Assessment Of Treatment Response Research Articles

Global metabolomic profiling of tumor tissue and paired serum samples to identify biomarkers for response to neoadjuvant FOLFIRINOX treatment of human pancreatic cancer.

Neoadjuvant chemotherapy (NAT) is increasingly used for the treatment of non-metastatic pancreatic ductal adenocarcinoma (PDAC) and is established as a standard of care for borderline resectable and locally advanced PDAC. However, full exploitation of its clinical benefits is limited by the lack of biomarkers that assess treatment response. To address this unmet need, global metabolomic profiling was performed on tumor tissue and paired serum samples from patients with treatment-naïve (TN; n = 18) and neoadjuvant leucovorin calcium (folinic acid), fluorouracil, irinotecan hydrochloride and oxaliplatin (FOLFIRINOX)-treated (NAT; n = 17) PDAC using liquid chromatography mass spectrometry. Differentially abundant metabolites (DAMs) in TN versus NAT groups were identified and their correlation with various clinical parameters was assessed. Metabolomics profiling identified 40 tissue and five serum DAMs in TN versus NAT PDAC. In general, DAMs associated with amino acid andnucleotide metabolism were lower in NAT compared to TN. Four DAMs-3-hydroxybutyric acid (BHB), 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF), glycochenodeoxycholate and citrulline-were common to both tissue and serum and showed a similar pattern of differential abundance in both groups. A strong positive correlation was observed between serum carbohydrate 19-9 antigen (CA 19-9) and tissue carnitines (C12, C18, C18:2) and N8-acetylspermidine. The reduction in CA 19-9 following NAT correlated negatively with serum deoxycholate levels, and the latter correlated positively with survival. This study revealed neoadjuvant-chemotherapy-induced changes in metabolic pathways in PDAC, mainly amino acid and nucleotide metabolism, and these correlated with reduced CA 19-9 following neoadjuvant FOLFIRINOX treatment.

An energy-conserving dose summation method for dose accumulation in radiotherapy.

Radiation therapy often requires the accumulation of doses from multiple treatment fractions or courses for plan evaluation and treatment response assessment. However, due to underlying mass changes, the accumulated dose may not accurately reflect the total deposited energy, leading to potential inaccuracies in characterizing the treatment input. This study introduces an energy-conserving dose summation method to calculate the total dose in scenarios where patients experience changes in body mass during treatment. The proposed method transfers dose and mass data from dosimetry images, where the delivered doses were calculated, to a reference image using an energy and mass-conserving dose reconstruction technique. The reconstructed dose assumes the same resolution and dimension as the reference image. The transferred masses are averaged at each image voxel in the reference image to generate an average mass. The transferred doses are then adjusted by multiplying by the ratio of their transferred mass to the average mass, and subsequently summed to calculate a mass-weighted (MW) total dose at each voxel. This method is demonstrated with a case of lung cancer retreatment. The MW total dose was shown to be equivalent to the total deposited energy divided by the average mass. In the lung cancer retreatment case, the energy derived from the MW total dose was consistent with the sum of energy transferred from two treatments across all evaluated organs. The MW dose summation method can produce a total dose that accurately reflects the total energy deposited in each organ. The consistency may provide a robust foundation for verifying dose accumulations in adaptive radiotherapy.

Precision Oncology in Melanoma: Changing Practices.

Over the last 2 decades, significant progress has been made in our understanding of the genomics, tumor immune microenvironment, and immunogenicity of malignant melanoma. Historically, the prognosis for metastatic melanoma was poor because of limited treatment options. However, after multiple landmark clinical trials displaying the efficacy of combined BRAF/MEK inhibition for BRAF-mutant melanoma and the application of immune checkpoint inhibitors targeting the programmed death-1, cytotoxic T-lymphocyte antigen-4, and lymphocyte activation gene-3 molecules, overall survival rates have dramatically improved. The role of immune checkpoint inhibition has since expanded to the neoadjuvant and adjuvant settings with multiple regimens in routine use. Personalized therapies, including tumor-infiltrating lymphocytes that are extracted from a patient's melanoma and eventually reinfused into the patient, and messenger RNA vaccines used to target neoantigens unique to a patient's tumor, show promise. Improvements in accompanying imaging modalities, particularly within the field of nuclear medicine, have allowed for more accurate staging of disease and assessment of treatment response. Continued growth in the role of nuclear medicine in the evaluation of melanoma, including the incorporation of artificial intelligence into image interpretation and use of radiolabeled tracers allowing for intricate imaging of the tumor immune microenvironment, is expected in the coming years.

Developing a peripheral blood RNA-seq based NETseq ensemble classifier: A potential novel tool for non-invasive detection and treatment response assessment in neuroendocrine tumor patients receiving 177Lu-DOTATATE PRRT.

