Staging CT Research Articles

Is There an Impact of Transperineal Versus Transrectal Magnetic Resonance Imaging–targeted Biopsy on the Risk of Upgrading in Final Pathology in Prostate Cancer Patients Undergoing Radical Prostatectomy? An European Association of Urology-Young Academic Urologists Prostate Cancer Working Group Multi-institutional Study

BackgroundThe concordance rates of transperineal (TP) versus transrectal (TR) prostate biopsies with radical prostatectomy (RP) specimen have been assessed poorly in men diagnosed with magnetic resonance imaging (MRI)-targeted biopsy (TBx). ObjectiveTo evaluate International Society of Urological Pathology (ISUP) concordance rates between the final pathology at RP and MRI-TBx or MRI-TBx + random biopsy (RB) according to the biopsy approach. Design, setting, and participantsA multi-institutional database included patients diagnosed with TP or TR treated with RP. InterventionTP-TBx or TR-TBx of the prostate. Outcome measurements and statistical analysisThe ISUP grade at biopsy was compared with the final pathology. A multivariable logistic regression analysis (MVA) was performed to assess the association between the biopsy approach (TP-TBx vs TR-TBx) and ISUP upgrading, downgrading, concordance, and clinically relevant increase (CRI). Results and limitationsOverall, 752 (59%) versus 530 (41%) patients underwent TR versus TP. At the MVA, TP-TBx was an independent predictor of upgrading (odds ratio [OR] 0.6, 95% confidence interval [CI] 0.4–0.9, p < 0.01) and improved concordance relative to the final pathology (OR 1.7, 95% CI 1.2–2.5, p < 0.01) after adjusting for age, cT stage, Prostate Imaging Reporting and Data System, number of targeted cores, prostate-specific antigen, and prostate volume. Moreover, TP-TBx was associated with a lower risk of CRI than TR-TBx (OR 0.7, p < 0.01). This held true when considering patients who underwent MRI-TBx + RB (OR 0.6, p < 0.01). The inclusion of men who had RP represents a potential selection bias. ConclusionsThe adoption of TP-TBx compared with TR-TBx may reduce the risk of upgrading and improve the concordance of biopsy grade with the final pathology. The TP approach decreases the odds of CRI with improved patient selection for the correct active treatment. Patient summaryIn this report, we evaluated whether transperineal (TP) targeted biopsy (TBx) may improve the concordance of clinically significant prostate cancer with the final pathology in comparison with transrectal (TR) TBx in a large worldwide population. We found that TP-TBx might increase concordance compared with TR-TBx. Adding random biopsies to target one increases accuracy; however, concordance with the final pathology is overall suboptimal even with the TP approach.

Diagnostic performance of PET-CT compared to conventional CT for lymph node staging in bladder cancer patients undergoing radical cystectomy and bilateral pelvic lymph node dissection

Diagnostic performance of PET-CT compared to conventional CT for lymph node staging in bladder cancer patients undergoing radical cystectomy and bilateral pelvic lymph node dissection

Artificial Intelligence in Bladder Cancer Diagnosis: Current Applications and Future Perspectives

Bladder cancer (BCa) is one of the most diagnosed urological malignancies. A timely and accurate diagnosis is crucial at the first assessment as well as at the follow up after curative treatments. Moreover, in the era of precision medicine, proper molecular characterization and pathological evaluation are key drivers of a patient-tailored management. However, currently available diagnostic tools still suffer from significant operator-dependent variability. To fill this gap, physicians have shown a constantly increasing interest towards new resources able to enhance diagnostic performances. In this regard, several reports have highlighted how artificial intelligence (AI) can produce promising results in the BCa field. In this narrative review, we aimed to analyze the most recent literature exploring current experiences and future perspectives on the role of AI in the BCa scenario. We summarized the most recently investigated applications of AI in BCa management, focusing on how this technology could impact physicians’ accuracy in three widespread diagnostic areas: cystoscopy, clinical tumor (cT) staging, and pathological diagnosis. Our results showed the wide potential of AI in BCa, although larger prospective and well-designed trials are pending to draw definitive conclusions allowing AI to be routinely applied to everyday clinical practice.

Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer.

Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p < 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.

Software-Based Assessment of Well-Aerated Lung at CT for Quantification of Predicted Pulmonary Function in Resected NSCLC.

