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163 Background: Being physically inactive is an independent predictor of poor outcomes in patients with stage III colon cancer. Whether physical activity can mitigate the oncologic risk of postoperative MRD is unknown. Methods: We concluded a post hoc analysis of a phase III trial evaluating celecoxib vs. placebo and 3 vs. 6 months of adjuvant chemotherapy in patients with resected stage III colon cancer. Self-reported physical activity was assessed in standardized measures of metabolic equivalent hours per week (MET-h/wk) at 2 timepoints: 1) midway through and 2) 6 months after completing adjuvant chemotherapy, modeled as a time-weighted average. MRD was determined via a clinically validated, tumor-informed circulating tumor DNA (ctDNA) assay (Signatera, Natera, Inc.). Disease-free survival (DFS) and overall survival (OS) were estimated using flexible parametric survival models. Results: Among 763 patients (median follow-up 6.0 years), 24% were highly active (≥18 MET-h/wk) and 32% were inactive (<3 MET-h/wk); 18% were ctDNA positive. Adjusting for covariates, DFS improved in patients who were ctDNA negative and moderately active (Ref: inactive; 3-17.9 MET-h/wk; HR=0.62, 95% CI [0.40-0.97]) or highly active (HR = 0.53 [0.30-0.94]). No benefit was seen among patients who were ctDNA positive (Ref: inactive; moderately active: HR = 1.20 [0.75-1.92]; highly active: HR=0.83 [0.45-1.54]). The interaction was not significant (Pint=0.269). Physical activity did not impact OS regardless of ctDNA status. The interaction of physical activity and adjuvant celecoxib use is shown in Table. Conclusions: Among patients who were ctDNA negative, physical activity was associated with improved DFS, and may demonstrate increased survival benefit alongside adjuvant celecoxib. The additive effects of both interventions were inconclusive among those who were ctDNA positive. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org; Natera, Pfizer; NCT01150045. Disease-free survival by physical activity level and celecoxib use, stratified by ctDNA status. 3-yr event # at risk Adjusted HR (95% CI) P-value Pint ctDNA Negative 0.258 Inactive + placebo 23 182 Ref Active + placebo 17 132 0.74 (0.43-1.28) 0.283 Inactive + celecoxib 23 167 0.92 (0.57-1.48) 0.720 Active + celecoxib 10 146 0.40 (0.22-0.79) 0.007 ctDNA Positive 0.221 Inactive + placebo 26 33 Ref Active + placebo 15 20 0.96 (0.50-1.84) 0.903 Inactive + celecoxib 34 54 0.62 (0.37-1.05) 0.076 Active + celecoxib 14 29 0.34 (0.18-0.64) 0.001 ctDNA, circulating tumor DNA; HR, hazard ratio; CI, confidence interval. Active = ≥9 MET-h/week, inactive = <9 MET-h/week. Celecoxib use defined by assignment in CALGB/SWOG 80702. Models adjusted by T and N stage, age, sex, race, assigned cycles of fluorouracil, leucovorin, and oxaliplatin, KRAS and BRAF status, BMI, and Western diet.

Abstract Background Atypical clinical presentations of Alzheimer's disease (AD) are associated with heterogeneous patterns of cortical tau‐PET uptake. The medial‐temporal (MTL) meta‐ROI is typically used to determine tau‐PET abnormality in AD, but this approach may not detect focal uptake in atypical patients. Our goal was to develop regional tau‐PET cut‐points and determine whether the number of positive regions better captures positive tau‐PET signal in atypical AD. Method 127 amyloid‐positive atypical AD (visual=68, language=39, motor=15, others=5) and 62 amyloid‐negative cognitively unimpaired (CU) individuals were recruited by the Neurodegenerative Research Group, Mayo Clinic, and underwent, amyloid‐PET and 18 F‐AV‐1451(tau)‐PET. Images were parcellated using the modified Harvard‐Oxford atlas and we focused on 67 AD‐specific regions. Rather than using the average SUVR across voxels within a region to quantify uptake, we used the 95 th percentile of SUVR values across voxels within a region to capture focal cases. We then used receiver operating characteristic (ROC) methods and a Youden threshold to define regional abnormality. The number of abnormal regions was calculated for each participant and used to discriminate between CU and atypical AD at the individual level. Result Across 64 regions, our approach showed excellent (AUROC>0.90) differentiation between atypical AD and CU. The temporal‐fusiform, parahippocampal gyrus and inferior temporal gyrus showed the best differentiation (Figure 1). All 67 regions showed excellent specificity (>85%), with 63 regions showing excellent sensitivity (≥80%). The lateral occipital cortex, temporal‐fusiform and parahippocampal gyrus showed the best specificity and sensitivity (Figure 2). The distribution of the number of tau‐elevated regions is shown in Figure 3. 74% of CU had no positive regions, while 43% of the atypical AD patients had all 67 regions affected. An optimal threshold of 7 tau‐elevated regions classified all CU below, and 123 (97%) atypical AD above threshold. Using a standard approach based on the average SUVR in the MTL meta‐ROI, only 116 (91%) atypical AD patients were tau‐PET positive. Conclusion Tau uptake in temporal regions showed the greatest group‐level differentiation. However, examining regional tau‐positivity may offer better sensitivity in atypical AD patients compared to the temporal meta‐ROI, likely due to the presence of focal non‐temporal patterns of uptake.