Neuroendocrine tumors (NETs) are presented with metastases due to delayed diagnosis. We aimed to identify NET-related biomarkers from peripheral blood. The development and validation of a multi-gene NETseq ensemble classifier using peripheral blood RNA-Seq is reported. RNA-Seq was performed on peripheral blood samples from 178 NET patients and 73 healthy donors. Distinguishing gene features were identified from a learning cohort (59 PRRT-naïve GEP-NET patients and 38 healthy donors). Ensemble classifier combining the output of five machine learning algorithms viz. Random Forest (RF), Extreme Gradient Boosting (XGBOOST), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and Logistic Regression (LR) were trained and independently validated in the evaluation cohort (n = 106). The response to PRRT was evaluated in the PRRT cohort (n = 46) and the PRRT response monitoring cohort (n = 16). The response to 177Lu-DOTATATE PRRT was assessed using RECIST 1.1 criteria. The Ensemble classifier trained on 61 gene features, distinguished NET from healthy samples with 100% accuracy in the learning cohort. In an evaluation cohort, the classifier achieved 93% sensitivity (95% CI: 87.8%-98.03%) and 91.4% specificity (95% CI: 82.1%-100%) for PRRT-naïve GEP-NETs (AUROC = 95.4%). The classifier returned >87.5% sensitivity across different tumor characteristics and outperformed serum Chromogranin A sensitivity (χ2 = 21.89, p = 4.161e-6). In the PRRT cohort, RECIST 1.1 responders showed significantly lower NETseq prediction scores after 177Lu-DOTATATE PRRT, in comparison to the non-responders. In an independent response monitoring cohort, paired samples (before PRRT and after 2nd or 3rd cycle of PRRT) were analyzed. The NETseq prediction score significantly decreased in partial responders (p = .002) and marginally reduced in stable disease (p = .068). The NETseq ensemble classifier identified PRRT-naïve GEP-NETs with high accuracy (≥92%) and demonstrated a potential role in early treatment response monitoring in the PRRT setting. This blood-based, non-invasive, multi-analyte molecular method could be developed as a valuable adjunct to conventional methods in the detection and treatment response assessment in NET patients.

The Added Value of Apparent Diffusion Coefficient and Histogram Analysis in Assessing Treatment Response of Locally Advanced Cervical Cancer

Objective The aim of the study is to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging in assessing treatment response in cervical cancer patients. Methods A retrospective analysis was done for 50 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy and underwent magnetic resonance imaging and diffusion-weighted imaging. Treatment response was classified into 4 categories according to RECIST criteria 6 months after therapy completion. Apparent diffusion coefficient (ADC) values were measured using both region of interest (ROI) ADC and whole lesion (WL) ADC histogram for all cases at both baseline pretreatment and posttreatment Magnetic resonance imaging studies. Changes in ADC values were calculated and compared between groups. Results The percentage change of ROI-ADCmean at a cutoff value of >20 had excellent discrimination of responders versus nonresponders, while the percentage change of WL-ADCmean, ADCmin, and ADCmax at cutoff values of >12.5, >35.8, and > 19.6 had acceptable discrimination of responders versus nonresponders. Logistic regression analysis revealed that only baseline WL ADCmin was a statistically significant independent predictor of response. Cancer cervix patients with baseline ADCmin < or equal to 0.73 have 12.1 times higher odds of exhibiting a response. Conclusions The percentage change of ROI-ADCmean and WL histogram ADCmean values after concurrent chemoradiotherapy can predict response. Pretreatment WL histogram ADCmin was a statistically significant independent predictor of posttherapy response.

HPB SO38 - Assessing current pancreatic cancer reporting practice against the PACT-UK Synoptic Reporting Template: An initial clinical audit

Abstract Background In the last decade, the incidence of pancreatic cancer has increased by 9% in the UK. The gold standard for initial assessment of pancreatic cancer (or even peri-ampullary cancer) resectability is pancreatic-protocol CT scan. The PACT-UK project introduced a synoptic template for pancreatic cancer to standardise CT reporting practice across UK and enable consistent reporting of pertinent aspects of resectability status such as vascular involvement of the tumour. The aim of this audit is to assess the quality of current CT reports received by a tertiary hepato-pancreato-biliary (HPB) unit against the standards set out by PACT-UK. Method A retrospective analysis of 66 patients who underwent pancreatic resection between September 2023 and May 2024 at a tertiary HPB centre was undertaken. Patients were excluded from the analysis if they underwent resection for benign pancreatic pathology, were diagnosed with pathology other than peri-ampullary cancer or did not have a formal report of their CT scan. Initial CT scans performed at presentation and if available, subsequent up-to-date staging scan prior to surgery were assessed against the PACT-UK reporting template, in accordance with their guidance. The audit was registered with our clinical audit team (no. 11643). Results In total, 42 patients with peri-ampullary cancers were included in this audit. All patients had a reported CT scan on presentation. Additionally, 24 patients had a reported staging CT scan. The compliance (i.e. more than 90% information available) with PACT-UK reporting standards was 0% for initial presentation scans and 4.2% (n=1) for staging scans. The only staging scan with >90% compliance was reported using the PACT-UK template. Majority (more than 80%) of CT scan reports lacked information on aspects such as pancreatic duct size, predicted tumour type and radiological stage, variant vascular anomalies, and arterial/venous involvement. Conclusion This audit highlights the substandard quality of current CT reporting for peri-ampullary cancer. There is an urgent need to adopt a structured and dedicated reporting template to address the issue. Utilising a template such as the one developed by PACT-UK will help ensure that relevant information is formally reported to facilitate optimal decision-making at MDT meetings, and assist surgeons in operative planning and oncologists in assessing treatment response.

