Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer.

BACKGROUND: Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. Therapeutic targeting of miR-155 through its antagonist, anti-miR-155, has proven challenging due to its dual molecular effects. METHODS: We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. RESULTS: Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimens to prevent antagonistic effects. CONCLUSIONS: This work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Prognostic Role of Preoperative Chemotherapy in Liver-Limited Metastasis from Gastric Cancer.

BACKGROUND: We investigated the prognostic role of preoperative chemotherapy in patients who underwent hepatectomy for liver-limited metastasis (LLM) from gastric cancer (GC). METHODS: A retrospective analysis was conducted for 52 consecutive patients who underwent macroscopically complete (R0 or R1) resection for synchronous or metachronous LLM from GC. RESULTS: Of the 52 patients, 18 (35%) received preoperative chemotherapy (PC group), while 34 (65%) underwent upfront surgery (US group). The PC group had a significantly longer overall survival than the US group (cumulative 5-year OS rate: 47.6% vs. 24.8%, p = 0.041). Multivariate analysis of OS revealed that preoperative chemotherapy was an independent favorable prognostic factor (hazard ratio: 0.445, p = 0.036). Patients showing a partial response to preoperative chemotherapy on RECIST had an improved OS compared with those exhibiting stable or progressive disease after preoperative chemotherapy and with US (p = 0.025), even among those with solitary LLM (p = 0.062) and multiple LLM (p = 0.026). At recurrence after hepatectomy for LLM, the PC group had a significantly higher incidence of solitary tumors than the US group (p = 0.043) and had a higher chance to undergo surgical resection for recurrent sites (p = 0.006). CONCLUSIONS: Preoperative chemotherapy can be recommended for patients with LLM from GC. The evaluation of the efficacy of preoperative chemotherapy offers additional information to determine the surgical indication for LLM.

RECIST 1.1, mRECIST, and Choi criteria for evaluating treatment response and survival outcomes in hepatocellular carcinoma patients treated with atezolizumab plus bevacizumab.

OBJECTIVES: We aimed to compare the early responder rates, defined as complete or partial responders, using response evaluation criteria in solid tumors (RECIST) 1.1, modified RECIST (mRECIST), and Choi criteria in advanced HCC patients treated with atezolizumab-bevacizumab (atezo-bev), and to correlate them with progression-free survival (PFS) and overall survival (OS). METHODS: This retrospective study included advanced HCC patients treated with ≥ 3 cycles of atezo-bev. Two reviewers assessed responses using RECIST 1.1, mRECIST, and Choi criteria at 1st follow-up imaging. Kaplan-Meier curves with log-rank tests evaluated and compared PFS and OS. Cox proportional hazard models identified survival outcome predictors. Kappa statistics assessed inter-reader agreement. RESULTS: We evaluated 77 patients (65 men; mean age, 62.8 ± 12.3 years). Choi's criteria revealed the highest early responders rate (53.2%), exceeding mRECIST (32.5-33.8%) and RECIST 1.1 (24.7-26.0%), with an excellent agreement in all criteria (κ, 0.85-0.95). Across criteria, a consistent number of patients progressed (23-26) and was associated with significantly poor OS (ps ≤ 0.049). Responders by any criteria showed longer PFS (ps ≤ 0.009), and 1-year OS (ps ≤ 0.01). Choi criteria linked to significantly better OS without landmark (p = 0.003), with 1-year OS rates at 76.9% for responders vs 38.1% for non-responders. Cox analysis identified responders by Choi criteria as a significant OS predictor. CONCLUSION: Choi criteria identified more early responders than RECIST 1.1 and mRECIST, significantly correlating with improved OS. Choi criteria could be considered as a formal response assessment criterion for the emerging atezo-bev systemic treatment. CLINICAL RELEVANCE STATEMENT: For atezo-bev treatment of advanced HCC, more comprehensive response criteria, such as Choi criteria, could be effective in identifying early responders and predicting survival outcomes along with RECIST 1.1 and mRECIST. KEY POINTS: Choi criteria identified a higher rate of early responders compared to mRECIST and RECIST1.1 following atezo-bev treatment. Responders by all criteria had longer PFS and 1-year OS, and only those by Choi criteria experienced longer OS without landmark time. Choi criteria, with RECIST 1.1 and mRECIST, is an effective response assessment tool for atezo-bev treatment.

