression analysis identified three factors that were independently associated with RCBD: time from first psychiatric consultation to BD diagnosis (Odds Ratio [OR] = 0.512, P = 0.0416), lifetime hospitalization history due to BD (OR = 0.516, P = 0.0476), and ECT treatment within the past 12 months (OR = 0.293, P = 0.0472). CONCLUSION: This study revealed that the duration from first psychiatric consultation to BD diagnosis, lifetime hospitalization history due to BD, and ECT treatment in the past year were associated with RCBD. Recognizing these factors could contribute to enhance the early identification and clinical outcomes of RCBD. Trial Registration Number Registry ClinicalTrials.gov NCT01770704. Date of Registration: First posted on January 18, 2013.

Effectiveness of online group cognitive-behavior therapy for adolescents with obsessive-compulsive disorder: a pilot study.

OBJECTIVE: This study aims to evaluate the effectiveness of online group cognitive-behavioral therapy (GCBT) guided by the CAMALEO TOC manual in treating of adolescents with obsessive compulsive disorder (OCD). METHOD: A quasi-experimental study with a single group pre-posttest intervention. Over 12 weeks 11 adolescents aged 11 to 17 years with OCD received weekly online sessions of GCBT based on CAMALEO TOC manual. The Children's Yale-Brown Obsessive-Compulsive Scale was used to assess OCD symptoms severity, the Family accommodation scale for obsessive-compulsive disorder interviewer-rated for family accommodation, the Children's Depression Inventory to assess depression symptoms, the Revised Children's Manifest Anxiety Scale for anxiety, and the Multidimensional Student Life Satisfaction Scale to assess life satisfaction. RESULTS: OCD symptoms decreased significantly (d = -1.55). A strong effect size (d = -1.03) was also found for family accommodation. No significant difference in OCD symptoms and family accommodation scores were found when controlling for differences between being in psychotherapeutic treatment, medication use, or psychiatric comorbidities. There was also no evidence that the intervention was effective in reducing symptoms of depression, anxiety or improving quality of life. CONCLUSION: We demonstrate the feasibility of a short-term online GCBT as an effective treatment for adolescents with OCD.

Predicting responses to omalizumab in antihistamine-refractory chronic urticaria: A real-world longitudinal study.

Background: Treating chronic urticaria (CU) that is unresponsive to H1-antihistamines (H1AHs) is challenging, and the real-world effectiveness of omalizumab remains unclear. Objective: Our aim was to evaluate the real-world effectiveness of omalizumab, optimal response assessment timing, and predictive factors. Methods: Initially, 5535 patients with CU who were receiving at least 20 mg of loratadine daily for at least 6 months (January 2007-August 2021) were screened. Ultimately, 386 patients who had been receiving omalizumab add-on treatment for >6 months were followed-up for more than 2 years. Predictors of treatment response to omalizumab add-on therapy for patients with antihistamine-refractory CU were identified by using a generalized linear model. Results: In our retrospective cohort, omalizumab treatment showed cumulative response rates of 55.2% at 3 months, 71.0% at 6 months, and 81.4% at 9 months for patients with H1AH-refractory CU. Analysis of longitudinal responses to omalizumab treatment revealed 3 distinct clusters: favorable (cluster 1 [n = 158]), intermediate (cluster 2 [n =1 43]), and poor responses (cluster 3 [n = 85]). Subjects were categorized on the basis of whether they had achieved a complete response within 3 months; 213 early responders, 117 late responders, and 56 nonresponders were identified. The initial dose of omalizumab differed significantly among the 3 clusters. Low total IgE level (<40 kU/L) predicted nonresponse (odds ratio [OR] = 3.10 [P = .018]). Early responders were associated with a higher initial omalizumab dose (≥300 mg) (OR = 2.07 [P = .016]), higher basophil counts (OR = 2.0 [P = .014]), total IgE levels exceeding 798 kU/L (OR = 0.37 [P = .047]), and lower platelet-to-lymphocyte ratio (OR = 0.50 [P = .050]). Conclusion: Real-world data reveal 3 distinct clusters for response to omalizumab treatment; confirm low serum total IgE level (<40 kU/L) as a predictor of nonresponse; and identify potential biomarkers, including IgE level, basophil count, and PLR, for early responders.