Abstract B020: A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness

Abstract Introduction: The standard clinical assessment for treatment response of lymphoma currently relies on periodic functional imaging examinations. In this prospective study, we utilized a blood-based multi-omics test, SeekInClarity, to evaluate treatment response and predict patient outcomes in the major types of lymphoma. Methods: 116 patients with various lymphoma subtypes were recruited from two clinical centers: The First Affiliated Hospital of Zhengzhou University and Sun Yat-sen University Cancer Center. Blood samples were collected at pre- treatment (baseline) and after two cycles of treatment (landmark) for SeekInClarity analysis, which integrated shallow whole-genome sequencing (sWGS) data of circulating-free DNA (cfDNA), including copy number aberrations (CNA) and fragment size (FS), with seven protein markers. The molecular tumor burden (MTB) score was calculated with SeekInClarity to assess the therapeutic efficacy of patients. Results: At 95.2% specificity, cancer signals were detected in 74.1% (86/116) of patients at baseline. Higher MTB scores were associated with advanced tumor stages, with MTB+ ratios of 31.8%, 63.6%, 84.6%, and 91.2% for stage I, II, III, and IV, respectively. After two cycles of treatment, patients with MTB+ status exhibited significantly poorer progression-free survival (PFS) (HR: 0.13, 95% CI, 0.05-0.33, P < 0.001) and overall survival (OS) (HR: 0.24, 95% CI, 0.06-0.97, P < 0.05) compared to MTB- patients. These trends were consistent across stages, subtypes, and treatment regimens. Traditional biomarkers, lactate dehydrogenase (LDH) and β2-microglobulin (B2M), showed no OS difference between high and low expression groups. The disease progression (PD) rate was 5.2 times higher in the MTB+ group (41.5%) than in the MTB- group (8.0%, P < 0.001), outperforming LDH (1.1 times, 20.7% vs 18.1%, P = 0.15) and B2M (3.1 times, 43.8% vs 14.0%, P = 0.02). All 116 patients, except four with stable disease, were classified as partial or complete response based on imaging at the landmark analysis. However, 13 patients experienced disease progression within six months after treatment. Notably, six (46.2%) were identified earlier through MTB reduction at the landmark. Greater MTB reduction at landmark associated with better OS (P<0.05). Multivariate Cox regression analysis confirmed MTB reduction at landmark as an independent prognostic indicator for PFS, with low reduction indicating a significant increase in disease progression (HR: 0.11, 95% CI: 0.03-0.42, P < 0.001), while other clinical parameters were not significant. Conclusions: This study confirms the clinical utility of SeekInClarity in evaluating lymphoma treatment responses. Reductions in MTB during treatment are associated with patient survival and can predict therapeutic outcomes. Furthermore, post-treatment MTB status after two cycles is an independent prognostic indicator for both PFS and OS. Citation Format: Mao Mao, Wang Xin hua, Li Zhi ming, Chang Yu, Li Shi yong, Wu Wei, Chang Fang yuan, Chang Yin yin, Zhu Dan dan, Zhang Ming zhi. A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B020.

OGC SO15 - Utility of radiological re-staging following neo-adjuvant chemotherapy and its impact on oncological outcomes in resectable gastric adenocarcinoma