Circulating miRNA-21 Levels in Breast Cancer Patients Before and After Chemotherapy and Its Association with Clinical Improvement.

Breast cancer is the most frequent type of cancer in women, many patients experience recurrences and metastasis. miR-21 (microRNA-21) as biomarker is under investigation for breast cancer. At present, there is very limited information available regarding effect of chemotherapy on miR-21 expression in breast cancer and its correlation with the clinical improvement. Hence, this study was planned to evaluate the effect of chemotherapy on miR-21 in metastatic breast cancer and its relationship with the clinical outcome. Females, aged-18-90 years diagnosed with Invasive Ductal Carcinoma of breast and candidate of neoadjuvant chemotherapy including Adriamycin (60 mg/m2), Cyclophosphamide (600 mg/m2) with or without Taxane (75-175 mg/m2) were included in the study. Before and after 42 days of staring of chemotherapy sample was collected for circulatory miR-21 and RECIST 1.1 criteria was applied to assess the clinical status. Blood samples for routine clinical biomarkers including liver function test and renal function tests was also collected. miR-21 expression before and after chemotherapy was assessed using standard method based on real time PCR. Expression of miR-21, RECIST criteria and other liver and kidney related biomarkers were compared before and after chemotherapy. After neoadjuvant chemotherapy expression of miR-21 was significantly increased by 5.65-fold. There was significant improvement in clinical scores based on RECIST criteria (0.046). No significant correlation was observed between miR-21 expression and difference in RECIST score (r = - 0.122, p = 0.570). Neoadjuvant chemotherapy causes clinical improvement in breast cancer patients however it is not correlated with the miR-21 expression which significantly increased after chemotherapy.

Risk model and factors for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer-a two-center cohort study.

OBJECTIVE: Due to inconsistency in neoadjuvant chemotherapy (NACT) response in advanced gastric cancer (GC), the indications remain the source of controversy. This study focused on identifying factors related to NACT chemosensitivity and providing the best treatment for GC cases. METHODS: Clinical data in 867 GC cases treated with neoadjuvant chemotherapy were downloaded from two medical centers between January 2014 and December 2020, and analyzed by logistic regression and the least absolute shrinkage and selection operator (LASSO) for identifying potential factors that predicted NACT response and might be incorporated in constructing the prediction nomogram. RESULTS: After the inclusion and exclusion criteria were applied, totally 460 cases were enrolled, among which, 307 were males (66.74%) whereas 153 were females (33.26%), with the age of 24-77 (average, 59.37 ± 10.60) years. Consistent with RECIST standard, 242 patients were classified into effective group (PR or CR) while 218 were into ineffective group (PD or SD), with the effective rate of 52.61%. In training set, LASSO and logistic regression analysis showed that five risk factors were significantly associated with NACT effectiveness, including tumor location, Smoking history, T and N stages, and differentiation. In terms of our prediction model, its C-index was 0.842. Moreover, calibration curve showed that the model-predicted results were in good consistence with actual results. Validation based on internal and external validation sets exhibited consistency between training set results and ours. CONCLUSIONS: This study identified five risk factors which were significantly associated with NACT response, including smoking history, clinical T stage, clinical N stage, tumor location and differentiation. The prediction model that exhibited satisfying ability to predict NACT effectiveness was constructed, which may be adopted for identifying the best therapeutic strategy for advanced GC by gastrointestinal surgeons.

Kappa statistic considerations in evaluating inter-rater reliability between two raters: which, when and context matters.

BACKGROUND: In research designs that rely on observational ratings provided by two raters, assessing inter-rater reliability (IRR) is a frequently required task. However, some studies fall short in properly utilizing statistical procedures, omitting essential information necessary for interpreting their findings, or inadequately addressing the impact of IRR on subsequent analyses' statistical power for hypothesis testing. METHODS: This article delves into the recent publication by Liu et al. in BMC Cancer, analyzing the controversy surrounding the Kappa statistic and methodological issues concerning the assessment of IRR. The primary focus is on the appropriate selection of Kappa statistics, as well as the computation, interpretation, and reporting of two frequently used IRR statistics when there are two raters involved. RESULTS: The Cohen's Kappa statistic is typically utilized to assess the level of agreement between two raters when there are two categories or for unordered categorical variables with three or more categories. On the other hand, when it comes to evaluating the degree of agreement between two raters for ordered categorical variables comprising three or more categories, the weighted Kappa is a widely used measure. CONCLUSION: Despite not substantially affecting the findings of Liu et al.?s study, the statistical dispute underscores the significance of employing suitable statistical methods. Rigorous and accurate statistical results are crucial for producing trustworthy research.