Abstract Background An intense search is underway for tau PET tracers with enhanced capability to visualize tau aggregates. Research indicates that [18F] AV1451 and [18F]MK 6240 exhibit comparable binding properties in terms of spatial distribution and severity of tau aggregates, as observed both in‐vivo and in‐vitro. This study focused on head‐to‐head pathological comparison of both the tracers binding specificity to tangle maturity levels (pretangles, mature tangles and ghost tangles) of tau aggregates as seen on autoradiography as compared to CP‐13 (early tangle maturity marker) and PHF‐1(middling tangle maturity marker) immunohistochemical (IHC) stains in Alzheimer's disease (AD) and non‐AD tauopathies. Method Study participants included included those with AD and non‐AD tauopathies. Analyses were performed on serial 5um formalin fixed paraffin embedded postmortem human brain sections acquired from Mayo clinic brain bank. Visual assessment of colocalization with IHC as well as quantitative analyses were used. IHC sections were incubated with antibodies CP‐13 (recognizing early tangle maturity) and PHF‐1 (recognizing middling tangle maturity). Result A total of 38 participants were examined. The participants included a spectrum from normal to AD, including mild cognitive impairment (MCI) and atypical AD. Participants with N279K (4R), P301L (4R), and R406W MAPT mutations (3R+4R) were included as well. Both the tracers showed strong binding to AD tau aggregates and no or minimal binding to non‐AD tauopathies. Generally, early tangle maturity tau accumulation participants had more tau demonstrated with CP‐13 than PHF‐1 and both the tracers [18F]MK 6240 and [18F]AV 1451 binding are well correlated with the PHF‐1 staining suggesting the preference for middling tangle level and minimal to early tangles. Conclusion The emergence and validation of these new tau PET tracers have opened new opportunities for the development of more accurate diagnostic and management tools for AD. In our study on post‐mortem sections, [ 18 F]MK‐6240 and [ 18 F]Flortaucipir showed similar binding profiles with preference to middling tangle maturity levels.

Abstract Background Isolated REM sleep behavior disorder (iRBD) is a parasomnia that reflects an evolving α‐synucleinopathy disorder, providing an opportunity to study early pathological changes. While diffusion tensor imaging (DTI) studies have shown white matter changes in iRBD, Neurite Orientation Dispersion and Density Imaging (NODDI) may offer better biological specificity in characterizing microstructural alterations through measures of Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and Free Water Fraction (FWF). Method We included 77 participants with polysomnography‐confirmed iRBD from the North American Prodromal Synucleinopathy (NAPS) Consortium and 154 age‐ and sex‐matched cognitively unimpaired controls from the Mayo Clinic Study of Aging. White matter microstructure was evaluated using standardized multi‐shell diffusion on 3T MRI, quantifying DTI metrics (fractional anisotropy, FA; and mean diffusivity, MD) and NODDI parameters across bilateral white matter tracts defined by the JHU “Eve” WM atlas. Group differences were assessed using conditional logistic regression, with correlations to motor performance evaluated using the Purdue Pegboard and Alternating Finger Tapping tests. Result Compared to controls, iRBD participants demonstrated widespread and bidirectional white matter changes across major white matter pathways (see Figure 1 for glass brain visualizations). While predominantly showing decreases, FA exhibited some increases, particularly in the corticospinal tract. MD showed a largely opposite pattern with predominantly increased values across tracts. NODDI metrics revealed complex bidirectional patterns: ODI was broadly increased across multiple tracts with focal decreases, while NDI showed a pattern of predominantly decreased values alongside localized increases. FWF demonstrated a mixed pattern with predominant decreases across most tracts. In addition, both DTI and NODDI metrics showed extensive, moderate correlations with the Purdue Pegboard Test and Alternating Finger Tapping performance ( T = 2.0, p < 0.05, Figure 2). Conclusion Our study highlighted widespread and complex bidirectional white matter microstructural alterations in individuals with iRBD, demonstrating significant correlations with dexterity and motor performance even during the prodromal stage. These results suggest that extensive white matter abnormalities occur early in prodromal α‐synucleinopathies and highlight the value of advanced diffusion imaging techniques in characterizing iRBD and its potential prediction of phenoconversion to overt neurodegenerative disorders.