Abstract Background The current perioperative chemotherapy regimen that comprises the multimodal treatment strategy for gastric cancer consists of Fluorouracil, Leucovorin, Oxaliplatin, and Docetaxel. Despite improvement in outcomes at a population level, real-world data suggests that ≤40% of patients show a poor/no response to the neoadjuvant phase of treatment. Identification of these poor/non-responders may facilitate a re-evaluation of their treatment strategy and prevent potentially futile surgery. Radiological re-staging following neoadjuvant treatment is routinely performed despite its debatable accuracy and benefits. This study aimed to define the accuracy of radiological re-staging and its impact on survival following neoadjuvant treatment for resectable GC. Method Patients with resectable gastric cancer who completed 4 cycles of neoadjuvant FLOT and underwent resectional surgery with curative intent between 2018 and 2022 were retrospectively identified. All patients were clinically staged with gastroscopy, CT and staging laparoscopy. The index radiological/clinical stage at diagnosis was compared to the radiological re-staging following neoadjuvant treatment. Patient were re-staged with either a CT or PET-CT. Both were then compared with the final pathological stage to assess for correlation between the radiological and pathological stage. A survival analysis was then performed to evaluate the impact of radiological-pathological staging discrepancy on overall survival Results A total of 65 consecutive patients met the inclusion criteria of this study. On comparison of the index clinical stage with the radiological re-stage post-neoadjuvant treatment, 71% had concordant stages, 25% were downstaged, and 4% were upstaged. On comparison of the index clinical stage with the final pathological stage, 35% had concordant stages, 38% were upstaged and 27% were down staged (Cohen kappa = -0.224, 95% CI -0.390, -0.058). Discrepancy between clinical stage and radiological re-stage did not influence survival. However, discrepancy between clinical and pathological stage highlighted survival differences where upstaged patients had reduced survival (p = 0.018). Conclusion The accuracy of clinical staging compared to final pathological staging in the setting of aggressive tumour biology remains undefined. Radiological re-staging following neoadjuvant treatment proves to be an unreliable tool for assessing treatment response and does not predict long-term survival outcomes. These findings highlight the importance of accurate staging and the need for more precise methods of evaluating treatment response. This may enhance decision-making, individualise treatment regimens, and improve patient outcomes.

Predictive value of 68[Ga]Ga-DOTA-TATE PET/CT volumetric parameters in assessing treatment response to long-acting somatostatin analogues in patients with well-differentiated neuroendocrine tumours.

Over the past decade, numerous treatment options have emerged for patients with locally advanced and metastatic neuroendocrine tumours (NETs). Nevertheless, the optimal timing of treatment interventions remains uncertain, given the highly variable disease course observed in these patients, even when patients have the same tumour stage and grade. The aim of the study was to evaluate the predictive role of standardized uptake values (SUVs) and volumetric parameters obtained from pretreatment [68Ga]Ga-DOTA-TATE for response to SSA therapy in patients with NET. In this retrospective study, we included 42 patients (21 women, 21 men; age range: 46-84years) with histologically confirmed, metastatic, NET (G1 13, G2 28 cases); median Ki-67 index 5%, range 1-16) who received long acting SSA as a first line treatment and underwent [68Ga]Ga-DOTA-TATE PET/CT before SSA treatment. For all [68Ga]Ga-DOTA-TATE avid lesion SUVmax, SUVmean, somatostatin receptor expression tumour volume (STV), total lesion somatostatin receptor expression (TLD, STV multiplied by SUV mean) and Tmean/Smean (SUVmean of tumours/metastases divided by SUVmean of normal spleen) were measured. Finally, the sum of STV (total STV, TSTV) and TLD (total TLD, TTLD) was calculated for each patient and used in the analysis. During the study period, 14 patients had stable disease (33.3%) and 28 patients experienced progression (66.7%), among whom 12 patients died. The median progression-free survival (PFS) and overall survival (OS) were 26.5 and 46.5months, respectively. In the univariate and multivariate analysis, in the whole population study, Tmean/Smean ratio (HR 1.88, 95% CI 1.06-3.35, p = 0.03), Ki-67 index (HR 1.14, CI 1.03-1.26, p = 0.01) and pre-treatment chromogranin A serum concentration (HR 1.01, CI 1.0-1.03, p = 0.01) were significantly associated with PFS. Among patients with small intestinal NETs, TSTV (< 125.85 cm3 vs. ≥ 125.85 cm3, p = 0.023) and TTLD (< 4168.95 vs. ≥ 4168.95, p = 0.026) were significantly associated with PFS in the univariate analyses. No significant correlation was found between measured volumetric parameters and OS. Volumetric parameters of pretreatment 68[Ga]Ga-DOTA-TATE PET/CT may be useful in prediction of the response to SSA (used in monotherapy as a first-line therapy) in patients with NET.

First-in-Human: Simultaneous Hyperpolarized 1-13C-Pyruvate Magnetic Resonance Spectroscopy and 18F-FDG PET (hyperPET) Imaging of a Patient With Lymphoma.

Hyperpolarized 1-13C-pyruvate magnetic resonance spectroscopy (MRS) and MRS imaging (MRSI) offer noninvasive and real-time direct assessment of the altered metabolism of cancer cells known as the Warburg effect-a key hallmark of cancer. When combined with simultaneously acquired 18F-FDG PET in a PET/MR scanner, coined hyperPET by us, this dual-modality may unveil cancer-type specific glucose metabolic phenotypes with potential implications for patient prognostication, treatment-response assessment, and prediction. We here present the first human data of simultaneously acquired hyperpolarized MRS/MRSI and PET performed in a PET/MR scanner-and the first human hyperpolarized MRS/MRSI data from a patient with lymphoma.