Circumventing drug resistance in gastric cancer: A spatial multi-omics exploration of chemo and immuno-therapeutic response dynamics.

BACKGROUND: Gastric Cancer (GC) characteristically exhibits heterogeneous responses to treatment, particularly in relation to immuno plus chemo therapy, necessitating a precision medicine approach. This study is centered around delineating the cellular and molecular underpinnings of drug resistance in this context. METHODS: We undertook a comprehensive multi-omics exploration of postoperative tissues from GC patients undergoing the chemo and immuno-treatment regimen. Concurrently, an image deep learning model was developed to predict treatment responsiveness. RESULTS: Our initial findings associate apical membrane cells with resistance to fluorouracil and oxaliplatin, critical constituents of the therapy. Further investigation into this cell population shed light on substantial interactions with resident macrophages, underscoring the role of intercellular communication in shaping treatment resistance. Subsequent ligand-receptor analysis unveiled specific molecular dialogues, most notably TGFB1-HSPB1 and LTF-S100A14, offering insights into potential signaling pathways implicated in resistance. Our SVM model, incorporating these multi-omics and spatial data, demonstrated significant predictive power, with AUC values of 0.93 and 0.84 in the exploration and validation cohorts respectively. Hence, our results underscore the utility of multi-omics and spatial data in modeling treatment response. CONCLUSION: Our integrative approach, amalgamating mIHC assays, feature extraction, and machine learning, successfully unraveled the complex cellular interplay underlying drug resistance. This robust predictive model may serve as a valuable tool for personalizing therapeutic strategies and enhancing treatment outcomes in gastric cancer.

Inflammatory and subtype-dependent serum protein signatures predict survival beyond the ctDNA in aggressive B cell lymphomas.

BACKGROUND: Biological heterogeneity of large B cell lymphomas (LBCLs) is poorly captured by current prognostic tools, hampering optimal treatment decisions. METHODS: We dissected the levels of 1,463 serum proteins in a uniformly treated trial cohort of 109 patients with high-risk primary LBCL (ClinicalTrials.gov: NCT01325194) and correlated the profiles with molecular data from tumor tissue and circulating tumor DNA (ctDNA) together with clinical data. FINDINGS: We discovered clinically and biologically relevant associations beyond established clinical estimates and ctDNA. We identified an inflamed serum protein profile, which reflected host response to lymphoma, associated with inflamed and exhausted tumor microenvironment features and high ctDNA burden, and translated to poor outcome. We composed an inflammation score based on the identified inflammatory proteins and used the score to predict survival in an independent LBCL trial cohort (ClinicalTrials.gov: NCT03293173). Furthermore, joint analyses with ctDNA uncovered multiple serum proteins that correlate with tumor burden. We found that SERPINA9, TACI, and TARC complement minimally invasive subtype profiling and that TACI and TARC can be used to evaluate treatment response in a subtype-dependent manner in the liquid biopsy. CONCLUSIONS: Altogether, we discovered distinct serum protein landscapes that dissect the heterogeneity of LBCLs and provide agile, minimally invasive tools for precision oncology. FUNDING: This research was funded by grants from the Research Council of Finland, Finnish Cancer Organizations, Sigrid Juselius Foundation, University of Helsinki, iCAN Digital Precision Cancer Medicine Flagship, Orion Research Foundation sr, and Helsinki University Hospital.

Thyroid stimulating immunoglobulin concentration is associated with disease activity and predicts response to treatment with intravenous methylprednisolone in patients with Graves' orbitopathy.

