Tumor Apparent Diffusion Coefficient Research Articles

Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma.

To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.

Association between programmed cell death ligand-1 expression in patients with cervical cancer and apparent diffusion coefficient values: a promising tool for patient´s immunotherapy selection.

To investigate the associations between apparent diffusion coefficient (ADC) values extracted from three different region of interest (ROI) position approaches and programmed cell death ligand-1 (PD-L1) expression, and evaluate the performance of the nomogram established based on ADC values and clinicopathological parameters in predicting PD-L1 expression in cervical cancer (CC) patients. Through retrospective recruitment, a training cohort of 683 CC patients was created, and a validation cohort of 332 CC patients was prospectively recruited. ROIs were delineated using three different methods to measure the mean ADC (ADCmean), single-section ADC (ADCss), and the minimum ADC of tumors (ADCmin). Logistic regression was employed to identify independent factors related to PD-L1 expression. A nomogram was drawn based on ADC values combined with clinicopathological features, its discrimination and calibration performances were estimated using the area under the curve (AUC) of receiver operating characteristic and calibration curve. The clinical benefits were evaluated by decision curve analysis. The ADCmin independently correlated with PD-L1 expression. The nomogram constructed with ADCmin and other independent clinicopathological-related factors: FIGO staging, pathological grade, parametrial invasion, and lymph node status demonstrated excellent diagnostic performance (AUC = 0.912 and 0.903, respectively), good calibration capacities, and greater net benefits compared to the clinicopathological model in both the training and validation cohorts. ADCmin independently correlated PD-L1 expression, and the nomogram established with ADCmin and clinicopathological independent prognostic factors had a strong predictive performance for PD-L1 expression, thereby serving as a promising tool for selecting cases eligible for immunotherapy. The minimum ADC can serve as a reliable imaging biomarker related to PD-L1 expression; the established nomogram combines the minimum ADC and clinicopathological factors that can assist clinical immunotherapy decisions.

The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis.

Diffusion Magnetic Resonance Imaging (MRI) is a useful method to evaluate tumor biology and tumor microstructure. The apparent diffusion coefficient (ADC) value correlates negatively with the cellular density of the tumor. This study aimed to investigate the effectiveness of the ADC histogram analysis in showing the relationship between breast cancer prognostic factors and ADC parameters. This study is a retrospective observational descriptive study. ADC histogram parameters were evaluated in all tumor volumes of 67 breast cancer patients. Minimum, 5, 10, 25, 50, 75, 90, 95 percentiles, maximum, mean, median ADC values, kurtosis, and skewness were calculated. Breast MRI examinations were performed on a 3T MR scanner. We evaluated the fibroglandular tissue density of bilateral breasts, background enhancement, localization of masses, multifocality-multicentricity, shape, rim, internal contrast enhancement, and kinetic curve on breast MRI. BIRADS scoring was performed according to breast MRI. Pathologically, histologic type, histologic grade, HER 2, Ki 67, ER-, and PR status were evaluated. A significant correlation was found between tumor volume and ADC scores. There is a significant correlation between min ADC values (p< 0.031), max ADC (p< 0.001), and skewness (p< 0.019). A significant correlation was found between tumor kurtosis and lymph nodes (p< 0.029). There was a significant difference in ADC <sub<mean</sub<, ADC<sub<10%</sub<, ADC<sub<25%</sub<, ADC<sub<50%</sub<, ADC<sub<75%</sub<, ADC<sub<90%</sub<, ADC <sub<95%</sub< and ADC<sub<max</sub> values depending on ER-and PRstatus. (for ER p = 0.004, p = 0.018, p = 0.010, p = 0.008, p = 0.004, p = 0.004, p = 0.02, p = 0.02 and p = 0.038, for PR p &#60; 0.001, p = 0.028, p = 0.011, p = 0.001, p < 0.001, p =<0.001, p < 0.001, and p < 0.001, respectively; p < 0.05). These values were lower in ER-and PR-positive status than in ER-and PR-negative receptor status. According to HER2 status, there was a statistically significant difference in ADC<sub<5%</sub< and measurements of the lesions (p = 0.041; p < 0.05). Our study found no significant correlation between other prognostic factors, such as histological grade, Ki-67 indices, and ADC values. Our study found a significant difference between tumor volume, ER- and, PR status, HER2, and lymph node involvement, and some ADC values among prognostic factors for breast cancer. Furthermore, ADC histogram analysis can provide additional value in predicting some prognostic factors.