NIMG-02. DEVELOPING A RADIOMIC HIERARCHICAL GAUSSIAN PROCESS BOOSTING MODEL TO PREDICT PRIMARY TUMOR ORIGIN FROM MULTICENTRIC LONGITUDINAL MRI DATA OF BRAIN METASTASES

Abstract Focal neurologic deficits due to brain metastases might be the initial presentation in patients with cancer. Common approaches to investigate the occult primary malignancy include a whole-body PET-CT, whole-body MRI, studying tumor markers, or histopathological examination. Most of these modalities are expensive, time-consuming, invasive, and delay treatment. The field of radiomics leverages quantitative features extracted from images to improve the decision-making process in clinical practices. Although not easily understandable, these features are proxies for the tumor’s shape, contour, texture, and intensity patterns. They can help understand tumor heterogeneity, predict tumor behavior, and assess treatment response. We propose a robust radiomic workflow using longitudinal MRI data from 914 high-resolution imaging studies from 12 different centers (Ocaña-Tienda et al. (2023), Ramakrishnan et al. (2023), Wang et al. (2023)) to predict the origin of brain metastases from brain MRI scans. After using ensemble feature selection methods, we trained three fixed-effects and one mixed-effects multiclass classification model to account for longitudinal data. Fixed-effects logistic regression and support vector kernel models performed the worst (AUC 0.74 and 0.75, respectively), while the random forest performed better (AUC 0.97). The mixed-effects hierarchical Gaussian process boosting (GPBoost) model performed the best with an accuracy of 85.8%, precision of 85.4%, sensitivity of 85.8%, specificity of 95.7%, and an AUC of 0.98. In one-versus-rest classification, the GPBoost model identified the primary tumor as melanoma with the highest accuracy (96.1%) and non-small cell lung cancer with the lowest accuracy (89.0%). Developing such models holds great promise in reducing patient and institutional costs, improving time to effective treatment, and enhancing overall survival rates through personalized therapy approaches. In the future, we hope that incorporating newer patient data and refining the model to improve external validity would enable more accurate and generalizable predictions, leading to better clinical outcomes across diverse populations.

BIOM-33. INVESTIGATING MIR-21 AS A NON-INVASIVE PROGNOSTIC BIOMARKER IN GLIOMA PATIENTS IN RESOURCE CONSTRAINT SETTINGS

Abstract BACKGROUND Glioma treatment remains challenging due to high recurrence rates and resistance to treatment. Diagnosis and follow-up in resource-constrained regions often leads to significant patient attrition. Serum microRNA (miRNA) expression profiles are shown to be expressed in tumor tissue and peripheral samples, offering a pathway for non-invasive, repetitive liquid biopsies. miR-21 shows promise in many populations; however, there is a dearth of data from our region. METHODOLOGY we collected 89 intraoperative tumor tissue samples, 42 pre- and post-operative serum samples from glioma patients, and included 10 control tissue samples along with 8 normal serum samples and analyzed for miR-21 expression through qPCR. Serum samples were collected before tumor resection and post-surgery (pre- and post-operative). Correlational analysis with molecular markers IDH, Ki-67, ATRX, p53, and survival curves through the Kaplan-Meier method were calculated in high and low miR-21 expression groups, The hazard ratio was quantitatively determined using Cox regression analysis, considering both univariate associations and multivariate correlations with clinical parameters. RESULTS miR-21 expression in tissue increased with higher grades of glioma (p=0.00064), of patients above 50 years (p=0.0027), and shows a positive correlation with tumor volume (r= 0.22, p=0.081). IDH-wildtype (p=2.06e-03) and high Ki-67 (p=2.50e-03) expression in tumors showed significant upregulation of miR-21 compared to IDH-mutant and low Ki-67. Patients with low miR-21 expression had significantly longer overall survival (OS) than patients with high miR-21 expression (p =0.006). Quantitative hazard analysis indicates that patients in the high expression group have a 2.77 times higher risk of mortality (95% CI: upper - 0.19, lower - 0.92), in comparison to patients in the low expression group (p= 0.008). CONCLUSION Our findings validate the future utility of miR-21 as a serum assay to help diagnose and assess treatment response in different grades of glioma, within our population. Keywords: Glioma, Biomarker, Molecular markers, Liquid biopsy

Magnetic resonance imaging techniques for monitoring glioma response to chemoradiotherapy.