Background: To test the agreement between postoperative pulmonary function tests 12 months after surgery (mpo-PFTs) for non-small cell lung cancer (NSCLC) and predicted lung function based on the quantification of well-aerated lung (WAL) at staging CT (sCT). Methods: We included patients with NSCLC who underwent lobectomy or segmentectomy without a history of thoracic radiotherapy or chemotherapy treatment with the availability of PFTs at 12 months follow-up. Postoperative predictive (ppo) lung function was calculated using the resected lobe WAL (the lung volume between −950 and −750 HU) at sCT. The Spearman correlation coefficient (rho) and intraclass correlation coefficient (ICC) were used to the test the agreement between WAL ppo-PFTs and mpo-PFTs. Results: the study included 40 patients (68 years-old, IQR 62−74 years-old; 26/40, 65% males). The WAL ppo-forced expiratory volume in 1 s (FEV1) and the ppo-diffusing capacity of the lung for carbon monoxide (%DLCO) were significantly correlated with corresponding mpo-PFTs (rho = 0.842 and 0.717 respectively; p < 0.001). The agreement with the corresponding mpo-PFTs of WAL ppo-FEV1 was excellent (ICC 0.904), while it was good (ICC 0.770) for WAL ppo-%DLCO. Conclusions: WAL ppo-FEV1 and WAL ppo-%DLCO at sCT showed, respectively, excellent and good agreement with corresponding mpo-PFTs measured 12 months after surgery for NSCLC. WAL is an easy parameter obtained by staging CT that can be used to estimate post-resection lung function for patients with borderline pulmonary function undergoing lung surgery.

The impact of postmastectomy radiotherapy on cT1-2N1 breast cancer patients with ypN0 after neoadjuvant chemotherapy: a retrospective study based on real-world data

BackgroundThe role of postmastectomy radiation therapy (PMRT) in clinical T1-2N1 breast cancer patients who achieve axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NAC) is controversial.MethodsData from cT1-2N1 breast cancer patients who converted to ypN0 after NAC and subsequent surgery were retrospectively analyzed. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan‒Meier method. Univariate and multivariate Cox regression models were applied to investigate the correlations between clinical or pathological parameters and survival.ResultsFrom 2012–2019, we identified 116 cases for analysis, including 31 (26.7%) who received PMRT and 85 (73.3%) who did not. At a median follow-up time of 56.4 months, the 5-year DFS and OS rates were 90.2% and 96.7% with PMRT and 93.7% and 97.3% without PMRT, respectively. PMRT did not affect either DFS (p = 0.234) or OS (p = 0.878). On multivariate analyses, no differences in DFS or OS between the two groups were detected, taking into consideration the following factors: age, molecular subtype, Ki67 index, cT stage, and in-breast pathologic complete response (DFS: HR 2.260; 95% CI 0.465–10.982; p = 0.312. OS: HR 1.400; 95% CI 0.138–14.202; p = 0.776). This nonsignificant difference was also consistent in subgroup analyses (all p > 0.05).ConclusionsPMRT has limited ability to confer DFS or OS benefits for cT1-2N1 breast cancer patients who achieved axillary pathological complete response after NAC and total mastectomy. It is imperative to conduct prospective studies to investigate the safety and feasibility of omitting PMRT.Trial registration: This research was approved by the Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (ID: No. 2021–442).

A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma.

Introduction: Renal cell carcinoma (RCC) is one of the most common urinary tumors. The risk of metastasis for patients with RCC is about 1/3, among which 30−40% have lymph node metastasis, and the existence of lymph node metastasis will greatly reduce the survival rate of patients. However, the necessity of lymph node dissection is still controversial at present. Therefore, a new predictive model is urgently needed to judge the risk of lymph node metastasis and guide clinical decision making before operation. Method: We retrospectively collected the data of 189 patients who underwent retroperitoneal lymph node dissection or enlarged lymph node resection due to suspected lymph node metastasis or enlarged lymph nodes found during an operation in Tongji Hospital from January 2016 to October 2021. Univariate and multivariate logistic regression and least absolute shrinkage and selection operator (lasso) regression analyses were used to identify preoperative predictors of pathological lymph node positivity. A nomogram was established to predict the probability of lymph node metastasis in patients with RCC before surgery according to the above independent predictors, and its efficacy was evaluated with a calibration curve and a DCA analysis. Result: Among the 189 patients, 54 (28.60%) were pN1 patients, and 135 (71.40%) were pN0 patients. Three independent impact factors were, finally, identified, which were the following: age (OR = 0.3769, 95% CI = 0.1864−0.7622, p < 0.01), lymph node size according to pre-operative imaging (10−20 mm: OR = 15.0040, 95% CI = 1.5666−143.7000, p < 0.05; >20 mm: OR = 4.4013, 95% CI = 1.4892−7.3134, p < 0.01) and clinical T stage (cT1−2 vs. cT3−4) (OR = 3.1641, 95% CI = 1.0336−9.6860, p < 0.05). The calibration curve and DCA (Decision Curve Analysis) showed the nomogram of this predictive model had good fitting. Conclusions: Low age, large lymph node size in pre-operative imaging and high clinical T stage can be used as independent predictive factors of pathological lymph node metastasis in patients with RCC. Our predictive nomogram using these factors exhibited excellent discrimination and calibration.

