Apparent diffusion coefficients of resectable rectal adenocarcinoma and distal paracancerous tissues derived from diffusion weighted imaging: association with tumor stage

Apparent diffusion coefficients of resectable rectal adenocarcinoma and distal paracancerous tissues derived from diffusion weighted imaging: association with tumor stage | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Apparent diffusion coefficients of resectable rectal adenocarcinoma and distal paracancerous tissues derived from diffusion weighted imaging: association with tumor stage Hui Luo, Yue-qin Gou, Yue-su Wang, Hui-lin Qin, Hai-ying Zhou, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7767461/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2026 Read the published version in Chinese Journal of Academic Radiology → Version 1 posted You are reading this latest preprint version Abstract Purpose To determine whether the apparent diffusion coefficient (ADC) parameters of tumor and distal paracancerous tissues in rectal adenocarcinoma (RA) derived from diffusion weighted imaging (DWI) can be associated with the tumor stages. Materials and methods 134 consecutive patients with RA underwent preoperative DWI (b = 0, 1000 s/mm 2 ). ADC values of the tumor, distal tumor-adjacent and tumor-distant tissues were measured (recorded as ADC t , ADC dta and ADC dtd , respectively). Additionally, ratios of ADC t to ADC dta (ADC t/dta ), ADC t to ADC dtd (ADC t/dtd ), and ADC dta to ADC dtd (ADC dta/dtd ) were calculated. Student’s t-test or Mann-Whitney U test were performed to compare the differences in the aforementioned ADC parameters between different tumor stages. The diagnostic efficacy of individual ADC and combined ADC parameters was evaluated using logistic regression analysis and receiver operating characteristic (ROC) analysis to predict tumor stages. Results Tumors with pT 3–4 stage demonstrated significantly lower values of ADC t , ADC t/dta , and ADC t/dtd compared to those with pT 1–2 stage; tumors with pN 1–2 stage exhibited significantly lower values of ADC t and ADC t/dta compared to those with pN 0 stage; and cases with lymph node metastasis (LNM) showed significantly lower values of ADC t , ADC t/dta , and ADC t/dtd compared to those without LNM (all P -values < 0.05). Area under the ROC curves (AUC) of the combination involving ADC t and ADC t/dta was higher than that of individual ADC parameters when assessing pT stage, pN stage, and LNM. Conclusion The ADC parameters of tumor and distal paracancerous tissues could be somewhat helpful in preoperatively assessing pT stage, pN stage, and LNM in RA. Diffusion-weighted imaging Apparent diffusion coefficient Rectal adenocarcinoma Paracancerous tissue Tumor stage Figures Figure 1 Figure 2 Figure 3 Introduction Rectal cancer is a prevalent malignant tumor globally, with adenocarcinoma being the most common histological subtype comprising more than 90% of cases [1, 2]. Prognosis varies among patients due to different disease stages [3]. In early-stage rectal cancer patients, the 5-year survival rates are approximately 90%, whereas for those with advanced rectal cancer, the 5-year survival rates drop below 10% [4]. Furthermore, the management of rectal cancer is individualized based on the specific stage of the disease for each patient [5, 6]. Thus, preoperative assessment of tumor stage plays a crucial role in determining the therapeutic approach and improving prognosis for individuals with resectable rectal adenocarcinoma (RA). Diffusion-weighted imaging (DWI), a non-enhanced functional magnetic resonance imaging (MRI) technique, is utilized for evaluating the microscopic random motion of water molecules in biological tissues. The apparent diffusion coefficient (ADC) is derived from DWI and serves as a quantitative measure for assessing the mobility of water molecules [7-9]. The ADC value is impacted by various factors, including cellular density, cell membrane integrity, impediments within the fluid, and the specific compartment in which the water molecules are located [7]. Some studies indicated that ADC parameters of the tumor were related to the pT stage [10-14] and pN stage [12, 15]. Additionally, paracancerous tissue actively interacts with the tumor, potentially offering valuable supplementary information. Chen et al. [16] found that ADC could help distinguish between RA, adjacent tissues of the tumor (about 1 cm from the tumor margins), and tissues near the safe resection margins. Moreover, the distal resection margin plays a pivotal role in the prognosis of rectal cancer [17], and the length of distal tumor infiltration into the paracancerous tissue can be influenced by tumor stage [4, 