Normal Brain and Brain Tumor ADC: Changes Resulting From Variation of Diffusion Time and/or Echo Time in Pulsed-Gradient Spin Echo Diffusion Imaging.

Increasing gradient performance on modern magnetic resonance imaging scanners has profoundly reduced the attainable diffusion and echo times for clinically available pulsed-gradient spin echo (PGSE) sequences. This study investigated how this may impact the measured apparent diffusion coefficient (ADC), which is considered an important diagnostic marker for differentiation between normal and abnormal brain tissue and for therapeutic follow-up. Diffusion time and echo time dependence of the ADC were evaluated on a high-performance 3 T magnetic resonance imaging scanner. Diffusion PGSE brain scans were performed in 10 healthy volunteers and in 10 brain tumor patients using diffusion times of 16, 40, and 70 ms, echo times of 60, 75, and 104 ms at 3 b-values (0, 100, and 1000 s/mm 2 ), and a maximum gradient amplitude of 68 mT/m. A low gradient performance system was also emulated by reducing the diffusion encoding gradient amplitude to 19 mT/m. In healthy subjects, the ADC was measured in 6 deep gray matter regions and in 6 white matter regions. In patients, the ADC was measured in the solid part of the tumor. With increasing diffusion time, a small but significant ADC increase of up to 2.5% was observed for 6 aggregate deep gray matter structures. With increasing echo time or reduced gradient performance, a small but significant ADC decrease of up to 2.6% was observed for 6 aggregate white matter structures. In tumors, diffusion time-related ADC changes were inconsistent without clear trend. For tumors with diffusivity above 1.0 μm 2 /ms, with prolonged echo time, there was a pronounced ADC increase of up to 12%. Meanwhile, for tumors with diffusivity at or below 1.0 μm 2 /ms, no change or a reduction was observed. Similar results were observed for gradient performance reduction, with an increase of up to 21%. The coefficient of variation determined in repeat experiments was 2.4%. For PGSE and the explored parameter range, normal tissue ADC changes seem negligible. Meanwhile, observed tumor ADC changes can be relevant if ADC is used as a quantitative biomarker and not merely assessed by visual inspection. This highlights the importance of reporting all pertinent timing parameters in ADC studies and of considering these effects when building scan protocols for use in multicenter investigations.

Association of ADC of hyperintense lesions on FLAIR images with TERT promoter mutation status in glioblastoma IDH wild type.

Although mutations in telomerase reverse transcriptase (TERT) promoter (TERTp) are the most common alterations in glioblastoma (GBM), predicting TERTp mutation status by preoperative imaging is difficult. We determined whether tumour-surrounding hyperintense lesions on fluid-attenuated inversion recovery (FLAIR) were superior to those of contrast-enhanced lesions (CELs) in assessing TERTp mutation status using magnetic resonance imaging (MRI). This retrospective study included 114 consecutive patients with primary isocitrate dehydrogenase (IDH)-wild-type GBM. The apparent diffusion coefficient (ADC) and volume of CELs and FLAIR hyperintense lesions (FHLs) were determined, and the correlation between MRI features and TERTp mutation status was analyzed. In a subset of cases, FHLs were histopathologically analyzed to determine the correlation between tumor cell density and ADC. TERTp mutations were present in 77 (67.5%) patients. The minimum ADC of FHLs was significantly lower in the TERTp-mutant group than in the TERTp-wild-type group (mean, 958.9 × 10-3 and 1092.1 × 10-3 mm2/s, respectively, P < 0.01). However, other MRI features, such as CEL and FHL volumes, minimum ADC of CELs, and FHL/CEL ratio, were not significantly different between the two groups. Histopathologic analysis indicated high tumor cell density in FHLs with low ADC. The ADC of FHLs was significantly lower in IDH-wild-type GBM with TERTp mutations, suggesting that determining the ADC of FHLs on preoperative MRI might be helpful in predicting TERTp mutation status and surgical planning.