Background: Thyroid stimulating immunoglobulins (TSI) play a central role in the pathogenesis of Graves' orbitopathy (GO), while soluble interleukin-2 receptor (sIL-2R) is a marker for T-cell activity. We investigated TSI and sIL-2R levels in relation to thyroid function, disease activity and severity and response to treatment with intravenous methylprednisolone (IVMP) in patients with GO. Methods: TSI (bridge-based TSI binding assay), sIL-2R, TSH and fT4 levels were measured in biobank serum samples from 111 GO patients (37 male, 74 female; mean age 49.2 years old) and 25 healthy controls (5 male, 20 female; mean age 39.8 years old). Clinical characteristics and response to treatment were retrospectively retrieved from patient files. Results: Higher sIL-2R levels were observed in GO patients compared to controls (p < 0.001). sIL-2R correlated with fT4 (r = 0.26), TSH (r = -0.40) and TSI (r = 0.21). TSI and sIL-2R concentrations were higher in patients with active compared to inactive GO (p < 0.001 and p < 0.05, respectively). Both TSI and sIL-2R correlated with total clinical activity score (CAS; r = 0.33 and r = 0.28, respectively) and with several individual CAS items. Cut-off levels for predicting active GO were 2.62 IU/L for TSI (AUC = 0.71, sensitivity 69%, specificity 69%) and 428 IU/mL for sIL-2R (AUC = 0.64, sensitivity 62%, specificity 62%). In multivariate testing higher TSI (p < 0.01), higher age (p < 0.001) and longer disease duration (p < 0.01) were associated with disease activity. TSI levels were higher in patients with a poor IVMP response (p = 0.048), while sIL-2R levels did not differ between responders and non-responders. TSI cut-off for predicting IVMP response was 19.4 IU/L (AUC = 0.69, sensitivity 50%, specificity 91%). In multivariate analysis TSI was the only independent predictor of response to IVMP (p < 0.05). Conclusions: High TSI levels are associated with active disease (cut-off 2.62 IU/L) and predict poor response to IVMP treatment (cut-off 19.4 IU/L) in GO. While sIL-2R correlates with disease activity, it is also related to thyroid function, making it less useful as an additional biomarker in GO.

Machine learning and optical coherence tomography-derived radiomics analysis to predict persistent diabetic macular edema in patients undergoing anti-VEGF intravitreal therapy.

BACKGROUND: Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. METHODS: A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. RESULTS: The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson's R = 0.44, p < 0.001). CONCLUSION: The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model's robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment.

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

Introduction: To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Methods: Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Results: Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Discussion: Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. Clinical trial registration: https://clinicaltrials.gov, identifier NCT00519428.

Predictors of treatment response in lymphogenic metastasized papillary thyroid cancer: a histopathological study.

BACKGROUND: Lymph node metastases in papillary thyroid cancer (PTC) increase the risk for persistent and recurrent disease. Data on the predictive value of histopathological features of lymph node metastases, however, are inconsistent. The aim of this study was to evaluate the prognostic significance of known and new histopathological features of lymph node metastases in a well-defined cohort of PTC patients with clinically evident lymph node metastases. METHODS: A total of 1042 lymph node metastases, derived from 129 PTC patients, were re-examined according to a predefined protocol and evaluated for diameter, extranodal extension, cystic changes, necrosis, calcifications and the proportion of the lymph node taken up by tumor cells. Predictors for a failure to achieve a complete biochemical and structural response to treatment were determined. RESULTS: The presence of more than 5 lymph node metastases was the only independent predictor for a failure to achieve a complete response to treatment (OR 3.39 [95% CI 1.57-7.33], p < 0.05). Diameter nor any of the other evaluated lymph node features were significantly associated with the response to treatment. CONCLUSIONS: Detailed re-examination of lymph nodes revealed that only the presence of more than 5 lymph node metastases was an independent predictor of failure to achieve a complete response to treatment. No predictive value was found for other histopathological features, including the diameter of the lymph node metastases. These findings have the potential to improve risk stratification in patients with PTC and clinically evident lymph node metastases.

Effect of CYP2C19 polymorphism on response to bortezomib-based therapy in multiple myeloma patients.