The Value of Clinical Anatomy, Imaging, Breast Gland Surgery and Therapeutic Implications in Breast Cancer

Breast cancer is a common disease in women over the age of 50. The risk of breast cancer in women between the ages of 30 to 39 is 1 in 250 women, and in women between the ages of 40 to 49 is 1 in 70 women. Material and method. We analysed clinicopathological data of the breast cancer on a series of 32 cases that underwent surgery between 2020–2021 in General Surgery Department of ”Providenta” Hospital Iasi, Romania. This includes the mammary gland and the cellular-adipose tissue placed between the glandular lobes and lobules together with blood and lymphatic vessels, and nerves. The study was conducted after the surgery on the parts resected through it, but we also used the explorations performed for diagnosis and stage evaluation such as breast ultrasound, mammography, staging CT. The patients ranged between 58 and 71 years old and came from rural areas. The anatomopathological examination confirmed the preoperative diagnosis, the patients being referred to oncology for evaluation followed by adjuvant treatment.

CORRELATION OF CT STAGING AND BIOCHEMICAL PARAMETERS IN ASSESSING DISEASE SEVERITY AND MORTALITY OF COVID -19 PATIENTS

Abstract: Background CT chest has become the front-line investigation even for a Real-time polymerase chain reaction (RT-PCR) negative patient due to low viral load. Many grading systems were formulated to assess the severity of lung involvement and combined with inflammatory markers like ferritin (Fr) and C reactive protein (CRP) to provide a guide for diagnosing and managing COVID patients. Methods After being tested with RT-PCR, Severe acute respiratory syndrome coronavirus -2(SARS-CoV-2) patients who were referred for CT were included in our study. A non-contrast CT scan of the chest was obtained with 16 slice -Toshiba with 1mm collimation. Findings documented included the presence and extent of ground glass opacities; consolidation whether round, linear, patchy, lobar, or diffuse; septal thickening; and other features of pre-existing diseases like cavity, bronchiectasis, pleural effusion, and cardiomegaly. CT staging was done based on the progress of the disease and compared with biochemical parameters. Results 571 patients; between the ages of 19 and 88 suspected to have Coronavirus pneumonia were included in the study. CT stages were compared with the median value of LDH, Fr, TGL, AND CRP All biochemical parameters LDH 692 (438.5 -771 ) (p-value 0.0001), Fr 1.27 (0.64 -1.89) (p-value 0.0001), and CRP (113.4 (95.5 2-207.7 ) (p-value 0.0001), were elevated in higher CT stages. Both elevated biochemical parameters and higher CT stages were associated with the severity and mortality of the disease. No significant p-value was noted with TGL. Conclusions Covid 19 pneumonia starts as a respiratory infection but spreads to become a systemic disease. The inflammation is associated with an increase in biochemical parameters which correlate with the staging of the lung by CT and in dead patients.

Prognostic stratification of oropharyngeal cancer patients in a betel nut chewing and low HPV area