High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.

Majority of men with low-risk prostate cancer can be managed with active surveillance (AS). This study evaluates a high-resolution diffusion-weighted imaging (HR-DWI) technique to predict adverse biopsy histology (AH), defined as Gleason score ≥7 on any biopsy or ≥3 increase in number of positive biopsy cores on systematic biopsies. We test the hypothesis that high-grade disease and progressing disease undergo subtle changes during even short intervals that can be detected by HR-DWI. In a prospective clinical trial, serial multiparametric MRIs, incorporating HR-DWI and standard DWI (S-DWI) were performed approximately 12 months apart prior to prostate biopsy (n = 59). HR-DWI, which uses reduced field-of-view and motion compensation techniques, was compared with S-DWI. HR-DWI had a 3-fold improvement in spacial resolution compared with S-DWI as confirmed using imaging phantoms. For detecting AH, multiparametric MRI using HR-DWI had a sensitivity of 75% and specificity of 83.9%, and MRI using S-DWI had a sensitivity of 71.4% and specificity of 54.8%. The AUC for HR-DWI was significantly higher (0.794 vs. 0.631, P = 0.014). Secondary analyses of univariable predictors of AH showed tumor size increase [OR 16.8; 95% confidence interval (CI): 4.06-69.48; P < 0.001] and apparent diffusion coefficient (ADC) decrease (OR 5.06; 95% CI: 1.39-18.38; P = 0.014) on HR-DWI were significant predictors of AH. HR-DWI outperforms S-DWI in predicting AH. Patient with AH have tumors that change in size and ADC that could be detected using HR-DWI. Future studies with longer follow-up should assess HR-DWI for predicting disease progression during AS. We report on a prospective clinical trial using a MRI that has three times the resolution of standard MRI. During AS for prostate cancer, two high-resolution MRIs performed approximately a year apart can detect tumor changes that predict the presence of aggressive cancers that should be considered for curative therapy such as prostatectomy or radiation.

Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients.

Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans. The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively. Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.

A preoperative magnetic resonance imaging can aid in staging and treatment choice for upper tract urothelial carcinoma.

The aim was to investigate the predictive abilities of a preoperative diffusion-weighted MRI (dwMRI) among patients with surgically treated upper tract urothelial carcinoma (UTUC). Written consent was obtained from all participants in this prospective and ethically approved study. Thirty-five UTUC patients treated with radical surgery were examined with a preoperative dwMRI and prospectively included during 2017-2022. Two radiologists examined the CT scans and dwMRIs for radiological stage, and the apparent diffusion coefficient (ADC) in the tumours at the dwMRI was registered. The radiologists were blinded for patient history, final histopathology and the readings of the other radiologist. The radiological variables were analysed regarding their abilities to predict muscle-invasive disease (MID, T2-T4) and tumour grade at final pathology after radical surgery. The predictive abilities were assessed using chi-square tests, Student's t-test and calculating the area under the curve in a receiver operating characteristic (ROC) curve. Correlation between the two radiologists was quantified calculating the intra-class correlation coefficient. P-values <0.05 were considered statistically significant. Mean age was 72 years, 20 had high-grade tumour, and 13 patients had MID. The ADC values at the dwMRI were significantly lower among patients with MID compared to patients with non-muscle-invasive disease (930 vs 1189, p = <0.001). The area under the ROC curve (AUC) in an ROC curve to predict MID was 0.88 (CI 0.77-0.99, p = <0.001). The ADC values were significantly lower among patients with high-grade tumours compared to low-grade tumours (1005 vs 1210, p = 0.002). The correlation of the ADC measurements between the two radiologists was of 0.93 (CI 0.85-0.96, p < 0.001). Tumour ADC at the MRI emerges as a potential biomarker for aggressive disease. The results are promising but should be validated in a larger, multicentre study.