German specialists treating testicular cancer follow different guidelines with resulting inconsistency in assessment of retroperitoneal lymph-node metastasis: clinical implications and possible corrective measures.

BACKGROUND: Testicular germ cell tumors (GCTs) are aggressive but highly curable tumors. To avoid over/undertreatment, reliable clinical staging of retroperitoneal lymph-node metastasis is necessary. Current clinical guidelines, in their different versions, lack specific recommendations on how to measure lymph-node metastasis. OBJECTIVE: We aimed to assess the practice patterns of German institutions frequently treating testicular cancer for measuring retroperitoneal lymph-node size. METHODS: An 8-item survey was distributed among German university hospitals and members of the German Testicular Cancer Study Group. RESULTS: In the group of urologists, 54.7% assessed retroperitoneal lymph nodes depending on their short-axis diameter (SAD) (33.3% in any plane, 21.4% in the axial plane), while 45.3% used long-axis diameter (LAD) for the assessment (42.9% in any plane, 2.4% in the axial plane). Moreover, the oncologists mainly assessed lymph-node size based on the SAD (71.4%). Specifically, 42.9% of oncologists assessed the SAD in any plane, while 28.5% measured this dimension in the axial plane. Only 28.6% of oncologists considered the LAD (14.3% in any plane, 14.3% in the axial plane). None of the oncologists and 11.9% of the urologists (n = 5) always performed an MRI for the initial assessment, while for follow-up imaging, the use increased to 36.5% of oncologists and 31% of urologists. Furthermore, only 17% of the urologists, and no oncologists, calculated lymph-node volume in their assessment (p = 0.224). CONCLUSION: Clear and consistent measurement instructions are urgently needed to be present in all guidelines across different specialistic fields involved in testicular cancer management.

Imaging Follow-Up of Nonsurgical Therapies for Lung Cancer: AJR Expert Panel Narrative Review.

Lung cancer continues to be the most common cause of cancer-related death worldwide. In the past decade, with the implementation of lung cancer screening programs and advances in surgical and nonsurgical therapies, the survival of patients with lung cancer has increased, as has the number of imaging studies that these patients undergo. However, most patients with lung cancer do not undergo surgical re-section, because they have comorbid disease or lung cancer in an advanced stage at diagnosis. Nonsurgical therapies have continued to evolve with a growing range of systemic and targeted therapies, and there has been an associated evolution in the imaging findings encountered at follow-up examinations after such therapies (e.g., with respect to posttreatment changes, treatment complications, and recurrent tumor). This AJR Expert Panel Narrative Review describes the current status of nonsurgical therapies for lung cancer and their expected and unexpected imaging manifestations. The goal is to provide guidance to radiologists regarding imaging assessment after such therapies, focusing mainly on non-small cell lung cancer. Covered therapies include systemic therapy (conventional chemotherapy, targeted therapy, and immunotherapy), radiotherapy, and thermal ablation.

Response heterogeneity as a new biomarker of treatment response in patients with neuroendocrine tumors.

Aim: The RAISE project aimed to find a surrogate end point to predict treatment response early in patients with enteropancreatic neuroendocrine tumors (NET). Response heterogeneity, defined as the coexistence of responding and non-responding lesions, has been proposed as a predictive marker for progression-free survival (PFS) in patients with NETs. Patients & methods: Computerized tomography scans were analyzed from patients with multiple lesions in CLARINET (NCT00353496; n = 148/204). Cox regression analyses evaluated association between response heterogeneity, estimated using the standard deviation of the longest diameter ratio of target lesions, and NET progression. Results: Greater response heterogeneity at a given visit was associated with earlier progression thereafter: week 12 hazard ratio (HR; 95% confidence interval): 1.48 (1.20-1.82); p < 0.001; n = 148; week 36: 1.72 (1.32-2.24); p < 0.001; n = 108. HRs controlled for sum of longest diameter ratio: week 12: 1.28 (1.04-1.59); p = 0.020 and week 36: 1.81 (1.20-2.72); p = 0.005. Conclusion: Response heterogeneity independently predicts PFS in patients with enteropancreatic NETs. Further validation is required.