BackgroundThis study aimed to establish a simple predictive model for oropharyngeal cancer (OPC) in an area with a relatively low prevalence of human papillomavirus (HPV) and frequent betel nut chewing.MethodsA total of 116 patients with OPC were recruited from the clinical research database of a referral cancer center between 2013 and 2018. Patient characteristics—including age, gender, tumor stage, differentiation, and treatment modality—were extracted from the database. Patients diagnosed after 2018 were staged using the 7th AJCC staging system to explore the impact of extra-nodal tumor extension (ENE) on survival. Immunohistochemical analysis was performed for p16, epidermal growth factor receptor (EGFR), p53, and programmed cell death ligand 1 (PD-L1). ENE status was evaluated by pathological analysis or radiological features. Primary outcome was disease-specific overall survival (OS). Univariate and multivariate Cox regression were used to establish a predictive model.ResultsMean age was 57.3 ± 9.9 years; 103 patients (88.8%) were male. P16 positive OPC was positively associated with higher PD-L1 and a tonsillar sub-site and negatively associated with betel nut chewing and cigarette smoking. In Cox regression, age, p16 status, EGFR, cT4, ENE, and cigarette smoking were significantly associated with OS. In survival tree analysis, cT stage was the most important risk stratification parameter, followed by EGFR expression and p16 status. Patients with cT4 stage or high EGFR were classified as the high-risk group and had poorest OS.ConclusionsDue to the low prevalence of HPV and popularity of betel nut chewing in Asia, the relative importance of prognostic predictors for OPC are not identical to Western countries. Identification of significant prognostic biomarkers may improve treatment.Trial registration This study was registered and approved by the Institutional Review Board (IRB) of Kaohsiung Veterans General Hospital (VGHKS19-CT9-07; date of approval: Aug 9, 2019).Graphic

Oncological outcomes of whole-gland cryoablation in patients with prostate cancer and high risk of lymph node invasion

Prostate cryoablation has been proposed as an alternative to radical prostatectomy for men with localized prostate cancer (PCa); however, it is limited by the lack of data regarding oncological outcomes and the impossibility of performing a lymph node dissection. The aim of this study was to assess if whole-gland cryoablation is oncologically safe, especially for patients in whom pelvic lymph node dissection would be necessary. After institutional review board approval, we identified 102 patients who underwent whole-gland prostate cryoablation between 2013 and April 2019. Lymph node invasion (LNI) probability was computed using Briganti nomogram, and a 5% cutoff probability was used to stratify the population in two groups. Biochemical recurrence after procedure was assessed using Phoenix criteria. Multiparametric magnetic resonance imaging, (CT), and bone scan or choline positron-emission tomography/CT were performed for the detection of distant metastases. Seventeen (17%) patients were treated for a low-risk PCa, 48 (47%) patients were at intermediate-risk PCa, and 37 (36%) patients were at high-risk PCa. Patients with a probability of LNI >5% (n = 46) exhibited higher prostate-specific antigen (PSA), PSA density, ISUP Grade Group, CT stage, and european association of urology (EAU) risk. Recurrence-free survival rates at 3 years' follow-up were 93%, 82%, and 72%, respectively for low-, intermediate-, and high-risk patients. At a median follow-up of 37 months (17-62), additional treatment and metastasis-free survival were 84% and 97%, respectively. No differences in oncological outcomes were found in patients with a probability of LNI above and below 5%. Prostate whole-gland cryoablation can be considered a safe procedure with acceptable outcomes in low- and intermediate-risk patients. A high preoperative risk of nodal involvement could not be considered an exclusion criterion to perform cryoablation. Further studies are required.

New Imaging Techniques.

The chapter discusses the advancement of new imaging techniques, the role of imaging in CCA diagnosis, anatomical and morphological classification, ultrasound screening of CCA, ultrasound findings of MF-CCA, PI-CCA, ID-CCA, the use of CT in CCA diagnosis, staging and treatment planning, CT volumetry and estimation of future liver remnant, post-treatment follow-up and surveillance, MRI imaging, Positron Emission Tomography (PET)/CT, limitations to contrast studies and resolution, internal receivers for CCA imaging, and in vitro imaging of CCA.

Pregnancy-associated breast malignancy mostly presents with an aggressive type of breast cancer

Published reports on the prognosis of pregnancy-associated breast cancer are controversial. This study aims to determine the histopathological features of pregnancy-associated breast carcinoma (PABC) and the outcomes of patients with breast cancer during pregnancy and lactation among Turkish women. The study retrospectively analyzed 29 patients diagnosed with pregnancy-associated breast malignancies who underwent surgery between January 1989 and March 2021. Demographic and pathological data were obtained to evaluate the clinicopathological and prognostic characteristics of the patients. The median age was 36 years (range: 26–42 years). Of the 29 patients with breast cancer, 13 (44.8%) were diagnosed during pregnancy, and the remaining 16 (55.2%) were diagnosed during lactation. Most patients had clinical tumor stage (cT) cT2–3 (n = 20, 69%) disease, and 15 patients had clinically node (cN)-positive disease (N1 and N2, 51.7%). The majority (n = 19, 65.5%) had invasive ductal carcinoma with high Ki-67 scores (&gt;20%). Patients with lactation-associated breast cancer were more likely to have a family history of breast cancer (44% vs. 8%, p = 0.04) than those with pregnancy-associated breast cancer. Notably, symptom duration ≥6 months and presenting with cT3–4 or cN(+) disease were associated with poor disease-free and disease-specific survival. However, no difference could be found in outcome among patients with pregnancy- and lactation-associated breast cancer. PABC mostly presents with aggressive tumor molecular subtypes with high Ki-67 scores and more advanced stages associated with poor outcome, possibly due to delayed diagnosis. Therefore, prompt early diagnosis and awareness of this disease might improve survival.