18]. To the best of our knowledge, the relationship of ADC parameters obtained from both tumor and distal paracancerous tissues with the tumor stage has not been explored in detail. Therefore, the purpose of this study was to investigate the associations of these ADC parameters with the tumor stage in resectable RA, as well as to evaluate its diagnostic performance in predicting the tumor stage. Materials and methods Patients The study protocol was approved by the institutional review board at our hospital, and informed consent requirements were exempted due to the retrospective design of this study. We consecutively enrolled a total of 156 patients with resectable RA who underwent preoperative MRI scans at our institution between January 2017 and December 2023. The following criteria were used for inclusion: (a) patients received MRI scans within 14 days before surgery; (b) patients had not undergone any form of cancer therapy prior to undergoing MRI scans; (c) postoperative pathology confirmed adenocarcinoma, and reported the pT stage, pN stage, lymph node status, and tumor deposit status; and (d) the distal tumor margin was located at a minimum distance of 3 cm above the dentate line. The following criteria were utilized to exclude certain cases: (a) the tumor size was too small to be measured for its ADC value (n = 3); (b) the presence of mucus was observed within the tumor (n = 9); (c) the image quality was deemed inadequate (n = 7); or (d) the clinical records of patients were found to be incomplete (n = 3). Ultimately, our study comprised a cohort of 134 patients for analysis. All individuals diagnosed with RA underwent radical resection combined with regional lymph node dissection. The pT stage and pN stage of the tumor were determined through postoperative histopathological examination, following the 8th edition of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system [19]. MR techniques The imaging procedure was conducted on each patient using a 3.0 Tesla scanner (Discovery MR 750, GE Healthcare, Milwaukee, WI, USA) equipped with a 32-channel phased-array torso coil. The participants were positioned in a supine posture during the scanning procedure. The scanning range was from the level of the sacral promontory to below the anal verge. T 2 -weighted (T 2 W) imaging was performed in the axial and sagittal planes. Sagittal T 2 W Propeller with fat suppression sequences were acquired using the following parameters: repetition time (TR) = 13166 ms, echo time (TE) = 102.9 ms, flip angle = 160°, field of view (FOV) = 30 cm × 30 cm, slice thickness = 5 mm, intersection gap = 1 mm, matrix = 352 × 352, and number of excitations (NEX) = 1. Axial T 2 W Propeller with fat suppression sequences were acquired perpendicular to the longitudinal axis of the rectum using the sagittal plane. The imaging parameters were as follows: TR = 7936 ms, TE = 95.6 ms, flip angle = 140°, FOV = 41 cm× 41 cm, slice thickness = 5 mm, intersection gap = 1 mm, matrix = 320 × 320, and NEX = 1. The axial DWI was obtained using an echo-planar imaging sequence in the identical orientation as axial T 2 W imaging, and employing the following parameters: TR = 3225 ms, TE = 57 ms, flip angle = 90°, FOV = 38 cm × 30 cm, slice thickness = 5 mm, intersection gap = 1mm, and matrix = 128 × 192. The DWI included b-values of 0 and 1000 s/mm 2 , with corresponding NEX of 1 and 4, respectively. Image analysis The DWI images were transferred to the GE Healthcare Advantage Workstation (version 4.6), where the post-processing Functool software automatically generated ADC maps. The images were independently analyzed by two radiologists (radiologists 1 and 2, with 7 and 3 years of experience, respectively). The detailed histopathology information of patients with RA was blinded to both radiologists. Clinically, a distal resection margin of 3 cm is generally considered safe margin for patients with rectal cancer [5, 17]. Moreover, molecular alterations associated with tumorigenesis are evident up to 1 cm from the tumor margins [20, 21]. Hence, in this study, tissues located approximately 1 cm and 3 cm from the distal tumor margin were defined as distal tumor-adjacent (DTA) tissue and distal tumor-distant (DTD) tissue, respectively. The methods used to measure ADCs of tumor, DTA and DTD tissues were as follows (Figure 1). Firstly, the tumor’s location was determined based on T 2 W and DWI images, where it manifested as an abnormally thickened rectal wall, exhibiting iso- or hyperintensity on T 2 W image and hyperintensity on DWI image. Secondly, We selected the maximum cross-sectional area of the tumor and delineated a region of interest (ROI) along its edge on axial high