We present a subset analysis on the adolescent cohort of the S1826 randomized phase three trial, comparing nivolumab, doxorubicin, vinblastine, dacarbazine (N-AVD) to brentuximab vedotin-AVD (BV-AVD) in newly diagnosed advanced-stage (AS, stages III and IV) classic Hodgkin lymphoma (cHL). Among 994 patients enrolled, 24% (n = 240) were age 12-17 years. The 3-year progression-free survival (PFS) was significantly higher in the N-AVD group (93% [95% CI, 87 to 96]) compared with the BV-AVD group (82% [95% CI, 73 to 88]; hazard ratio, 0.37 [95% CI, 0.17 to 0.80]). One N-AVD and two BV-AVD patients received protocol-specified residual site radiotherapy (RT). Rates of febrile neutropenia and sepsis were low in both groups. Severe immune-related adverse events were infrequent, although thyroid dysfunction was seen in 7% with N-AVD. Sensory neuropathy (grade ≥2) was more frequent with BV-AVD (14% v 7%) by clinician report. Although premature discontinuation of therapy was reported in 12 N-AVD patients and four BV-AVD patients, no PFS events were noted in the N-AVD group. Patient-reported outcomes indicated less toxicity with N-AVD. N-AVD demonstrated high 3-year PFS in adolescents with AS cHL, with minimal RT use. S1826 exemplifies the benefits of harmonized clinical trial protocols, resulting in timely access to novel agents for adolescents.

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer's disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract Background Plasma neurofilament light chains (NfL) and glial fibrillary acidic protein (GFAP) are blood‐based biomarkers of axonal injury and astrocytic activation, respectively, that are elevated in those with Alzheimer's disease (AD) and mild cognitive impairment (MCI) relative to cognitively unimpaired (CU) individuals. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method capable of evaluating tissue microstructure at the axonal and dendritic level. We evaluated associations between temporal cortex orientation dispersion index (ODI), neurite density index (NDI) and isotropic volume fraction (ISOVF) and plasma NfL and GFAP concentrations. Method We included Mayo Clinic Study of Aging (MCSA) participants (ages 60‐95 years) with diagnoses or CU ( n = 356) or MCI ( n = 60), and Alzheimer's Dementia Research Center (ADRC) participants with dementia ( n = 51). NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. NfL and GFAP were measured using the Simoa® Neurology 4‐Plex E Advantage kit. We fit separate linear regression models within each MCALT_ADIR122 cortical ROI with regional NODDI as the primary predictor and log‐transformed plasma concentration as the outcome. Models were adjusted for age, sex, BMI, cortical thickness (or hippocampal & amygdalar volume) and total intracranial volume. Result The Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ISOVF measures to plasma NfL concentrations across participants in individual ROIs (similar findings were noted with GFAP). A significant inverse relationship between NfL concentrations and NDI was observed in hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus as well as all temporal neocortical regions except the superior temporal gyrus ( p <0.001) (Figure 1), whereas higher NfL concentrations were associated with higher ISOVF in all regions ( p <0.001) (Figure 2). Fewer significant associations were also seen with ODI. After adjusting for age, cortical thickness/volume and other confounds, significant associations with NDI remain, particularly in hippocampal and amygdalar regions. Conclusion NODDI‐derived measures (NDI and ISOVF) within the temporal lobe cortical regions demonstrate significant associations with plasma biomarkers of axonal and astrocytic dysfunction that are elevated during cognitive decline. This association provides preliminary validation of the utility of NODDI in assessing cortical microstructural changes associated with cognitive decline.