A deep learning approach for predicting visceral pleural invasion in cT1 lung adenocarcinoma.

Currently, patients with cT1 stage non-small cell lung cancer measuring less than 2 cm are recommended to undergo sublobar resection. However, it should be noted that there is tumor heterogeneity within these lung nodules. Potential visceral pleural invasion (VPI) is regarded as a significant factor that contributes to local recurrence and poorer prognosis after sublobar resection and postoperative upstaging of the T-stage. Currently, there are no effective techniques for preoperative or intraoperative prediction of the status of VPI in lung nodules. The primary objective of this study is to develop a machine learning model for the non-invasive prediction of VPI, thereby providing surgical decision-making support for surgeons during operations. A total of 983 patients with nodules located within 5 mm distance from the pleura were included. Machine learning models were developed utilizing preprocessed 2D, 2.5D, and 3D computed tomography (CT) imaging data. These models were employed to predict the status of VPI, leveraging radiomics and deep learning techniques. The aforementioned three groups of data were further categorized into region of interest (ROI)-only (exclusively focused on the ROI) and ROI-rect (the minimum bounding rectangle or cuboid of the ROI) groups, based on whether they included images outside the ROI. Receiver operating characteristic (ROC) curves were created for the assessment of predictive accuracy across different models. Employing the Youden's index, patients were categorized into high-risk and low-risk groups based on the model's criteria, which was then followed by an in-depth analysis of overall survival rates among the distinct patient cohorts. This study included a training cohort of 786 patients and a validation cohort of 197 patients. In comparison to radiomic and radiological models, deep learning models, especially the 2D-rect model, demonstrated better predictive performance. Although the 3D-ROI-only model exhibited the highest areas under the curve (AUC) value (0.952), its predictive performance for the status of VPI was found to be inferior according to the decision curve, calibration curve, and survival analysis. The developed deep learning signature offers a robust instrument for the precise prognostication of vascular invasion in stage cT1 lung adenocarcinoma, thereby enhancing stratification for prognostic evaluation. Moreover, the application of this advanced computational model aids in the refinement of therapeutic approach formulation for individuals diagnosed with cT1 lung adenocarcinoma.

Patients achieved pCR during neoadjuvant chemotherapy had better outcome than adjuvant chemotherapy setting in breast cancer: A comparative study

Purpose: Pathological complete response(pCR) during neoadjuvant chemotherapy(NAC) has been proposed as a predictor for better prognosis in breast cancer. However, few studies compare the outcomes of patients receiving NAC and adjuvant chemotherapy(AC). Methods: We retrospectively matched the patients who received NAC(N = 462) and AC(N = 462) by age, time of diagnosis, and primary clinical stage using the propensity score match in breast cancer patients treated in Sir Run Run Shaw Hospital with the median follow up of 67 months. Death from breast cancer and recurrence were used as endpoints. A multivariable Cox models were used to estimate the hazard ratios for breast-cancer specific survival (BCSS) and DFS. A multivariable logistic regression model was simulated to predict pCR. Results: In patients who received NAC, 18.0%(83/462) patients achieved pCR, while the rest of the patients did not. pCR subgroup demonstrated significant better BCSS and DFS than patients receiving AC(BCSS: HR = 0.39, 95% CI:0.12–0.93, P = 0.03; DFS: HR = 0.16, 95%CI 0.009–0.73, P = 0.013) and non-pCR patients(BCSS: HR = 0.32, 95%CI 0.10–0.77, P = 0.008; DFS: HR = 0.12, 95%CI 0.007–0.55, P = 0.002). Patients who received AC demonstrated insignificant survival compared to non-pCR patients(BCSS: HR= 0.82, 95%CI 0.62–1.10, P = 0.19; DFS: HR = 0.75, 95%CI 0.53–1.07, P = 0.12). Patients with AC had significant better DFS than non-pCR patients(HR = 0.33, 95% CI 0.10–0.94, P = 0.04) in luminal B Her2+ patients. More NAC cycles(>2), TNBC, lower cT stage, and mixed histology indicate higher possibility of pCR(AUC = 0.89). Conclusion: pCR patients with NAC indicated better prognosis than patients receiving AC or non-pCR patients from NAC. The timing of chemotherapy may need carefully pondering in luminal B Her2+ patients.