Evaluation of the Prognostic Value of Pretherapeutic Magnetic Resonance Imaging in Predicting Soft Tissue Sarcoma Radiation Response: A Retrospective Study from a Large Institutional Sarcoma Imaging Database.

Background: RT-induced hyalinization/fibrosis was recently evidenced as a significant independent predictor for complete response to neoadjuvant radiotherapy (RT) and survival in patients with soft tissue sarcoma (STS). Purpose: Non-invasive predictive markers of histologic response after neoadjuvant RT of STS are expected. Materials and Methods: From May 2010 to April 2017, patients with a diagnosis of STS who underwent neoadjuvant RT for limb STS were retrieved from a single center prospective clinical imaging database. Tumor Apparent Diffusion Coefficients (ADC) and areas under the time-intensity perfusion curve (AUC) were compared with the histologic necrosis ratio, fibrosis, and cellularity in post-surgical specimens. Results: We retrieved 29 patients. The median ADC value was 134.3 × 10-3 mm2/s. ADC values positively correlated with the post-treatment tumor necrosis ratio (p = 0.013). Median ADC values were lower in patients with less than 50% necrosis and higher in those with more than 50% (120.3 × 10-3 mm2/s and 202.0 × 10-3 mm2/s, respectively (p = 0.020). ADC values higher than 161 × 10-3 mm2/s presented a 95% sensitivity and a 55% specificity for the identification of tumors with more than 50% tumor necrosis ratio. Tumor-to-muscle AUC ratios were associated with histologic fibrosis (p = 0.036). Conclusions: ADC and perfusion AUC correlated, respectively, with radiation-induced tumor necrosis and fibrosis.

Can the ADC Value Be Used as an Imaging “Biopsy” in Endometrial Cancer?

Background: The tumor histological grade is closely related to the prognosis of patients with endometrial cancer (EC). Multiparametric MRI, including diffusion-weighted imaging (DWI), provides information about the cellular density that may be useful to differentiate between benign and malignant uterine lesions. However, correlations between apparent diffusion coefficient (ADC) values and histopathological grading in endometrial cancer remain controversial. Material and methods: We retrospectively evaluated 92 patients with endometrial cancers, including both endometrioid adenocarcinomas (64) and non-endometrioid adenocarcinomas (28). All patients underwent DWI procedures, and mean ADC values were calculated in a region of interest. These values were then correlated with the tumor grading offered by the histopathological examination, which was considered the gold standard. In this way, the patients were divided into three groups (G1, G2, and G3). The ADC values were then compared to the results offered by the biopsy to see if the DWI sequence and ADC map could replace this procedure. We also compared the mean ADC values to the myometrial invasion (&lt;/&gt;50%) and lymphovascular space invasion. Results: We have divided the ADC values into three categories corresponding to three grades: &gt;0.850 × 10−3 mm2/s (ADC1), 0.730–0.849 × 10−3 mm2/s (ADC2) and &lt;0.730 × 10−3 mm2/s (ADC3). The diagnostic accuracy of the ADC value was 85.71% for ADC1, 75.76% for ADC2, and 91.66% for ADC3. In 77 cases out of 92, the category in which they were placed using the ADC value corresponded to the result offered by the histopathological exam with an accuracy of 83.69%. For only 56.52% of patients, the biopsy result included the grading system. For each grading category, the mean ADC value showed better results than the biopsy; for G1 patients, the mean ADC value had an accuracy of 85.71% compared to 66.66% in the biopsy, G2 had 75.76% compared to 68.42%, and G3 had 91.66 compared to 75%. For both deep myometrial invasion and lymphovascular space invasion, there is a close, inversely proportional correlation with the mean ADC value. Conclusions: Mean endometrial tumor ADC on MR-DWI is inversely related to the histological grade, deep myometrial invasion and lymphovascular space invasion. Using this method, the patients could be better divided into risk categories for personalized treatment.

Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas.

To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values ​​as prognostic factors of surgical outcomes. Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values ​​to pons (ADCR) were compared with tumor consistency and grade of surgical resection. A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10-3 mm2/sec (0.306-1.096 × 10-3 mm2/sec), and in the intermediate/hard consistency group was 0.509 × 10-3 mm2/sec (0.308-0.818 × 10-3 mm2/sec). There was no significant difference between the median values ​​of ADC, ADCR and signal on T1W between the soft and hard tumor groups, or between patients with and without tumor residue. Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.