b-value DWI images. Thirdly, the locations of DTA and DTD tissues were determined based on the sagittal T 2 W images. Following the methodology described in a previously published report [16], the ROIs of DTA and DTD tissues were delineated on the corresponding axial DWI images. The ROIs covered more than half of the rectal wall, carefully excluding surrounding adipose tissue and luminal gas. Simultaneously, the ROIs for the tumor, DTA, and DTD tissues were automatically generated on the corresponding ADC maps. We obtained the mean ADC values of the tumor, DTA, and DTD tissues, which were recorded as ADC t , ADC dta , and ADC dtd , respectively. The ADC measurement was conducted three times for each tissue, and the final value was determined by computing the average of these three measurements. In addition, the ADC ratios were calculated to represent the relative change in ADC values between different tissues: ADC t/dta = ADC t /ADC dta , ADC t/dtd = ADC t /ADC dtd , and ADC dta/dtd = ADC dta /ADC dtd . The ADC t , ADC dta and ADC dtd values were independently measured by radiologists 1 and 2 to evaluate the interobserver agreement. Additionally, the previous measurement was repeated by radiologist 1 after one month to assess the intraobserver agreement. Statistical analyses Statistical analyses were performed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA). A P-value less than 0.05 was considered to indicate statistical significance. The intraclass correlation coefficient (ICC) was used to assess the inter- and intra-observer agreements for the ADC measurements. If both agreements were good (0.6 0.8) [16], the initial measurements conducted by radiologist 1 would be utilized as the final values for subsequent analysis; otherwise, the average of three measurements conducted by radiologist 1 and 2 would be utilized as the final values for analysis. The Shapiro-Wilk test was used to examine the distribution pattern of continuous variables. Data that conformed to a normal distribution were described as mean ± standard deviation, while data that did not follow it were presented using the median (25th percentile, 75th percentile). The ADCs of the tumor, DTA and DTD tissues were compared using the one-way repeated measures ANOVA (for normally distributed data) or Friedman test (for non-normally distributed data) with Bonferroni correction. The ADC parameters were analyzed using Student’s t-test (for normally distributed data) or Mann-Whitney U test (for non-normally distributed data) to compare differences between different groups. For variables showing statistically significant differences in ADC parameters between different groups, logistic regression analysis and receiver operating characteristic (ROC) curve analysis were used to evaluate the diagnostic performance of individual ADC parameters and combined ADC parameters in predicting tumor stage. Results Patient characteristics A total of 134 patients with RA were finally included for analysis, with a median age of 65 years (interquartile range: 53–72 years), as detailed in Table 1. Inter- and intra-observer agreements of ADC measurement The interobserver agreements for ADC t (ICC, 0.885; 95% confidence interval [CI], 0.836–0.919), ADC dta (ICC, 0.911; 95% CI, 0.877–0.936), and ADC dtd (ICC, 0.917; 95% CI, 0.885–0.940) were found to be excellent in this study. Similarly, the intraobserver agreements for ADC t (ICC, 0.900; 95% CI, 0.841–0.935), ADC dta (ICC, 0.953; 95% CI, 0.935–0 .966), and ADC dtd (ICC, 0.924; 95% CI, 0.895–0.946) were also excellent. Therefore, the first measurements taken by radiologist 1 were repeatable and used as the final values for subsequent analysis. Comparison of ADCs between the tumor, DTA and DTD tissues The ADC values of the tumor, DTA and DTD tissues were presented as the median (25th percentile, 75th percentile), which were 0.987 (0.939, 1.044) × 10 −3 mm 2 /s, 1.415 (1.263, 1.520) × 10 −3 mm 2 /s, and 1.550 (1.419, 1.644) × 10 −3 mm 2 /s respectively (Figure 2). The Friedman test with Bonferroni correction revealed statistically significant differences in ADCs between different tissues. The ADC value of tumor was significantly lower compared to both DTA and DTD tissues, and the ADC value of DTA tissue was lower than that of DTD tissue (all P -values < 0.001). Association between ADC parameters and tumor stage The ADC parameters were compared between pT 1–2 stage and pT 3–4 stage, as well as between pN 0 stage and pN 1–2 stage. The corresponding results are presented in Table 2. Tumors with pT 3–4 stage demonstrated significantly lower values of ADC t ( P -value = 0.001), ADC t/dta ( P -value = 0.017), and ADC t/dtd ( P -value = 0.019) compared to