Analysis of a Biopsy-Based Genomic Classifier in High-Risk Prostate Cancer: Meta-Analysis of the NRG Oncology/Radiation Therapy Oncology Group 9202, 9413, and 9902 Phase 3 Randomized Trials

Decipher is a genomic classifier (GC) prospectively validated postprostatectomy. We validated the performance of the GC in pretreatment biopsy samples within the context of 3 randomized phase 3 high-risk definitive radiation therapy trials. A prespecified analysis plan (NRG-GU-TS006) was approved to obtain formalin-fixed paraffin-embedded tissue from biopsy specimens from the NRG biobank from patients enrolled in the NRG/Radiation Therapy Oncology Group (RTOG) 9202, 9413, and 9902 phase 3 randomized trials. After central review, the highest-grade tumors were profiled on clinical-grade whole-transcriptome arrays and GC scores were obtained. The primary objective was to validate the independent prognostic ability for the GC for distant metastases (DM), and secondary for prostate cancer-specific mortality (PCSM) and overall survival (OS) with Cox univariable and multivariable analyses. GC scores were obtained on 385 samples, of which 265 passed microarray quality control (69%) and had a median follow-up of 11 years (interquartile range, 9-13). In the pooled cohort, on univariable analysis, the GC was shown to be a prognostic factor for DM (per 0.1 unit; subdistribution hazard ratio [sHR], 1.29; 95% confidence interval [CI], 1.18-1.41; P < .001), PCSM (sHR, 1.28; 95% CI, 1.16-1.41; P < .001), and OS (hazard ratio [HR], 1.16; 95% CI, 1.08-1.22; P < .001). On multivariable analyses, the GC (per 0.1 unit) was independently associated with DM (sHR, 1.22; 95% CI, 1.09-1.36), PCSM (sHR, 1.23; 95% CI, 1.09-1.39), and OS (HR, 1.12; 95% CI, 1.05-1.20) after adjusting for age, Prostate Specific Antigen, Gleason score, cT stage, trial, and randomized treatment arm. GC had similar prognostic ability in patients receiving short-term or long-term androgen-deprivation therapy, but the absolute improvement in outcome varied by GC risk. This is the first validation of a gene expression biomarker on pretreatment prostate cancer biopsy samples from prospective randomized trials and demonstrates an independent association of GC score with DM, PCSM, and OS. High-risk prostate cancer is a heterogeneous disease state, and GC can improve risk stratification to help personalize shared decision making.

Establishing and validating predictive nomograms for lateral pelvic lymph node metastasis in patients with rectal cancer based on radiologic factors and clinicopathologic characteristics

IntroductionIt is critical to accurately predict the occurrence of lateral pelvic lymph node (LPN) metastasis. Currently, verified predictive tools are unavailable. This study aims to establish nomograms for predicting LPN metastasis in patients with rectal cancer who received or did not receive neoadjuvant chemoradiotherapy (nCRT). Materials and methodsWe carried out a retrospective study of patients with rectal cancer and clinical LPN metastasis who underwent total mesorectal excision (TME) and LPN dissection (LPND) from January 2012 to December 2019 at 3 institutions. We collected and evaluated their clinicopathologic and radiologic features, and constructed nomograms based on the multivariable logistic regression models. ResultsA total of 472 eligible patients were enrolled into the non-nCRT cohort (n = 312) and the nCRT cohort (n = 160). We established nomograms using variables from the multivariable logistic regression models in both cohorts. In the non-nCRT cohort, the variables included LPN short diameter, cT stage, cN stage, histologic grade, and malignant features, and the C-index was 0.930 in the training cohort and 0.913 in the validation cohort. In the nCRT cohort, the variables included post-nCRT LPN short diameter, ycT stage, ycN stage, histologic grade, and post-nCRT malignant features, and the C-index was 0.836 in the training dataset and 0.827 in the validation dataset. The nomograms in both cohorts were moderately calibrated and well-validated. ConclusionsWe established nomograms for patients with rectal cancer that accurately predict LPN metastasis. The performance of the nomograms in both cohorts was high and well-validated.