Abstract A098: Quantitative MRI metrics capture pancreatic cancer and stroma responses to novel KRAS inhibitor

Abstract Introduction Pancreatic ductal adenocarcinoma (PDA) is a deadly cancer with limited treatment options. Oncogene KRAS mutations found in majority of PDA patients with KRAS(G12D) mutation being the most common. A new KRAS(G12D) specific inhibitor, MRTX1133 has been shown to induce rapid tumor regression in PDA models while the effect on stroma is only revealed by postmortem analyses of tumor specimens, making it hard to assess the dynamics of stroma remodeling. Furthermore, in clinical testing of KRAS(G12C) inhibitor, only ~50% of patients responded to the treatment despite the presence of correct genetic mutation in biopsy specimens, therefore, early and accurate assessment of the drug-target engagement is important in clinical setting. Our study was designed to test the hypothesis that multimetric MRI captures early responses to KRAS(G12D) inhibitor beyond the change of tumor size in a PDA model. Especially, changes in apparent diffusion coefficient (ADC) from diffusion weighted (DW) MRI, Ktrans from dynamic contrast enhanced (DCE) MRI, and magnetization transfer ratio (MTR). Methods A genetically engineered model of PDA bearing KRAS(G12D) and Trp53 mutation referred to as KPC was used. Male and female mice were enrolled to receive MRTX1133 at 30mg/kg BID or PBS via i.p injection. Murine PDA cells bearing KRAS(G12C) mutation were inoculated in the flank of C57BL/6 mice to grow subcutaneous tumors. In vivo DW- and DCE-MRI were obtained on a 9.4T Bruker system employing pulse sequences insensitive to respiratory motion. Results In KPC mice, striking increase of tumor ADC were detected as early as 48h after treatment initiation and was confirmed by statistical analyses at 48h and day7 accompanied by decrease of tumor size, in contrast to a trend of increased tumor size and decreased ADC in PBS-treated mice. H&amp;E section revealed gross necrosis and extensive cell death. A clear increase of Ktrans suggesting an increase of capillary permeability and/or perfusion was detected at 48h, persisting to day7; while CD31 did not change significantly, capillary lumen area appeared enlarged at 48h, consistent with reduced interstitial fluid pressure resulted from clearance of stromal hyaluronic acid. A remarkable reduction of MTR at 48h clearly captured the stromal effect of MRTX1133 whereas no change observed in PBS-treated mice. Consistently, Sirius red (SR) staining for collagen revealed a high degree of heterogeneity where regions of depletion versus dense SR staining coexist. Lack of tumor regression and ADC change in KRAS(G12C) tumors confirmed the specificity of MRTX1133 to G12D however, a reduction of MTR was revealed, suggesting stromal impact as off-target effect of MRTX1133. Conclusion To our knowledge, this represents the first MRI study of the new KRAS inhibitor. The multimetric MRI approach is novel and significant because it captured MRTX1133-induced cancer cell death and stroma change over time. With further validation, these translatable imaging metrics can provide biological mechanism underneath tumor size change in the clinical setting. Citation Format: Mamta Gupta, Hoon Choi, Emma E. Furth, Miguel Joaquim, Stephen Pickup, Cynthia Clendenin, Margo Orlen, Thomas Karasic, Hee Kwon Song, Yong Fan, Peter O’Dwyer, Robert H. Vonderheide, Mark Rosen, Ben Z. Stanger, Rong Zhou. Quantitative MRI metrics capture pancreatic cancer and stroma responses to novel KRAS inhibitor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A098.

Predictive Factor of Tumor Aggressiveness in Patients with Extrahepatic Cholangiocarcinoma Based on Diffusion-weighted MRI.