Treatment response assessment for gliomas currently uses changes in tumour size as measured with T1- and T2-weighted MRI. However, changes in tumour size may occur many weeks after therapy completion and are confounded by radiation treatment effects. Advanced MRI techniques sensitive to tumour physiology may provide complementary information to evaluate tumour response at early timepoints during therapy. The objective of this review is to provide a summary of the history and current knowledge regarding advanced MRI techniques for early treatment response evaluation in glioma. The literature survey included perfusion MRI, diffusion-weighted imaging, quantitative magnetization transfer imaging, and chemical exchange transfer MRI. Select articles spanning the history of each technique as applied to treatment response evaluation in glioma were chosen. This report is a narrative review, not formally systematic. Chemical exchange saturation transfer imaging potentially offers the earliest method to detect tumour response due to changes in metabolism. Diffusion-weighted imaging is sensitive to changes in tumour cellularity later during radiotherapy and is prognostic for progression-free and overall survival. Substantial evidence suggests that perfusion MRI can differentiate between tumour recurrence and treatment effect, but consensus regarding acquisition, processing, and interpretation is still lacking. Magnetization transfer imaging shows promise for detecting subtle white matter damage which could indicate tumour invasion, but more research in this area is needed. Advanced MRI techniques show potential for early treatment response assessment, but each technique alone lacks specificity. Multiparametric imaging may be necessary to aid biological interpretation and enable treatment guidance.

NIMG-70. COMPARISON OF VOLUMETRIC AND CROSS-SECTIONAL MEASUREMENTS IN DIFFUSE MIDLINE GLIOMAS: RETHINKING RESPONSE ASSESSMENT

Abstract BACKGROUND The Response Assessment in Pediatric Neuro-Oncology (RAPNO) criteria, which are based on bidimensional or cross-sectional product (CP) measurements of tumor size, are the standard for assessing treatment response in diffuse midline glioma (DMG). This study aims to investigate the correlation between CP and volumetric measurements in progressive disease (PD) and compare their prognostic impact in pediatric patients with DMG. METHODS We retrospectively reviewed clinical and imaging data from 27 subjects with newly diagnosed DMG, encompassing 16 subjects from the PNOC003 and PNOC007 clinical trials and 11 subjects from the Children’s Hospital of Philadelphia. Tumors were segmented using a pretrained pediatric-specific autosegmentation model followed by manual revisions. Tumor volume and CP measurements were automatically derived from the outlined tumor. Cox regression analysis was used to compare the performance of CP and volumetric measurements in predicting overall survival (OS). The correlation between CP and volumetric thresholds for PD was assessed by linear regression. Comparison of survival of patients classified as PD versus non-PD by CP and volumetric measurements at 7 months post-baseline scan was performed using log-rank analysis. RESULTS Cox regression analysis demonstrated that volumetric measurements were significantly associated with OS (p=0.04), whereas CP measurements were not a significant predictor (p=0.07). An approximate 55% increase in segmented volume corresponded to a 25% increase in CP, which is the definition of PD according to RAPNO criteria (R2 = 0.71). At 7 months, volumetric classification of PD more accurately predicted survival than the CP method (p=0.06 for volumetric vs 0.14 for CP). CONCLUSION Our study showed that volumetric measurements are better predictors of survival compared to bidimensional measurements. We are extending this analysis to a larger sample size, examining survival at additional time points, and incorporating other factors influencing OS, such as treatment approaches.

BIOM-25. MOLECULAR PROFILING PREDICTS EARLY AND LATE PROGRESSION IN GLIOBLASTOMA

Abstract Patients with glioblastoma experience a wide variation in response to standard treatment, with nearly 30% experiencing tumour progression during treatment, and nearly 6% surviving more than 5 years. To date, there are few non-invasive clinical biomarkers to predict response to first – line treatment. Chemical exchange saturation transfer (CEST) MRI may have the potential to fill this gap. CEST MRI is sensitive to treatment-induced changes and changes in tumor metabolism. Our team has obtained CEST data for patients before, during and after the end of standard chemoradiation treatment, and found that CEST provides markers of early response and can identify early, standard and late progressors before treatment initiation. In this study, we aimed to establish molecular profiles of early, standard and late progressors with IDH wild-type glioblastoma. Patients (n=180) with primary, IDH wild-type glioblastoma were imaged with CEST-MRI at multiple time points throughout standard chemoradiation treatment. DNA and RNA were co-extracted from matched normal and tumour pairs and processed for whole genome sequencing, enzymatic methyl-seq and gene expression analysis using Nanostring. Clinical variables such as age, extent of resection, sex, ECOG status and MGMT promoter methylated were also collected. A survival analysis was conducted using the Kaplan-Meier method with log-rank tests. Univariate and multi-variate hazard ratios for clinical variables were calculated by fitting Cox Proportional Hazards Models. Early progressors reported a median progression-free survival (PFS) of 142 days compared to 832 days in late progressors (p&amp;lt;0.0001). Early progressors also harbored distinct and statistically significant differences in gene expression and genomic alterations, namely in DNA damage repair, glucose transport and arginine metabolism pathways. A gene signature was prognostic of PFS and overall survival. Collectively, this data has the potential to serve as a radiogenomic biomarker to assess treatment response before or within early phases of treatment and allow for individual tailoring of the treatment plan.