Medium-term oncological outcomes of intermediate-risk prostate cancer treated with HIFU or cryotherapy. A single center 10-year experience.

Focal therapies (FTs) are promising techniques for the treatment of localized prostate cancer. We assessed the medium-term oncological outcomes of intermediate-risk prostate cancer (PCa) treated with HIFU or cryotherapy. One-hundred and fifty consecutive patients with intermediate-risk PCa, treated between 2009 and 2018 at a single center were included. Primary study outcome was failure-free survival (FFS), defined as absence of additional treatment, systemic progression or prostate cancer related death. Thirty-seven (25%) patients underwent cryotherapy and 113 (75%) HIFU. Median age was 69 (IQR 62-72) years, with 36 (24%) presenting palpable disease on rectal examination, and median total PSA of 7.85 (IQR 5.75-10.62) ng/mL. Patients were followed for a median of 61 (IQR 48-82) months. FFS at 2 and 4 years was of 75.6% and 53.6%, respectively. Survival from whole gland or systematic treatment at 2 and 4 years was of 78.9% and 53.9%, respectively. Patients with FFS presented lower total PSA nadir (1.89 vs 3.25 ng/mL, p < 0.001), higher % PSA reduction at 3 months (66.1% vs 49.3%, p < 0.001), and at nadir (75.5% vs 55.8%, p < 0.001). Other characteristics such has the treatment modality, age, prostate size, initial total PSA, cT stage, International Society of Urological Pathology (ISUP), tumor location and biopsy results by region did not differ between patients failing and not failing FT. Complications were uncommon (13%), with only onr (1%) patient having Clavien-Dindo grade > II. No deaths due to treatment were registered. At medium-term, FTs for intermediate-risk PCa presented good oncological results, with an excellent safety profile.

OGC P20 Metabolic tumour and nodal response to neoadjuvant chemotherapy on FDG PET-CT as a predictor of pathological response and survival in patients undergoing surgical resection for locally advanced oesophageal adenocarcinoma