Neuroendocrine tumors (NET) are rare, slow-growing cancers that can grow in various parts of the body. By understanding how NETs are responding to treatment, doctors can choose the best treatment for a patient and monitor whether the treatment needs to be changed. Treatment response is determined using 'Response Evaluation Criteria in Solid Tumors (RECIST)': a technique which measures the size of tumors to assess whether they are shrinking. However, RECIST is not always useful in NETs, which grow slowly and rarely shrink. 'Response heterogeneity' describes the situation in which some tumors respond well to treatment, while other tumors in the same patient do not. Response heterogeneity may be important in understanding how tumors are responding to treatment and predicting outcomes for patients. Until now, the link between response heterogeneity and treatment response has not been studied in patients with NETs. The RAISE project examined data from a clinical trial of patients with NETs treated with lanreotide. In RAISE, response heterogeneity was estimated using imaging scans of NETs. Response heterogeneity was compared with factors such as tumor size and amounts of certain molecules found in the blood, to see how well response heterogeneity could predict outcomes for patients with NETs. In this study, response heterogeneity was linked with worse outcomes for patients. Therefore, it may be useful in understanding how NETs respond to treatment. Further research is needed in a different group of patients with NETs, and in patients receiving other treatments, to better understand response heterogeneity.

The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors.

Aim: The RAISE project assessed whether deep learning could improve early progression-free survival (PFS) prediction in patients with neuroendocrine tumors. Patients & methods: Deep learning models extracted features from CT scans from patients in CLARINET (NCT00353496) (n = 138/204). A Cox model assessed PFS prediction when combining deep learning with the sum of longest diameter ratio (SLDr) and logarithmically transformed CgA concentration (logCgA), versus SLDr and logCgA alone. Results: Deep learning models extracted features other than lesion shape to predict PFS at week 72. No increase in performance was achieved with deep learning versus SLDr and logCgA models alone. Conclusion: Deep learning models extracted relevant features to predict PFS, but did not improve early prediction based on SLDr and logCgA.

CT-based radiomics to distinguish progressive from stable neuroendocrine liver metastases treated with somatostatin analogues: an explorative study.

BACKGROUND: Accurate response evaluation in patients with neuroendocrine liver metastases (NELM) remains a challenge. Radiomics has shown promising results regarding response assessment. PURPOSE: To differentiate progressive (PD) from stable disease (SD) with radiomics in patients with NELM undergoing somatostatin analogue (SSA) treatment. MATERIAL AND METHODS: A total of 46 patients with histologically confirmed gastroenteropancreatic neuroendocrine tumors (GEP-NET) with ≥1 NELM and ≥2 computed tomography (CT) scans were included. Response was assessed with Response Evaluation Criteria in Solid Tumors (RECIST1.1). Hepatic target lesions were manually delineated and analyzed with radiomics. Radiomics features were extracted from each NELM on both arterial-phase (AP) and portal-venous-phase (PVP) CT. Multiple instance learning with regularized logistic regression via LASSO penalization (with threefold cross-validation) was used to classify response. Three models were computed: (i) AP model; (ii) PVP model; and (iii) AP + PVP model for a lesion-based and patient-based outcome. Next, clinical features were added to each model. RESULTS: In total, 19 (40%) patients had PD. Median follow-up was 13 months (range 1-50 months). Radiomics models could not accurately classify response (area under the curve 0.44-0.60). Adding clinical variables to the radiomics models did not significantly improve the performance of any model. CONCLUSION: Radiomics features were not able to accurately classify response of NELM on surveillance CT scans during SSA treatment.

Assessment of the response to systemic treatment of colorectal liver metastases on cross-sectional imaging - a systematic review.