CCRG-03. DETECTION OF HETEROGENEOUS CELL CYCLE ALTERATIONS UPON TMZ CHEMOTHERAPY TREATMENT THROUGH ADVANCED MACHINE LEARNING

Abstract Glioblastoma (GB), the most aggressive central nervous system tumor, is hallmarked by its frequent relapse under alkylating chemotherapy. GB cells frequently exhibit changes in cell cycle phases during TMZ treatment, with a reduction in the G0-G1 phase and an increase in the S and G2 phases. This indicate both tumor cell re-entry into the cell cycle and a TMZ-induced arrest, contributing to resistance and progression. In this study, we leverage dynamic protein abundance of Ki-67, a proliferation marker peaking during S, G2, and M phases, to analyse cellular responses to TMZ in various cell lines and tissue samples. We designed an image-based machine learning approach for pattern recognition to reconstruct and analyse the cell cycle at the single-cell level. Six primary cell lines were characterized through whole-genome DNA, methylation and RNA sequencing. Functional read-outs were performed with large-scale, time- and concentration-dependent TMZ treatments in cell culture and GB-tissue slice models. Our model successfully reconstructed detailed cell cycle stages, showing that untreated cells were predominantly in the G0-G1 phase. TMZ treatment significantly shifted cells toward the S/G2 phase (p &amp;lt; 0.02) in 3 of 6 cell lines and the pseudo-time reconstruction highlighted dose-dependent cell cycle changes. Cell lines with enhanced stem-like features, defined based on epigenetic and transcriptional data signature, showed no cell cycle changes at high TMZ doses (&amp;gt;150µM), regardless the MGMT promoter methylation status. This heterogeneity in cell cycle response emphasizes the complexity of GB and the need for personalized treatments. Our study provides insights into GB MGMT cell cycle alterations and resistance mechanisms that are independent of MGMT methylation status, a known TMZ response biomarker. Therefore, the observed TMZ-induced cell cycle changes may serve as novel biomarkers for assessing treatment response, paving the way for personalized therapeutic approaches.

BIOM-70. CSF TUMOR CELL (CSF-TC) DETECTION, QUANTIFICATION AND BIOMARKER ASSESSMENT HELPS IN CLINICAL MANAGEMENT OF BREAST CANCER AND NON-SMALL CELL LUNG CANCER PATIENTS HAVING LEPTOMENINGEAL DISEASE (FORESEE STUDY, NCT05414123)

Abstract Leptomeningeal metastases (LM) or the presence of cancer cells in the cerebrospinal fluid (CSF)/pia remains a challenging disease to diagnosis and treat. Current standard of care methods to diagnose or assess treatment response of LM (Clinical Evaluation, MRI and Cytology) have limited sensitivity and specificity and are poorly quantifiable. This creates challenges for physicians to manage LM or determine the best course of treatment. The FORESEE Study was a multi-center, prospective clinical trial evaluating a novel diagnostic platform, CNSide, that aimed to overcome these challenges. The FORESEE study enrolled patients with breast or non-Small Cell Lung Cancer (NSCLC) with suspicion of or confirmed LM. CNSide can detect and quantify tumor cells in the CSF from patients with breast cancer or NSCLC having a suspicious or confirmed LM. This platform also is able to identify actionable mutations in the CSF via Fluorescent In Situ Hybridization (FISH) and next-generation sequencing. The primary end point of the FORESEE study was clinical utility and the impact of CNSide on physician treatment decisions. Secondary endpoints included evaluating the clinical performance of CNSide vs. cytology in tumor cell detection (sensitivity, specificity, PPV and NPV). The study enrolled 40 patients (22 breast cancer and 18 NSCLC). Each patient underwent standard of care diagnostic evaluations at baseline and at three follow up timepoints through their treatment. CNSide aided clinical decision making in 93% (50/54) of the clinical decisions. At baseline 39 patients were assessed and confirmed a positive LM diagnosis in 15% (6/39), a negative LM diagnosis in 8% (3/39), progression in 15% (6/39), resolution in 15% (6/39) and no progression, or resolution in 36% (14/39) of the patients. CNSide informed the specific drug selected for treatment in 26% (10/39) patients at baseline and demonstrated clinical high utility. The FORESEE data is undergoing ongoing analysis; updated analysis will be presented at the meeting.

Assessment of response to PRRT including anatomical and molecular imaging as well as novel biomarkers.

Peptide receptor radionuclide therapy (PRRT) is an effective treatment for both oncological and hormone control and is a widely accepted standard of care treatment for patients with neuroendocrine neoplasms (NEN). Its use is anticipated to increase significantly, and this demands accurate tools and paradigms to assess treatment response post PRRT. This article outlines the current role and future developments of anatomical, molecular imaging and biomarkers for response assessment to PRRT, highlighting the challenges and provides perspectives for the need to focus on a multimodality, multidisciplinary and individualised approach for patients with this complex heterogeneous disease.