Background Costosternal cartilages and the costal margin, collectively termed costal cartilage, are hyaline cartilage connecting ribs to the sternum and to adjacent ribs, respectively. Presence of intact costal cartilage is essential for elasticity of the chest wall. Anecdotally, costal cartilage injuries are underdiagnosed on trauma CT scan in patients with rib fractures. Our aim was to determine a baseline frequency of acute costal cartilage injury among patients presenting with rib fractures. Methods We performed a retrospective cohort study of injured adult patients admitted to Level I/II trauma centers with rib fractures from January 2020 to July 2024. CT images obtained at admission were manually reviewed by chest wall surgeons for presence of costal cartilage injury. Concordance with the original radiology report was obtained. Multivariable regression was used to analyze factors associated with costal cartilage injury and missed cartilage fractures. Results 1441 patients were identified; 197 (14%) had a costal cartilage fracture. A plurality of injuries included falls (n=667, 46%). Median ISS (Injury Severity Score) was 13 (IQR: 9 to 21), median Abbreviated Injury Scale thorax score was 3 (IQR: 3 to 3), and median number of fractured ribs was 3 (IQR: 3 to 7). 294 (21%) patients had radiographic flail segments, and 136 (9%) had sternal fractures. 172 (87%) patients had a costal cartilage fracture missed on initial trauma chest CT. On multivariable analysis, ISS (adjusted OR (aOR) 1.02 (95% CI 1.01 to 1.04), radiographic flail segment (aOR 1.6 (95% CI 1.10 to 2.31)) and presence of sternal fracture (aOR 1.85 (95% CI 1.19 to 2.89)) were associated with costal cartilage fractures. Only the total number of rib fractures was associated with a missed costal cartilage fracture on univariate analysis (OR 1.17 (95% CI 1.01 to 1.36)). Conclusions Costal cartilage injuries are common and frequently are not identified during interpretation of the initial trauma CT. A higher index of suspicion is warranted for costal cartilage fractures among patients with greater injury burden, radiographic flail segment, and sternal fractures. Level of evidence Level III.

Abstract Background Neuroinflammation plays a crucial role in neuronal damage, synaptic dysfunction, and impaired neurogenesis, significantly contributing to Alzheimer's Disease (AD) progression. To address this, we assessed ER176's effectiveness in detecting neuroinflammation in cognitively unimpaired (CU) A–, CU A+, mild cognitive impairment (MCI), and AD participants, with a particular focus on their amyloid and tau status. This research aims to help identify suitable candidates for specialized treatment when adversely impacted by neuroinflammation. Method Participants from the Mayo Clinic Study of Aging were recruited for this study. The study included four participant groups: CU A– ( n = 25), CU A+ ( n = 25), MCI A+ ( n = 25), and AD ( n = 15). We explored the variations in neuroinflammation PET results among different groups. Result When compared to CU A–, both CU A+ and MCI A+ groups (Figure 1) showed greater regional neuroinflammation. AD exhibited more widely affected regions with neuroinflammation (temporal, occipital, and parietal lobes) than CU A‐ over the PVC spectrum (Figure 1). Minimally more neuroinflammation was seen (temporal lobes) in MCI A+ than CU A+ (Figure 1). AD had more widespread regional neuroinflammation vs CU A+ (Figure 1) than in MCI A+ vs CU+. The least difference in neuroinflammation is seen in MCI A+ vs AD (Figure 1). For A+ vs A‐, A+ showed more widespread neuroinflammation (Figure 2). T+ (tau>=1.29) vs T‐ (tau<1.29) showed more neuro inflammation with T+ (Figure 2). Comparisons varied modestly in significance level with PVC method (Figures 1 and 2). Conclusion The findings demonstrate that neuroinflammatory changes are associated with AD pathology. Even at early stages, neuroinflammation is associated with CU+. As the condition progresses, neuroinflammation extends to more brain regions and is associated with increased A+ and T+ pathology in MCI A+ and AD. These results suggest an early and persistent role of neuroinflammation in the progression AD pathology, indicating that therapy options could include early anti‐inflammatory intervention, even prior to clinical symptoms, along with treatment during clinical manifestations. PVC methods used may provide somewhat variable results.