those with pT 1–2 stage. Tumors with pN 1–2 stage exhibited significantly lower values of ADC t ( P -value = 0.005) and ADC t/dta ( P -value = 0.021) compared to those with pN 0 stage. Additionally, both lymph node metastasis (LNM) and tumor deposit (TD) are recognized as N staging elements according to the 8th edition of the AJCC TNM staging system (19). Comparisons of ADC parameters were also conducted between LNM-negative and LNM-positive cases, as well as between TD-negative and TD-positive cases, as shown in Table 3. Patients with the presence of LNM showed significantly lower values of ADC t ( P -value = 0.002), ADC t/dta ( P -value = 0.005), and ADC t/dtd ( P -value = 0.023) compared to those without LNM. However, there was no significant association between the ADC parameters and TD (all P -values > 0.05). ROC analyses of ADC parameters to assess pT stage, pN stage, and LNM Based on the aforementioned results, ROC analysis was performed to evaluate the diagnostic performance of individual ADC parameters and combined ADC parameters in predicting pT stage, pN stage, and LNM. The findings are displayed in Table 4 and Figure 3. The area under the ROC curves (AUCs) for the combined ADC t and ADC t/dta (AUC = 0.720), as well as for the combined ADC t , ADC t/dta , and ADC t/dtd (AUC = 0.721), exhibited higher values compared to other individual or combined ADC parameters when evaluating pT stage. The AUC of the combined ADC t and ADC t/dta was highest when assessing pN stage (AUC = 0.672) and LNM (AUC = 0.711). Discussion The ADC value serves as a potential imaging biomarker that reflects the biological characteristics of tissues [14]. Previous studies have demonstrated that ADC parameters of tumors were related to the pT stage [10-14] and pN stage [12, 15]. Furthermore, LNM and TD are recognized as N staging elements in accordance with the 8th edition of the AJCC TNM staging system [19]. In this study, we investigated the associations of ADC parameters obtained from both tumor and distal paracancerous tissues with pT stage, pN stage, LNM, and TD in resectable RA. Additionally, we evaluated the diagnostic performance of certain individual ADC parameters and combined ADC parameters in predicting the pathological stage. Our results indicated that the tumors exhibited significantly lower mean ADCs compared to DTA and DTD tissues, which can be explained by the irregular cell morphology and increased cellular density within the tumor, leading to distorted and narrower intercellular spaces that restrict the diffusion of water molecules [22]. In addition, the mean ADC of DTA tissue was significantly lower than that of DTD tissue, which is consistent with the previous research [16]. The likely reason for this phenomenon is that the tumor-adjacent tissue actively interacts with the tumor and exhibits numerous complex molecular changes, which are associated with various conditions such as tumorigenesis, fibrosis, and inflammatory inductions [20, 21, 23, 24]. Additionally, molecular changes that occur during tumorigenesis lead to abnormal increases in both water molecule mobility and quantity [25]. Du et al. [26] observed a negative correlation between the ADC value and the severity of intestinal inflammation and fibrosis. Therefore, water molecule diffusion is more restricted in DTA tissues compared with DTD tissues. In our study, tumors classified as pT 3–4 stage exhibited significantly lower ADC t values compared to those classified as pT 1–2 stage. Tumors categorized as pN 1–2 stage demonstrated significantly lower ADC t values compared to those categorized as pN 0 stage. And, the presence of LNM was associated with significantly lower ADC t values compared to cases without LNM. These findings of our research are in line with the results of prior studies [12, 13]. The observed trend could be explained by the fact that as tumors progress, there is a higher density of tumor cells and less extracellular space, which leads to greater hindrance in the diffusion of water molecules. Consequently, this results in lower ADC t values for more advanced stage tumors. Several studies have shown that tumors with TD-positive exhibit significantly lower ADC values compared to tumors with TD-negative [13, 27]. But, our research suggested that there was no significant association between the ADC t and TD, possibly due to the relatively small patient population of TD-positive. Additionally, tumor stage has been reported to potentially impact the length of tumor infiltration into adjacent tissue, and certain molecular changes in tumor-adjacent tissue vary at different stages of the tumor [4, 18, 23]. However, the results of our study showed no significant