BACKGROUND: Bortezomib, a commonly used anti-myeloma drug, is metabolized by liver microsomal enzymes which may be polymorphic and responsible for lack of response in 30% patients. Hence, the association of CYP2C19 polymorphism with treatment response was explored in this study. METHODS: Treatment naive multiple myeloma (MM) patients, eligible for bortezomib-based induction treatment, were recruited as per the inclusion - exclusion criteria. The genotyping of CYP2C19 was done using polymerase chain reaction-restriction fragment length polymorphism for *2, *3 and *17 alleles. The incidence and severity of peripheral neuropathy were noted at follow-up visits and graded as per CTCAE criteria ver 5.0. RESULTS: Total 220 patients were recruited from August 2016 till May 2021; with a mean age of 55.6 (9.5) years and 65.9% males. Bortezomib+cyclophosphamide+dexamethasone (41.8%) and bortezomib+lenalidomide+dexamethasone (38.2%) were the most prescribed regimens. The CYP2C19 was polymorphic in 38.6%, 2.3% and 23.7% patients for *2, *3 and *17 allele respectively. There were 195 treatment responders and 25 non-responders, and CYP2C19*2 allele was different between responders and non-responders (p = 0.02). All extensive metabolisers (n = 54) were noted to be treatment responders. Peripheral neuropathy was reported by 23.2% patients. The frequency of peripheral neuropathy was somewhat lower in patients having either *2/*2 or *3/*3 allele pattern for CYP2C19 (p = 0.44). CONCLUSIONS: Polymorphism in CYP2C19 enzyme is likely to have an impact on bortezomib treatment response and peripheral neuropathy. The study suggests the role of pharmacogenetics in personalised treatment of MM.

Biomarker Predictors of Clinical Efficacy of the Anti-IgE Biologic, Omalizumab, in Severe Asthma in Adults: Results of the SoMOSA Study.

BACKGROUND: The anti-IgE monoclonal, omalizumab, is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during one year of omalizumab treatment. METHODS: 1-year, open-label, Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 severe (GINA step 4/5) uncontrolled atopic asthmatics (≥2 severe exacerbations in previous year) on high-dose inhaled corticosteroids, long-acting ß-agonists, ± mOCS. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE), and 16-52 weeks, to assess late responses by ≥50% reduction in exacerbations or dose of maintenance oral corticosteroids (mOCS). All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. RESULTS: 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ≥50%, while 57% (37/65) on mOCS reduced their dose by ≥50%. The primary outcome 2, 3-dinor-11-ß-PGF2α, GETE and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five breathomics (GC-MS) and 5 plasma lipid biomarkers strongly predicted the ≥50% reduction in exacerbations (receiver operating characteristic area under the curve (AUC): 0.780 and 0.922, respectively) and early responses (AUC:0.835 and 0.949, respectively). In independent cohorts, the GC-MS biomarkers differentiated between severe and mild asthma. Conclusions This is the first discovery of omics biomarkers that predict improvement to a biologic for asthma. Their prospective validation and development for clinical use is justified.

Measurement of metabolite levels and treatment-induced changes in hepatic metastases of gastro-esophageal cancer using 7-T phosphorus magnetic resonance spectroscopic imaging.

Methods for early treatment response evaluation to systemic therapy of liver metastases are lacking. Tumor tissue often exhibits an increased ratio of phosphomonoesters to phosphodiesters (PME/PDE), which can be noninvasively measured by phosphorus magnetic resonance spectroscopy (31P MRS), and may be a marker for early therapy response assessment in liver metastases. However, with commonly used 31P surface coils for liver 31P MRS, the liver is not fully covered, and metastases may be missed. The objective of this study was to demonstrate the feasibility of 31P MRS imaging (31P MRSI) with full liver coverage to assess 31P metabolite levels and chemotherapy-induced changes in liver metastases of gastro-esophageal cancer, using a 31P whole-body birdcage transmit coil in combination with a 31P body receive array at 7 T. 3D 31P MRSI data were acquired in two patients with hepatic metastases of esophageal cancer, before the start of chemotherapy and after 2 (and 9 in patient 2) weeks of chemotherapy. 3D 31P MRSI acquisitions were performed using an integrated 31P whole-body transmit coil in combination with a 16-channel body receive array at 7 T, with a field of view covering the full abdomen and a nominal voxel size of 20-mm isotropic. From the 31P MRSI data, 12 31P metabolite signals were quantified. Prior to chemotherapy initiation, both PMEs, that is, phosphocholine (PC) and phosphoethanolamine (PE), were significantly higher in all metastases compared with the levels previously determined in the liver of healthy volunteers. After 2 weeks of chemotherapy, PC and PE levels remained high or even increased further, resulting in increased PME/PDE ratios compared with healthy liver tissue, in correspondence with the clinical assessment of progressive disease after 2 months of chemotherapy. The suggested approach may present a viable tool for early therapy (non)response assessment of tumor metabolism in patients with liver metastases.