Abstract Background 18F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) is routinely used for staging of oesophageal cancer and has an emerging role in assessing response to neoadjuvant therapy. Several studies have demonstrated that a reduction in FDG avidity of the primary tumour and loco-regional lymph nodes following neoadjuvant chemotherapy predicts pathological response and survival in this patient group. However, no studies have evaluated the prognostic significance of metabolic parameters with respect to pathological response in lymph nodes. Change in primary tumour maximum standardised uptake value (SUVmax) is the most widely used FDG PET-CT parameter to define metabolic response, with various thresholds described. The most commonly utilised are a 35% reduction in SUVmax (MUNICON), and a 30% reduction in SUVmax (PERCIST). However, there is no consensus regarding the optimal classification; the MUNICON threshold was derived from only 40 patients and PERCIST is not tumour specific. The primary aim of this study was to evaluate the ability of FDG PET-CT to predict pathological response in the primary tumour (pTR) and lymph nodes (pNR) in patients with oesophageal adenocarcinoma undergoing neoadjuvant chemotherapy before surgery. Secondary aims were to assess the prognostic effect of metabolic and pathological response and evaluate the predictive ability of response classifications. Methods Cohort study of 75 patients with locally advanced oesophageal or oesophago-gastric junctional adenocarcinoma who underwent FDG-PET-CT before and after neoadjuvant chemotherapy, prior to surgical resection at Guy's and St Thomas’ NHS Foundation Trust, London, UK, between 2017–2020. SUV metrics related to the primary tumour and loco-regional lymph nodes were derived on pre- and post- treatment FDG PET-CT. pTR and pNR were evaluated using the Mandard classification. Patients with Mandard scores of 1–3 were classified as pathological responders and those with Mandard scores of 4–5 as non-responders. Clinicopathological characteristics were compared using the Chi-squared test. Receiver operator characteristic (ROC) analysis was performed and area under the curve (AUC) calculated to determine optimum SUVmax thresholds for metabolic response in the primary tumour (mTR) and lymph nodes (mNR). Survival curves were created using the Kaplan-Meier method, with subgroups compared using the log-rank test. Survival analysis was performed using Cox proportional hazards regression providing hazard ratios (HR) with 95% confidence intervals (CI) adjusted for age (continuous), sex (male or female), chemotherapy regimen (ECX or FLOT), cT stage (cT1–2 or cT3–4), cN stage (cN0 or cN+), tumour grade (well / moderately differentiated or poorly differentiated) and presence of signet ring cells (yes or no). Results Mean age was 63 years with the majority male (86.7%). Almost two thirds received FLOT (48/75, 64.0%) with the remainder receiving ECX chemotherapy. There was discordance between pathological response in the primary tumour and lymph nodes in several patients, including 23.1% (6/26) who demonstrated a lymph node response in the absence of a response in the primary tumour. ROC analysis demonstrated an optimum tumour SUVmax decrease of 51.2% for predicting pTR. Using a pragmatic cut-off of 50% this provided better prediction of pTR (AUC 0.714, sensitivity 73.5%, specificity 69.2%, p&amp;lt;0.001) than PERCIST (AUC 0.631, sensitivity 87.8%, specificity 38.5%, p=0.008) and MUNICON (AUC 0.659, sensitivity 85.7%, specificity 46.2%, p=0.003) criteria. ROC analysis demonstrated an optimum nodal SUVmax decrease of 32.6% for predicting pNR or pathological node negativity. Using a pragmatic 30% SUVmax cut-off and excluding metabolically negative nodes, mNR demonstrated high sensitivity but low specificity (AUC 0.749, sensitivity 92.6%, specificity 57.1%, p=0.010) for predicting pNR. pTR, mTR, pNR and mNR were independent predictive factors for overall survival on adjusted analysis (pTR responder HR 0.10 95% CI 0.03–0.34; mTR responder HR 0.17 95% CI 0.06–0.48; pNR responder HR 0.17 95% CI 0.06–0.54; mNR responder HR 0.13 95% CI 0.02–0.66). Conclusions In this study metabolic response on FDG PET-CT after neoadjuvant chemotherapy was predictive of pathological response in both the primary tumour and lymph node metastases of patients with oesophageal adenocarcinoma. Patients who had a favourable metabolic or pathological response in the primary tumour or lymph nodes had improved survival compared to non-responders. It has been suggested that commonly utilised thresholds of SUVmax are not optimal for response assessment in this patient group. This is supported by the results of the present study which suggest a reduction in SUVmax of 50% in the primary tumour was not only a better predictor of pathologic response, but also tumour recurrence and survival compared with PERCIST and MUNICON criteria. No previous studies have evaluated the ability of FDG PET-CT to predict pathologic nodal response despite recent findings suggesting it is an independent predictor of survival and evidence of a discrepancy, in some patients, who demostrate a nodal response in the absence of a response in the primary tumour. The use of FDG PET-CT in assessing response to neoadjuvant chemotherapy remains an under researched area and further evaluation is needed to establish whether it could be used to tailor individualised treatment strategies.

OGC P47 The Role of Endoscopic Ultrasound Scan In Staging Patients With Oesophageal Cancer- A Retrospective Single Centre Study

Abstract Background There are conflicting opinions on the role of Endoscopic Ultrasound (EUS) in the staging of oesophageal cancer (OG) patients which can complicate and delay intervention. We aim to audit the use of EUS in the OG cancer staging pathway as well as assess accuracy in selected cases. Methods A retrospective audit of the hospital database of patients diagnosed with oesophageal carcinoma between January 2016 and March 2021.The duration between the first MDT and EUS performed was calculated. Concordance between initial CT and EUS stage as well as histology in patients that were offered direct to surgery were evaluated using Cohen's Weighted Kappa. Results A total of 301 patients were identified. Overall, there was a moderate agreement (K=0.526) between CT and EUS reported T Staging(p&amp;lt;0.001). There was substantial agreement (K=0.798) between CT reporting T2, T3 and EUS(p&amp;lt;0.0005). Twenty-seven patients underwent upfront surgery-11 were T1, 16 were T2 and T3 disease. Comparing to final histology, EUS reported an accurate T1 stage in 36.3% compared with 0% with CT (p=0.018), whereas T2 and T3 disease were accurately reported with EUS and CT in 43.7% and 37.5% respectively (p=0.375). The median number of days between first MDT and EUS was 14 days (8,18) and this was requested after CT and PET CT results were available in 80% of cases. Conclusions This audit demonstrates minor differences between EUS and CT for T2 and T3 disease and therefore unlikely to alter management. However, EUS is superior to CT for staging Tx and T1 disease and is therefore likely to impact on the treatment options. EUS also contributed to prolonged pre-treatment staging time. Adopting a selective approach to EUS could result in overall reduction of waiting times from referral to decision making and increase cost-effectiveness.