differences in ADC dta and ADC dtd between different tumor stages. On one hand, various factors such as patient age, degree of fibrosis, inflammation, and tumor infiltration in distal paracancerous tissues may potentially influence ADC dta and ADC dtd ; on other hand, using different methods of ROI delineation for paracancerous tissues could potentially impact the outcomes of the study. Currently, the research on the ADC of tumor-adjacent rectal tissue is limited, and we have employed the ROI delineation method as mentioned in previously published literature [16]. Further research is needed to determine whether different ROI delineation methods may produce different results. ADC, as an absolute value, can be influenced by various factors, such as imager vendors, field strength, imaging parameters, breathing patterns and demographic characteristics. In recent years, several studies have investigated the potential benefits of using the ADC ratio instead of absolute ADC values because it may partially reduce or eliminate some external effects [13, 28, 29]. We further investigated the relationship between ADC ratios (ADC t/dta , ADC t/dtd and ADC dta/dtd ) and tumor stage. We found that ADC t/dta was associated with pT stage, pN stage, and LNM, while ADC t/dtd was associated with pT stage and LNM. Furthermore, both ADC t/dta and ADC t/dtd showed a certain degree of decreased diagnostic performance compared to ADC t alone in assessing pT stage, pN stage, and LNM. There are two possible reasons for this. Firstly, various factors such as population characteristics, inflammatory cell infiltration and tumor infiltration can affect the ADC of distal paracancerous tissues. Secondly, Takatsu et al. [30] have demonstrated that the different slice positions can influence ADC. In this study, ROIs for ADC t , ADC dta , and ADC dtd were located in different slices, and ADC ratios failed to eliminate the impact of slice positions. Combining any two or all three of ADC t , ADC t/dta , and ADC t/dtd results in a slight improvement in the diagnostic efficacy for predicting pT stage, pN stage, and LNM compared to an individual ADC parameter. Moreover, the AUC of the combination involving ADC t and ADC t/dta was higher when assessing pT stage, pN stage, and LNM. This could be attributed to the valuable information provided by DTA tissue or possibly due to the elimination of some external effects through the ratio of ADC t to ADC dta . Our study had some limitations. Firstly, it was a single-center retrospective study with a relatively small number of patients, particularly in cases of TD-positive (11 of 134). Thus, future studies with a larger sample size are recommended. Secondly, we only investigated the mean ADC values of the tumor, DTA and DTD tissue without analyzing their additional parameters such as maximum and minimum ADC values; it is worth noting that exploring the ADC histogram parameters could potentially provide additional information. Therefore, we plan to conduct further relevant research in the near future. In conclusion, our study revealed that RA with pT 3–4 stage demonstrated lower ADC t , ADC t/dta , and ADC t/dtd than with pT 1–2 stage, the tumor with pN 1–2 stage exhibited lower ADC t and ADC t/dta than with pN 0 stage, and cases with LNM showed lower ADC t , ADC t/dta , and ADC t/dtd than without LNM. Certain individual and combined ADC parameters could be helpful to some extent in preoperatively assessing pT stage, pN stage, and LNM, among which the combination involving ADC t and ADC t/dta can be more helpful than that of individual ADC parameters. We hope that our findings can be helpful for better understanding of the diffusion of water molecules in RA and the distal paracancerous tissues. Abbreviations RA Rectal adenocarcinoma DWI Diffusion-weighted imaging MRI Magnetic resonance imaging ADC Apparent diffusion coefficient AJCC American Joint Committee on Cancer TNM Tumor-node-metastasis () s T 2 W T 2 -weighted TR Repetition time TE Echo time FOV Field of view NEX Number of excitations DTA Distal tumor-adjacent DTD Distal tumor-distant ROI Region of interest ADC t ADC of tumor tissue ADC dta ADC of DTA tissue ADC dtd ADC of DTD tissue ADC t/dta Ratio of ADC t to ADC dta ADC t/dtd Ratio of ADC t to ADC dtd ADC dta/dtd Ratio of ADC dta to ADC dtd ICC Intraclass correlation coefficient ROC Receiver operating characteristic CI Confidence interval LNM Lymph node metastasis TD Tumor deposit AUC Area under the ROC curve Declarations Acknowledgments: Not applicable. Conflicts of interest : The authors have no conflicts of interest to declare that are relevant to the content of this article. Ethics approval : The study was approved by the