Using total adenosine triphosphate (tATP) measurements for cyanobacterial bloom monitoring and response assessment during algaecide treatments.

Total adenosine triphosphate (tATP) was investigated for its potential as a rapid indicator of cyanobacterial growth and algaecide effectiveness. tATP and other common bloom monitoring parameters were measured over the growth cycles of cyanobacteria and green algae in laboratory cultures and examined at a drinking water source during an active bloom. Strong correlations (R2>0.78) were observed between tATP and chlorophyll-a in cyanobacteria cultures. tATP offered greater sensitivity by increasing two orders of magnitude approximately 7 d before changes in chlorophyll-a or optical density were observed in Lyngbya sp. and Dolichospermum sp. cultures. Increases in tATP per cell coincided with the onset of exponential growth phases in lab cultures and increase in cell abundance in field samples, suggesting that ATP/cell is a sensitive indicator that may be used to identify the development of blooms. Bench-scale trials using samples harvested during a bloom showed that tATP exhibited a clear dose-response during copper sulfate (CuSO4) and hydrogen peroxide (H2O2) treatment compared to chlorophyll-a and cell counts, indicating that cellular production and storage of ATP decreases even when live and dead cells cannot be distinguished. During Copper (Cu) algaecide application at a reservoir used as a drinking water source, tATP and cell counts decreased following initial algaecide application; however, the bloom rebounded within 10 d showing that the Cu algaecide only has limited effectiveness. In this case, tATP was a sensitive indicator to bloom rebounding after algaecide treatments and correlated positively with cell counts (R2=0.7). These results support the use of tATP as a valuable complementary bloom monitoring tool for drinking water utilities to implement during the monitoring and treatment of cyanobacterial blooms.

LI-RADS version 2018 treatment response algorithm on extracellular contrast-enhanced MRI in patients treated with transarterial chemoembolization for hepatocellular carcinoma: diagnostic performance and the added value of ancillary features.

BACKGROUND: The Liver Imaging Reporting and Data System (LI-RADS) Treatment Response Algorithm (TRA) (LI-RADS TRA) is used for assessing response of HCC to locoregional therapy (LRT), however, the value of ancillary features (AFs) for TACE-treated HCCs has not been extensively investigated on extracellular agent MRI (ECA-MRI). PURPOSE: To evaluate the diagnostic performance of LI-RADS v2018 TRA on ECA-MRI for HCC treated with transarterial chemoembolization (TACE) and the value of ancillary features. METHODS: This retrospective study included patients who underwent TACE for HCC and then followed by hepatic surgery between January 2019 and June 2023 with both pre- and post-TACE contrast-enhanced MRI available. Two radiologists independently evaluated the post-treated lesions on MRI using LI-RADS treatment response (TR) (LR-TR) algorithm and modified LR-TR (mLR-TR) algorithm in which ancillary features (restricted diffusion and intermediate T2-weighted hyperintensity) were added, respectively. Lesions were categorized as complete pathologic necrosis (100%, CPN) and non-complete pathologic necrosis (< 100%, non-CPN) on the basis of surgical pathology. The diagnostic performance in predicting viable and non-viable tumors based on LR-TR and mLR-TR algorithms was compared using the McNemar test. Interreader agreement was calculated by using Cohen's weighted and unweighted κ. RESULTS: A total of 61 patients [mean age 59 years ± 10 (standard deviation); 47 men] with 79 lesions (57 pathologically viable) were included. For non-CPN prediction, the sensitivity, specificity of LR-TR viable and mLR-TR viable category were 75% (43 of 57), 82% (18 of 22) and 88% (50 of 57), 77% (17 of 22), respectively, the sensitivity of mLR-TR was significantly higher than that of LR-TR (P = 0.016) without difference in specificity (P = 1.000). Interreader agreement for LR-TR and mLR-TR category was moderate (k = 0.50, 95% confidence interval 0.33, 0.67, k = 0.42, 95% confidence interval 0.20, 0.63). The sensitivity of both LR-TR and mLR-TR algorithms in predicting viable tumors between conventional TACE (cTACE) and drug-eluting beads TACE (DEB-TACE) did not have significant difference (cTACE: 76%, 89% vs. DEB-TACE: 73%, 82%). CONCLUSIONS: On ECA-MRI, applying ancillary features to LI-RADS v2018 TRA can improve the sensitivity in predicting pathologic tumor viability in patients treated with TACE for hepatocellular carcinoma with no significant difference in specificity.