Extrahepatic cholangiocarcinoma (EHCC), an exceedingly malignant neoplasm, often eludes early detection, culminating in a dire prognosis. Accurate cancer staging systems and pathological differentiation are designed to guide adjuvant interventions and predict postoperative prognoses. This study sought to investigate the predictive capacity of DW-MRI in discerning T stages, lymph node metastasis, and pathological differentiation grades in patients with EHCC. Eighty-five patients were pathologically diagnosed with EHCC and underwent abdominal MRI within two weeks before surgery at our hospital from Aug 2011 to Aug 2021. Tumor axial maximum area (AMA) and apparent diffusion coefficient (ADC) values for diverse T stages, N stages, and differentiation grades were retrospectively analyzed. The Mann-Whitney U test displayed significantly higher lesion AMA values (P =0.006) and lower tumor ADC values (P = 0.001) in the nodepositive group (median ADC and AMA value: 1.220×10-3 mm2/s, 82.231 mm2) than in the node-negative group (median ADC and AMA value: 1.316×10-3 mm2/s, 51.174 mm2). A tumor ADC value<1.249×10-3 mm2/s from the receiver operating characteristic curve (AUC=0.725, P=0.001) exhibited the capability to predict node-positive EHCC with a sensitivity of 64.29%, and specificity of 73.68%. Furthermore, a progressive decrease in the degree of EHCC differentiation was associated with a reduction in the tumor ADC value (P=0.000). The N stage and differentiation of EHCC can be evaluated non-invasively using diffusion-weighted MRI.

Peritumoral Fat Content Identified Using Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-squares Estimation (IDEAL) Correlates with Breast Cancer Prognosis.

Adipocytes around aggressive breast cancer (BC) are less lipid different from naive adipocytes (cancer-associated adipocytes, CAAs), and peritumoral edema caused by the release of cytokines from CAAs can conduce to decrease the peritumoral fat proportion. The purpose of this study was to correlate peritumoral fat content identified by using iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) with lymph node metastasis (LNM) and recurrence-free survival (RFS) in BC patients and to compare with T2-weighted (T2WI) and diffusion-weighted images (DWI) analyses. This retrospective study consisted of 85 patients who were diagnosed with invasive carcinoma of breast and underwent breast MRI, including IDEAL before surgery. The scan time of fat fraction (FF) map imaging using IDEAL was 33s. Four regions of interest (ROIs), which are 5 mm from the tumor edge, and one ROI in the mammary fat of the healthy side were set on the FF map. Then average peritumoral FF values (TFF), average FF values on the healthy side (HFF), and peritumoral fat ratio (PTFR, which is defined as TFF/HFF) were calculated. Tumor apparent diffusion coefficient (ADC) values were measured on ADC map obtained by DWI. Peritumoral edema was classified into three grades based on the degree of signal intensity around the tumor on T2WI (T2 edema). The results of stepwise logistic regression analysis for four variables (TFF, PTFR, T2 edema, and ADC value) indicated that TFF and T2 edema were significant factors of LNM (p < 0.01). RFS was significantly associated with TFF (p = 0.016), and 47 of 49 (95.9%) patients with TFF more than 85.5% were alive without recurrence. Peritumoral fat content identified by using IDEAL is associated with LNM and RFS and may therefore be a useful prognostic biomarker for BC.

Clinical value of conventional magnetic resonance imaging combined with diffusion-weighted imaging in predicting pelvic lymph node metastasis of cervical cancer.