Colorectal cancer (CRC) is one of the most common malignancies in the world. Nowadays many treatments are available to help control CRC, including surgery, radiation therapy, interventional radiology, and drug treatments. A multidisciplinary approach and the role of radiologists is needed to assist the surgeon in the management thanks to emerging technology and strategies. The Response Evaluation Criteria in Solid Tumours (RECIST) has been created to objectify and standardize cancer response assessment. Thus, in this article specific presumptions and practical aspects of evaluating responses according to the RECIST 1.1 are discussed. Furthermore, examples of possible response to systemic treatment of colorectal liver metastases (CRLM), including tumour necrosis, apparent diffusion coefficient (ADC) values, tumour calcification, tumour fibrosis and intratumoural fat deposition observed on cross-sectional imaging, are described. Disappearing liver metastases (DLM) presents a therapeutic dilemma. The optimal management of DLM remains controversial due to the uncertainty of residual microscopic disease and effective long-term outcomes. The article provides an overview of the CRLM phenomenon and current possible assessment methods of the response to systemic treatment.

Deciphering radiological stable disease to immune checkpoint inhibitors.

BACKGROUND: 'Stable disease (SD)' as per RECIST is a common but ambiguous outcome in patients receiving immune checkpoint inhibitors (ICIs). This study aimed to characterize SD and identify the subset of patients with SD who are benefiting from treatment. Understanding SD would facilitate drug development and improve precision in correlative research. PATIENTS AND METHODS: A systematic review was carried out to characterize SD in ICI trials. SD and objective response were compared to proliferation index using The Cancer Genome Atlas gene expression data. To identify a subgroup of SD with outcomes mirroring responders, we examined a discovery cohort of non-small-cell lung cancer (NSCLC). Serial cutpoints of two variables, % best overall response and progression-free survival (PFS), were tested to define a subgroup of patients with SD with similar survival as responders. Results were then tested in external validation cohorts. RESULTS: Among trials of ICIs (59 studies, 14 280 patients), SD ranged from 16% to 42% in different tumor types and was associated with disease-specific proliferation index (ρ = -0.75, P = 0.03), a proxy of tumor kinetics, rather than relative response to ICIs. In a discovery cohort of NSCLC [1220 patients, 313 (26%) with SD to ICIs], PFS ranged widely in SD (0.2-49 months, median 4.9 months). The subset with PFS >6 months and no tumor growth mirrored partial response (PR) minor (overall survival hazard ratio 1.0) and was proposed as the definition of SD responder. This definition was confirmed in two validation cohorts from trials of NSCLC treated with durvalumab and found to apply in tumor types treated with immunotherapy in which depth and duration of benefit were correlated. CONCLUSIONS: RECIST-defined SD to immunotherapy is common, heterogeneous, and may largely reflect tumor growth rate rather than ICI response. In patients with NSCLC and SD to ICIs, PFS >6 months and no tumor growth may be considered 'SD responders'. This definition may improve the efficiency of and insight derivable from clinical and translational research.

Efficacy of immunotherapy beyond RECIST progression in advanced melanoma: a real-world evidence.

Immunotherapy (ITH) holds the possibility of tumor burden decrease after initial RECIST 1.1 defined progression. The clinical concept of treating selected patients (pts) beyond disease progression (PD) is supported by so-called pseudoprogression phenomenon. The aim of this study was to evaluate real-life practice and outcomes related to treatment beyond (RECIST) progression (TBP) in advanced melanoma patients. Of 584 subsequent melanoma pts analyzed 77 (13.2%) received TBP. In this cohort, the median time to first PD (TTFP) was 5.29 months (m), while time to second PD (TTSP)-8.02 m. On TBP 23.4% pts achieved an objective response (OR), and next 42.9%-stabilization of the disease (SD). 1st PD was reported most often as the development of a new lesion or increase (> 20%) of the diameter of three or more targets. In about 50% second PD was observed as an increase in the diameter of different targets that in 1st PD. Multimodal treatment resulted in 9.82 m TTSP, while ITH alone-4.93 m (p = 0.128). An oligoprogressive pattern of first PD was associated with longer TTSP (HR 0.55, 95% CI: 0.32-0.94). Median OS after first PD was 28.75 months and correlated with OR during TBP (HR 0.18, 95% CI: 0.004-0.76). Selected clinically fit melanoma patients, despite evidence of first radiographic progression, may benefit from continued treatment with PD-1 checkpoint inhibitors, but the findings should be validated in larger prospective trials. Multidisciplinary treatment should be offered to advanced melanoma patients, including radiosurgery or stereotactic radiotherapy of single loci progressing during immunotherapy.