Bridging the feedback implementation gap: A comparison of empirical and rational decision rules in naturalistic psychotherapy.

Objective: Previous research indicates positive effects of feedback based on rational or empirical decision rules in psychotherapy. The implementation of these usually session-to-session-based feedback systems into clinical practice, however, remains challenging. This study aims to evaluate decision rules based on routine outcome monitoring with reduced assessment frequency. Method: Data routinely collected every 5-20 sessions of N = 3758 patients treated with CBT in an outpatient clinic (Msessions = 42.8, SD = 15.4) were used to develop feedback decision rules based on the expected treatment response and nearest neighbors approach, the reliable change index, and method of percental improvement. The detection of patients at risk of treatment failure served as primary endpoint. Results: Significantly lower reliable improvement, higher reliable deterioration rates, and smaller effect sizes were found for patients identified at risk of treatment failure by all rules. The nearest neighbors-based approach showed the highest sensitivity regarding the detection of reliably deteriorated cases. Conclusion: Consistent with previous research, the empirical models outperformed the rational rules. Still, the first-time used percental improvement-based rule also showed satisfactory results. Overall, the results point to the potential of basic feedback systems that might be easier to implement in practice than session-to-session based systems.

Utility of clinical and MR imaging parameters for prediction and monitoring of response to capecitabine and temozolomide (CAPTEM) therapy in patients with liver metastases of neuroendocrine tumors.

BACKGROUND: This study explores the predictive and monitoring capabilities of clinical and multiparametric MR parameters in assessing capecitabine and temozolomide (CAPTEM) therapy response in patients with neuroendocrine tumors (NET). PATIENTS AND METHODS: This retrospective study (n = 44) assessed CAPTEM therapy response in neuroendocrine liver metastases (NELM) patients. Among 33 monitored patients, as a subgroup of the overall study cohort, pretherapeutic and follow-up MRI data (size, apparent diffusion coefficient [ADC] values, and signal intensities), along with clinical parameters (chromogranin A [CgA] and Ki-67%), were analyzed. Progression-free survival (PFS) served as the reference. Responders were defined as those with PFS ≥ 6 months. RESULTS: Most patients were male (75%) and had G2 tumors (76%) with a pancreatic origin (84%). Median PFS was 5.7 months; Overall Survival (OS) was 25 months. Non-responders (NR) had higher Ki-67 in primary tumors (16.5 vs. 10%, p = 0.01) and increased hepatic burden (20% vs. 5%, p = 0.007). NR showed elevated CgA post-treatment, while responders (R) exhibited a mild decrease. ADC changes differed significantly between groups, with NR having decreased ADCmin (-23%) and liver-adjusted ADCmean/ADCmean liver (-16%), compared to R's increases of ADCmin (50%) and ADCmean/ADCmean liver (30%). Receiver operating characteristic (ROC) analysis identified the highest area under the curve (AUC) (0.76) for a single parameter for ∆ ADC mean/liver ADCmean, with a cut-off of < 6.9 (76% sensitivity, 75% specificity). Combining ∆ Size NELM and ∆ ADCmin achieved the best balance (88% sensitivity, 60% specificity) outperforming ∆ Size NELM alone (69% sensitivity, 65% specificity). Kaplan-Meier analysis indicated significantly longer PFS for ∆ ADCmean/ADCmean liver < 6.9 (p = 0.024) and ∆ Size NELM > 0% + ∆ ADCmin < -2.9% (p = 0.021). CONCLUSIONS: Survival analysis emphasizes the need for adapted response criteria, involving combined evaluation of CgA, ADC values, and tumor size for monitoring CAPTEM response in hepatic metastasized NETs.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma.

Background and purpose: Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response. Materials and methods: Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease. Results: ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed. Conclusion: The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.