Ethical Committees of the Affiliated Hospital of North Sichuan Medical College (Number: 2024ER219-1). Informed consent : The Institutional Review Board waived the requirement for written informed consent due to the retrospective nature of the study. Data availability : The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Author contributions Guarantor of integrity of the entire study: Tian-wu Chen. Study concepts and design: Hai-ying Zhou, Xiao-ming Zhang, and Tian-wu Chen. Literature research: Yue-su Wang and Hui-lin Qin. Clinical studies: Hui Luo, Yue-qin Gou, and Yue-su Wang. Experimental studies/data analysis: Hui Luo and Hui-lin Qin. Statistical analysis: Hui Luo and Yue-qin Gou. Manuscript preparation: Hui Luo, Yue-qin Gou, Yue-su Wang, and Hui-lin Qin. Manuscript editing: Hui Luo, Hai-ying Zhou, Xiao-ming Zhang, and Tian-wu Chen. 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Abdominal Diffusion-Weighted MRI With Simultaneous Multi-Slice Acquisition: Agreement and Reproducibility of Apparent Diffusion Coefficients Measurements. J Magn Reson Imaging. 2024;59(4):1170–8. Takatsu Y, Nakamura M, Suzuki Y, Miyati T. Dependence of apparent diffusion coefficient on slice position in magnetic resonance diffusion imaging. Magn Reson Imaging. 2023;99:41–7. Tables Table 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Table2.docx Table3.docx Table4.docx Cite Share Download PDF Status: Published Journal Publication published 06 Jan, 2026 Read the published version in Chinese Journal of Academic Radiology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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irregular thickening of rectal wall. (b) Axial diffusion-weighted imaging (DWI) with a b-value of 1000 s/mm\u003csup\u003e2\u003c/sup\u003e shows that the tumor appears as a hyperintense lesion, and the apparent diffusion coefficient (ADC) of the tumor (ADC\u003csub\u003et\u003c/sub\u003e) is measured by manually delineating the region of interest (ROI) on its largest cross-section. (c) The ROI of the tumor is automatically transferred onto the ADC map to obtain the ADC\u003csub\u003et\u003c/sub\u003e value, which is 1.080 × 10\u003csup\u003e-3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s. (d) On sagittal T\u003csub\u003e2\u003c/sub\u003e-weighted imaging, the red, orange and blue lines represent the distal tumor margin, the distal tumor-adjacent (DTA) and distal tumor-distant (DTD) tissue, respectively. (e) The ROI is manually delineated to encompass more than a half circle of the rectal wall to measure the ADC of DTA tissue (ADC\u003csub\u003edta\u003c/sub\u003e). (f) On the ADC map, the ADC\u003csub\u003edta\u003c/sub\u003e value is 1.450 × 10\u003csup\u003e-3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s. The ADC measurement of DTD tissue is conducted in a manner consistent with that of DTA tissue.\u003c/p\u003e","description":"","filename":"Figure1a.png","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/01a36a4bcdd71f9ae9a1bf28.png"},{"id":93946811,"identity":"927991bc-7683-41d0-a0ef-5331c3cccdeb","added_by":"auto","created_at":"2025-10-20 14:24:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":52293,"visible":true,"origin":"","legend":"\u003cp\u003eComparisons of ADC values between the tumor, DTA and DTD tissues.\u003c/p\u003e\n\u003cp\u003eIn boxplot, boxes represent the interquartile range, and the lines inside show the median; whiskers denote the lowest and highest values within 1.5 times the interquartile range; and asterisks indicate significant differences between the tissues (*** \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eNotes:\u003cstrong\u003e \u003c/strong\u003eADC, apparent diffusion coefficient; DTA, distal tumor-adjacent; and DTD, distal tumor-distant.\u003c/p\u003e","description":"","filename":"Figure214.png","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/64c82853412f19d9557d4b2d.png"},{"id":93947838,"identity":"e354aa71-a7a0-4dd0-8a44-54f2570931e6","added_by":"auto","created_at":"2025-10-20 14:32:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":404472,"visible":true,"origin":"","legend":"\u003cp\u003eROC analyses of ADC parameters for assessment of pT stage (a), pN stage (b) and LNM (c).\u003c/p\u003e\n\u003cp\u003eNotes: ROC, receiver operating characteristic curve; ADC, apparent diffusion coefficient; LNM, lymph node metastasis; ADC\u003csub\u003et\u003c/sub\u003e, ADC of tumor tissue; ADC\u003csub\u003edta\u003c/sub\u003e, ADC of distal tumor-adjacent tissue; ADC\u003csub\u003edtd\u003c/sub\u003e, ADC of distal tumor-distant tissue; ADC\u003csub\u003et/dta\u003c/sub\u003e, ratio of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edta\u003c/sub\u003e; and ADC\u003csub\u003et/dtd\u003c/sub\u003e, ratio of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edtd\u003c/sub\u003e.