Clinical benefit of continuing pembrolizumab treatment beyond progression in patients with metastatic urothelial carcinoma.

BACKGROUND: There has been no clinical evidence to justify continued pembrolizumab therapy beyond progression in patients with metastatic urothelial carcinoma (UC). MATERIALS AND METHODS: We conducted a multicenter retrospective study evaluating the clinical efficacy of continued use of pembrolizumab beyond progression in patients with metastatic UC. Data from 51 patients with metastatic UC, who developed progression during second-line pembrolizumab therapy, were analyzed. Progression was defined based on the Immunotherapy Response Evaluation Criteria in Solid Tumors. The outcome was overall survival (OS). The association between continued treatment, OS, and the risk of all-cause mortality was tested using log-rank test, conventional and time-dependent Cox regression models. RESULTS: No significant difference in patient characteristics was noted between patients continuing pembrolizumab beyond progression (N = 21) and those discontinuing pembrolizumab (N = 30). Median OS was significantly longer in the continuation group (17.8 vs. 8.8 months; P = 0.038). A multivariable conventional Cox regression model identified continued pembrolizumab administration as a significant independent prognostic factor of all-cause mortality (hazard ratio [HR]: 0.21, 95% confidence interval [CI]: 0.05-0.90, P = 0.036), irrespective of the time from treatment initiation to progression and concurrent clinical progression. Further, longer duration of pembrolizumab treatment beyond progression was independently associated with a reduced risk of all-cause mortality in a multivariable time-dependent Cox regression model, when used as a time-dependent variable (HR: 0.07, 95% CI: 0.01-0.45, P = 0.006). CONCLUSIONS: Continued pembrolizumab administration beyond progression might be beneficial in patients with metastatic UC who were clinically stable.

Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics.

BACKGROUND: Significant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients. METHODS: In this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival. RESULTS: Of 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNApost-NAC was a preferential prognosticator for all endpoints, especially for distant metastasis. In contrast, radiological response was more preferentially associated with locoregional recurrence. Intriguingly, cfEBV DNApost-NAC further stratified RECIST-responsive and non-responsive patients; RECIST-based non-responsive patients with cBR still derived substantial clinical benefits. Moreover, detectable cfEBV DNApost-NAC had 83.6% prediction sensitivity for detectable post-treatment ctDNA, which conferred early determination of treatment benefits. Finally, we established individualized risk prediction models and demonstrated that introducing on-treatment ctDNA significantly refined risk stratification. CONCLUSIONS: Our study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation. OBJECTIVE: To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria. METHODS: One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort. RESULTS: In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)]. CONCLUSION: The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

Comparison of Magnetic Resonance Imaging With Positron Emission Tomography/Computed Tomography in the Evaluation of Response to Neoadjuvant Therapy of Breast Cancer.

INTRODUCTION: The present study aims to determine the diagnostic accuracy of magnetic resonance imaging (MRI) and positron emission tomography-computed tomography (PET-CT) in predicting a pathological response of molecular subtypes of breast cancer to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: We retrospectively analyzed patients with breast cancer who were operated after NAC between January 2018 and May 2020. Radiological responses were evaluated as per the Response Evaluation Criteria in Solid Tumors (RECIST) and changes in contrast enhancement patterns on MRI and the classification of PET Response Criteria in Solid Tumors (PERCIST) on PET-CT. The presence of a pathological response was evaluated based on the Sataloff classification. The agreement between the radiological response determined through imaging modalities before and after the NAC and the postoperative pathological complete response (pCR) was evaluated and compared statistically. Among the patients diagnosed with breast cancer between the ages of 18 and 80 y, those with N (+) at the time of diagnosis, those with T2 and advanced tumors, and those who were planned for breast conserving surgery were included in our study. Male patients, patients with distant metastases at the time of diagnosis, and patients with other system malignancies were excluded. RESULTS: The study included 88 patients who had undergone surgery for breast cancer after NAC between January 2018 and May 2020. The study was conducted retrospectively in a single center. The tumor diameters and standard uptake values significantly decreased after NAC (P < 0.001). Estrogen receptor (ER) and progesterone receptor (PR) positivity were negatively associated with pCR (P = 0.03 and P = 0.03, respectively), whereas there was a significant positive association between HER-2 positivity and pCR (P = 0.004). There was a moderate agreement between the RECIST criteria used with MRI and pCR (k: 0.46). Moreover, a good agreement between PET-CT-PERCIST and pCR was detected (k: 0.61). In predicting pCR after NAC, MRI showed a selectivity of 80.7%, a sensitivity of 65.2%, a positive predictive value (PPV) of 75%, and a negative predictive value (NPV) of 72.4%. The corresponding rates for PET-CT were 75.7%, 100%, 57.9%, and 100%. CONCLUSIONS: When evaluating pCR after NAC, MRI was found to be more sensitive in patients with ER-positive cancer cell nuclei with weak to medium staining intensity and a loss of E-cadherin expression, whereas PET-CT was found to be more sensitive in patients with HER-2 overexpression, Luminal B, or Ki-67 proliferation >14% (P = 0.01).