In cervical cancer (CC), the involvement of pelvis lymph nodes is a crucial factor for patients' outcome. We aimed to investigate the value of conventional magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in predicting CC pelvic lymph node metastasis (PLNM). This retrospective study included CC patients who received surgical treatments. Surgical pathology results served as the gold standard for investigating the diagnostic performance of conventional MRI combined with DWI. We analyzed the association between tumor ADC and PLNM, as well as other pathological factors. The areas under the receiver operating characteristic curves (AUCs) for ADC in assessing PLNM and pathological factors were evaluated, and optimal cut-off points were obtained. A total of 261 CC patients were analyzed. PLNM patients had significantly lower tumor ADC (0.829 ± 0.144×10-3mm2/s vs. 1.064 ± 0.345×10-3mm2/s, p<0.0001), than non-PLNM CC. The agreement between conventional MRI combined with DWI and pathological results on PLNM diagnosis was substantial (Kappa=0.7031, p<0.0001), with 76% sensitivity, 94.31% specificity, and 90.8% accuracy. The AUC of tumor ADC was 0.703, and the optimal cut-off was 0.95×10-3 mm2/s. In multivariate analysis model 1, tumor ADC<0.95×10-3mm2/s was significantly associated with PLNM (OR, 2.83; 95%CI, 1.08-7.43; p= 0.0346) after adjusting for age and pathological risk factors. In multivariate analysis model 2, tumor ADC<0.95×10-3mm2/s (OR, 4.00; 95%CI, 1.61-9.89; p=0.0027), age<35 years old (OR, 2.93; 95%CI, 1.04-8.30; p=0.0428), increased tumor diameter on MRI (OR, 2.17; 95%CI, 1.18-3.99; p=0.0128), vaginal vault involvement on MRI (OR, 2; 95%CI, 1.002-3.99; p=0.0494) were independent predictors for PLNM. Tumor ADC<0.95×10-3mm2/s was significantly associated with higher risk of tumor diameter ≥4cm (OR, 2.60; 95%CI, 1.43-4.73; p=0.0017), muscular layer infiltration >1/2 (OR, 5.46; 95%CI, 3.19-9.34; p<0.0001), vaginal vault involvement (OR, 2.25; 95%CI, 1.28-3.96; p=0.0051), and lymphovascular space involvement (OR, 3.81; 95%CI, 2.19-6.63; p<0.0001). Conventional MRI combined with DWI had a good diagnostic performance in detecting PLNM. The tumor ADC value in PLNM patients was significantly lower than that in non-PLNM patients. Tumor ADC <0.95×10-3mm2/s, age <35 years old, increased tumor diameter on MRI, vaginal vault involvement on MRI were independent predictors for PLNM.

Preoperative Dynamic Contrast-Enhanced and Diffusion-Weighted Breast Magnetic Resonance Imaging Findings for Prediction of Lymphovascular Invasion of the Lesions in Node-Negative Invasive Breast Cancer.

Purpose: Our single-centre retrospective study aimed to investigate the relationship between preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings and apparent diffusion coefficient (ADC) values and lymphovascular invasion (LVI) status of the lesions in patients with clinically-radiologically lymph node-negative invasive breast cancer. Methods: A total of 250 breast lesions diagnosed in preoperative magnetic resonance imaging were identified. All patients were divided into 2 subgroups: LVI-negative and LVI-positive according to the pathological findings of surgical specimens. The 2 groups' DCE-MRI findings, ADC values, and histopathological results of lesions were compared. Results: LVI was detected in 100 of 250 lesions. Younger age than 45 years and larger lesion size than 20 mm were found to be associated with the presence of LVI (P < .001). High histological and nuclear grade (P = .001), HER2-enriched molecular subtype (P = .001), and Ki-67 positivity (P = .016) were significantly associated with LVI. The LVI positivity rate was significantly higher in the lesions with medium-rapid initial phase kinetic curve and washout delayed phase kinetic curve (P = .001). The presence of LVI was significantly associated with the presence of peritumoural edema, sentinel lymph node metastasis, adjacent vessel sign, and increased whole breast vascularity (P < .001). When diffusion-weighted imaging findings were evaluated, it was determined that tumoural ADC values lower than 1068 × 10-6 mm2/second (P = .002) and peritumoural-tumoural ADC ratios higher than 1.5 (P = .001) statistically increased the probability of LVI. Conclusion: The patient's age, various histopathological and DCE-MRI findings, tumoural ADC value, and peritumoural-tumoural ADC ratio may be useful in the preoperative prediction of LVI status in breast cancer lesions.

Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole‐body Diffusion‐weighted MR Imaging

BackgroundThe International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole‐body diffusion‐weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM.PurposeTo explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM).Study TypeRetrospective.PopulationThirty‐six patients with NDMM.Field Strength/Sequence3.0T/single‐shot DWI echo planar imaging (EPI) sequence with an integrated slice‐by‐slice shimming (iShim) technique.AssessmentBaseline (median: 1 day before treatment) and post‐treatment (median: five cycles of therapy) whole‐body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per‐patient total tumor data. Post‐treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression‐free survival (PFS) was also calculated.Statistical TestsMann–Whitney test and Fisher's exact or Chi‐squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan–Meier analysis and Cox proportional hazards model. A two‐tailed P‐value &lt;0.05 was considered statistically significant.ResultsThirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post‐treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821–0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392–190.677).Data ConclusionttADC histogram may facilitate response assessment in patients with NDMM.Level of Evidence3Technical EfficacyStage 4

Editorial for: “Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole‐body Diffusion‐weighted MR Imaging”

Editorial for: “Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole‐body Diffusion‐weighted <scp>MR</scp> Imaging”

Apparent diffusion coefficient measurements of bone marrow infiltration patterns in multiple myeloma for the assessment of tumor burden - a feasibility study.

The purpose of our study was to explore and compare the tumor burden of different bone marrow infiltration patterns and evaluate the feasibility of apparent diffusion coefficient (ADC) value to identify patterns in multiple myeloma (MM). Ninety-three patients with newly diagnosed multiple myeloma and 23 controls had undergone routine magnetic resonance imaging (MRI) and diffusion-weighted MRI (DWI) from January 2019 to November 2020. Five bone marrow (BM) infiltration patterns were allocated according to routine MRI. The laboratory data and ADC values of patterns were analyzed and compared. ROC analysis was used to establish the best diagnostic ADC threshold value for identifying these patterns and distinguishing normal pattern from controls. Besides, the correlation between the ADC values of diffuse pattern and the plasma cells ratio was assessed. The values of hemoglobin, beta-2 microglobulin (β2-MG), plasma cell, M protein, the percentages of stage, high-risk fluorescence in situ hybridization, and ADC values showed significant difference among patterns. ADCmean at a specific value (368.5×10-6 mm2/s) yielded a maximum specificity (95.5%) and sensitivity (92.0%) in diagnosing MM. A specific value (335.5×10-6mm2/s) yielded a maximum specificity (84.7%) and sensitivity (88.0%) in discriminating visually normal pattern in MM from controls. There was a moderate positive correlation between the plasma cells ratio and ADCs of diffuse infiltration patterns (r = 0.648, P < 0.001). The bone marrow infiltration patterns in MM patients can indicate the tumor burden and ADC value has the ability to discriminate these patterns objectively.

The value of apparent diffusion coefficient in predicting treatment response of rectal cancer after neoadjuvant radiation therapy

Objective: To evaluate the value of the apparent diffusion coefficient (ADC) in predicting treatment response in rectal cancer patients after neoadjuvant chemoradiation therapy (nRCT). Subject and method: A study was conducted on 29 rectal cancer patients who underwent nRCT. Patients underwent magnetic resonance imaging (MRI), and tumor volume and ADC values (b-values: 0-1000s/mm²) were measured before and after nRCT. ADC values were measured in two ways: 1. For the entire tumor (ADC1) and 2. On the slice with the largest tumor area (ADC2). Changes in tumor volume (ΔV) and ADC values (ΔADC) before and after treatment were compared with the surgical pathology results, categorized into complete response (pCR)/incomplete response and downstaging T/not downstaging T groups. Result: ΔADC values were higher in the downstaging T group compared to the non-downstaging T group, with ΔADC1 values of 45.4% and 19.1%, respectively (p = 0.005), and ΔADC2 values of 51.7% and 20.2%, respectively (p = 0.01). At the ΔADC1 threshold of 42.2%, sensitivity was 55.6%, and specificity was 100%, while for ΔADC2 at 18.1%, sensitivity and specificity were 88.9% and 72.7%, respectively. There was no statistically significant difference in ΔADC values between the complete response and incomplete response groups (p&gt;0.05). Changes in tumor volume did not provide prognostic value for treatment response to NRCT. Conclusion: The ΔADC value is a potential prognostic factor in predicting treatment response in rectal cancer patients after nRCT, with more accurate diagnostic information compared to tumor volume.