\u003c/p\u003e","description":"","filename":"Figure3a.png","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/480fc681436a1d8ae47ba13c.png"},{"id":100070860,"identity":"c8f33ccb-b430-4577-8851-205d7ece591d","added_by":"auto","created_at":"2026-01-12 16:18:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2748249,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/fbc7d170-31eb-4d62-b642-b06b3b9e89b1.pdf"},{"id":93946816,"identity":"82fb6f4f-ac60-43a1-be8a-58c1e2defa40","added_by":"auto","created_at":"2025-10-20 14:24:35","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":19528,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/241502bc70b7377b1323767f.docx"},{"id":93946822,"identity":"08fd2c73-95d4-47a0-bfc9-d36dbf397070","added_by":"auto","created_at":"2025-10-20 14:24:35","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":16663,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/7ac282eb1649197130b025e7.docx"},{"id":93947839,"identity":"79b7d8a3-75ed-42c3-b9db-6b1129eae398","added_by":"auto","created_at":"2025-10-20 14:32:35","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":16642,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/93d7337dfa8f640560e5363a.docx"},{"id":93946821,"identity":"622ba712-95de-41c6-9375-c7568e1f0d78","added_by":"auto","created_at":"2025-10-20 14:24:35","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":21201,"visible":true,"origin":"","legend":"","description":"","filename":"Table4.docx","url":"https://assets-eu.researchsquare.com/files/rs-7767461/v1/b7f473b79c2f175c6d44e42e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Apparent diffusion coefficients of resectable rectal adenocarcinoma and distal paracancerous tissues derived from diffusion weighted imaging: association with tumor stage","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRectal cancer is a prevalent malignant tumor globally, with adenocarcinoma being the most common histological subtype comprising more than 90% of cases [1, 2]. Prognosis varies among patients due to different disease stages [3]. In early-stage rectal cancer patients, the 5-year survival rates are approximately 90%, whereas for those with advanced rectal cancer, the 5-year survival rates drop below 10% [4]. Furthermore, the management of rectal cancer is individualized based on the specific stage of the disease for each patient [5, 6]. Thus, preoperative assessment of tumor stage plays a crucial role in determining the therapeutic approach and improving prognosis for individuals with resectable rectal adenocarcinoma (RA).\u003c/p\u003e\n\u003cp\u003eDiffusion-weighted imaging (DWI), a non-enhanced functional magnetic resonance imaging (MRI) technique, is utilized for evaluating the microscopic random motion of water molecules in biological tissues. The apparent diffusion coefficient (ADC) is derived from DWI and serves as a quantitative measure for assessing the mobility of water molecules [7-9]. The ADC value is impacted by various factors, including cellular density, cell membrane integrity, impediments within the fluid, and the specific compartment in which the water molecules are located [7]. Some studies indicated that ADC parameters of the tumor were related to the pT stage [10-14] and pN stage [12, 15]. Additionally, paracancerous tissue actively interacts with the tumor, potentially offering valuable supplementary information. Chen et al. [16] found that ADC could help distinguish between RA, adjacent tissues of the tumor (about 1 cm from the tumor margins), and tissues near the safe resection margins. Moreover, the distal resection margin plays a pivotal role in the prognosis of rectal cancer [17], and the length of distal tumor infiltration into the paracancerous tissue can be influenced by tumor stage [4, 18]. To the best of our knowledge, the relationship of ADC parameters obtained from both tumor and distal paracancerous tissues with the tumor stage has not been explored in detail. Therefore, the purpose of this study was to investigate the associations of these ADC parameters with the tumor stage in resectable RA, as well as to evaluate its diagnostic performance in predicting the tumor stage.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the institutional review board at our hospital, and informed consent requirements were exempted due to the retrospective design of this study.