Immunotherapy-Based Treatments of Hepatocellular Carcinoma: AJR Expert Panel Narrative Review.

The advent of immunotherapy for patients with hepatocellular carcinoma (HCC) has changed the treatment landscape and conferred a survival benefit on patients with advanced HCC, who typically have a very poor prognosis. The most pronounced improvements in response, as documented by standardized response criteria based on CT or MRI, have been achieved when immunotherapy is combined with other systemic or locoregional therapies. Immune checkpoint inhibitor treatments result in unique patterns on CT and MRI that challenge the application of conventional response criteria such as RECIST, modified RECIST, and European Association for the Study of the Liver criteria. Thus, newer criteria have been developed to gauge therapy response or disease progression for patients receiving immunotherapy, including immune-related RECIST (iRECIST) and immune-modified RECIST (imRECIST), though these remain unvalidated. In this review, we describe the current landscape of immunotherapeutic agents used for HCC, summarize the results of published studies, review the pathobiologic mechanisms that provide a rationale for the use of these agents, and report on the status of response assessment for immunotherapy either alone or in combination with other treatment options. Finally, consensus statements are provided to inform radiologists about essential considerations in the era of a rapidly changing treatment paradigm for patients with HCC.

Exploratory analysis of tumor imaging in a Phase 2 trial with cabozantinib in gastrointestinal stromal tumor: lessons learned from study EORTC STBSG 1317 'CaboGIST'.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) are malignant mesenchymal tumors arising in the gastrointestinal tract. Their systemic treatment is based on the use of tyrosine kinase inhibitors (TKIs) with imatinib, sunitinib, and regorafenib being the preferred agents. Assessment of tumor response to TKI treatment in GISTs is traditionally done according the Response Evaluation Criteria in Solid Tumors (RECIST), while Choi criteria have also been proposed as alternative tool assessing both volumetric and density changes on computer tomography (CT) scans. EORTC STBSG 1317 'CaboGIST' was a single-arm prospective Phase 2 trial which met its primary endpoint, as 60% of patients previously treated with imatinib and sunitinib were progression-free at 12 weeks (95% CI 45-74%) based on local RECIST assessment. MATERIALS AND METHODS: We report here an exploratory analysis of local versus central RECIST version 1.1 assessment and a comparison of RECIST version 1.1 versus Choi criteria. RESULTS: Comparisons between local and central RECIST version 1.1 at week 12 revealed discrepancies in 17/43 evaluable cases (39.5%). When comparing Choi with local and central RECIST version 1.1, discrepancies were observed in 27/43 (62.8%) and 21/43 (48.8%) cases, respectively. A total of 68% of evaluable patients were progression-free and alive at week 12 based on local RECIST, 84% according to central RECIST analysis and 81% when applying Choi criteria. Central assessment upgraded the treatment response both with RECIST version 1.1 and Choi. CONCLUSIONS: The results of this exploratory analysis support the conclusion that cabozantinib is active in patients with metastatic or recurrent GIST after treatment with imatinib and sunitinib and confirm once again the limitations of RECIST to capture response to TKI in GIST, and the importance to include density changes in the response evaluation in this setting. Clinical trial number: EORTC 1317, NCT02216578.