Magnetic resonance imaging-guided single-fraction preoperative radiotherapy for early-stage breast cancer (the RICE trial): feasibility study

BackgroundOver the past decade, the adoption of screening programs, digital mammography, and magnetic resonance imaging (MRI) has increased early-stage breast cancer diagnosis rates. Mortality rates have decreased due to early detection and improved treatments, including personalized therapies. Accelerated partial-breast irradiation (APBI) is emerging as a convenient and effective treatment for some patients, with studies exploring its preoperative use. Preoperative APBI, especially with MRI guidance, offers improved tumor targeting and potentially reduced side effects. Magnetic Resonance Imaging-Guided Single-Fraction Pre-Operative Radiotherapy for Early-Stage Breast Cancer (RICE trial) aims to assess the feasibility and efficacy of MRI-guided single-dose radiotherapy (RT) for early-stage breast cancer.MethodsThe RICE study is a prospective, single-arm study evaluating single-fraction preoperative, APBI treatment for patients with early-stage breast cancer using a magnetic resonance imaging linear accelerator (MRI linac). Eligible patients enrolled in this study will have a core biopsy to confirm estrogen receptor-positive and HER2-negative sub-type. RT planning will use a planning computed tomography (CT) co-registered with a MRI with the patient in either the supine or prone position. For the diagnostic workup, [18F] fluorodeoxyglucose positron emission tomography/CT ([18F] FDG PET/CT) and [18F] fluoroestradiol positron emission tomography/CT ([18F] FES PET/CT) will be performed prior to treatment. Thirty patients will receive a single ablative RT dose of 21 Gray to the tumor. Pre-treatment and post-treatment MRI scans will be acquired at baseline and 5 weeks post-RT respectively. Breast-conserving surgery will be scheduled for 6 weeks after APBI treatment using the MRI linac.The primary study endpoint is the successful administration of a single fraction of preoperative breast RT under the guidance of an MRI linac. Secondary endpoints include evaluating the utility of MRI, [18F] FDG PET/CT, and [18F] FES PET/CT as a non-invasive method for assessing treatment response in patients undergoing single-fraction preoperative APBI.ConclusionThe RICE trial represents a significant step in breast cancer treatment, offering insights that could lead to treatment protocols with minimized RT appointments and enhanced patient outcomes.Trial registrationThis trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR). Registered 31st of May 2021. Registration number: ACTRN12621000659808.

Repeatability of quantitative MR fingerprinting for T1 and T2 measurements of metastatic bone in prostate cancer patients.

MR fingerprinting (MRF) has the potential to quantify treatment response. This study evaluated the repeatability of MRF-derived T1 and T2 relaxation times in bone metastasis, bone, and muscle in patients with metastatic prostate cancer. This prospective single-centre study included same-day repeated MRF acquisitions from 20 patients (August 2019-October 2020). Phantom and human data were acquired on a 1.5-T MR scanner using a research MRF sequence outputting T1 and T2 maps. Regions of interest (ROIs) across three tissue types (bone metastasis, bone, muscle) were drawn on two separate acquisitions. Repeatability of T1 and T2 was assessed using Bland-Altman plots, together with repeatability (r) and intraclass correlation (ICC) coefficients. Mean T1 and T2 were reported per tissue type. Twenty patients with metastatic prostate cancer (mean age, 70 years ± 8 (standard deviation)) were evaluated and bone metastasis (n = 44), normal-appearing bone (n = 14), and muscle (n = 20) ROIs were delineated. Relative repeatability of T1 measurements was 6.9% (bone metastasis), 32.6% (bone), 5.8% (muscle) and 21.8%, 32.2%, 16.1% for T2 measurements. The ICC of T1 was 0.97 (bone metastasis), 0.94 (bone), 0.96 (muscle); ICC of T2 was 0.94 (bone metastasis), 0.94 (bone), 0.91 (muscle). T1 values in bone metastasis were higher than in bone (p < 0.001). T2 values showed no difference between bone metastasis and bone (p = 0.5), but could separate active versus treated metastasis (p < 0.001). MRF allows repeatable T1 and T2 measurements in bone metastasis, bone, and muscle in patients with primary prostate cancer. Such measurements may help quantify the treatment response of bone metastasis. Question MR fingerprinting has the potential to characterise bone metastasis and its response to treatment. Findings Repeatability of MRF-based T1 measurements in bone metastasis and muscle was better than for T2. Clinical relevance MR fingerprinting allows repeatable T1 and T2 quantitative measurements in bone metastasis, bone, and muscle in patients with primary prostate cancer, which makes it potentially applicable for disease characterisation and assessment of treatment response.