\u003c/p\u003e\n\u003cp\u003eWe consecutively enrolled a total of 156 patients with resectable RA who underwent preoperative MRI scans at our institution between January 2017 and December 2023. The following criteria were used for inclusion: (a) patients \u0026nbsp;received MRI scans within 14 days before surgery; (b) patients had not undergone any form of cancer therapy prior to undergoing MRI scans; (c) postoperative pathology confirmed adenocarcinoma, and reported the pT stage, pN stage, lymph node status, and tumor deposit status; and (d) the distal tumor margin was located at a minimum distance of 3 cm above the dentate line. The following criteria were utilized to exclude certain cases: (a) the tumor size was too small to be measured for its ADC value (n = 3); (b) the presence of mucus was observed within the tumor (n = 9); (c) the image quality was deemed inadequate (n = 7); or (d) the clinical records of patients were found to be incomplete (n = 3). Ultimately, our study comprised a cohort of 134 patients for analysis. All individuals diagnosed with RA underwent radical resection combined with regional lymph node dissection. The pT stage and pN stage of the tumor were determined through postoperative histopathological examination, following the 8th edition of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMR techniques \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe imaging procedure was conducted on each patient using a 3.0 Tesla scanner (Discovery MR 750, GE Healthcare, Milwaukee, WI, USA) equipped with a 32-channel phased-array torso coil. The participants were positioned in a supine posture during the scanning procedure. The scanning range was from the level of the sacral promontory to below the anal verge. T\u003csub\u003e2\u003c/sub\u003e-weighted (T\u003csub\u003e2\u003c/sub\u003eW) imaging was performed in the axial and sagittal planes. Sagittal T\u003csub\u003e2\u003c/sub\u003eW Propeller with fat suppression sequences were acquired using the following parameters: repetition time (TR) = 13166 ms, echo time (TE) = 102.9 ms, flip angle = 160\u0026deg;, field of view (FOV) = 30 cm \u0026times; 30 cm, slice thickness = 5 mm, intersection gap = 1 mm, matrix = 352 \u0026times; 352, and number of excitations (NEX) = 1. Axial T\u003csub\u003e2\u003c/sub\u003eW Propeller with fat suppression sequences were acquired perpendicular to the longitudinal axis of the rectum using the sagittal plane. The imaging parameters were as follows: TR = 7936 ms, TE = 95.6 ms, flip angle = 140\u0026deg;, FOV = 41 cm\u0026times; 41 cm, slice thickness = 5 mm, intersection gap = 1 mm, matrix = 320 \u0026times; 320, and NEX = 1.\u0026nbsp;The axial DWI was obtained using an echo-planar imaging sequence in the identical orientation as axial T\u003csub\u003e2\u003c/sub\u003eW imaging, and employing the following parameters: TR = 3225 ms, TE = 57 ms, flip angle = 90\u0026deg;, FOV = 38 cm \u0026times; 30 cm, slice thickness = 5 mm, intersection gap = 1mm, and matrix = 128 \u0026times; 192.\u0026nbsp;The\u0026nbsp;DWI included b-values of 0 and 1000 s/mm\u003csup\u003e2\u003c/sup\u003e, with corresponding NEX of 1 and 4, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImage analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe DWI images were transferred to the GE Healthcare Advantage Workstation (version 4.6), where the post-processing Functool software automatically generated ADC maps. The images were independently analyzed by two radiologists (radiologists 1 and 2, with 7 and 3 years of experience, respectively).\u0026nbsp;The detailed histopathology information of patients with RA was blinded to both radiologists.\u003c/p\u003e\n\u003cp\u003eClinically, a distal resection margin of 3 cm is generally considered safe margin for patients with rectal cancer [5, 17]. Moreover, molecular alterations associated with tumorigenesis are evident up to 1 cm from the tumor margins [20, 21]. Hence, in this study, tissues located approximately 1 cm and 3 cm from the distal tumor margin were defined as distal tumor-adjacent (DTA) tissue and distal tumor-distant (DTD) tissue, respectively.\u003c/p\u003e\n\u003cp\u003eThe methods used to measure ADCs of tumor, DTA and DTD tissues were as follows (Figure 1). Firstly, the tumor\u0026rsquo;s location was determined based on T\u003csub\u003e2\u003c/sub\u003eW and DWI images, where it manifested as an abnormally thickened rectal wall, exhibiting iso- or hyperintensity on T\u003csub\u003e2\u003c/sub\u003eW image and hyperintensity on DWI image. Secondly, We selected the maximum cross-sectional area of the tumor and delineated a region of interest (ROI) along its edge on axial high b-value DWI images. Thirdly, the locations of DTA and DTD tissues were determined based on the sagittal T\u003csub\u003e2\u003c/sub\u003eW images. Following the methodology described in a previously published report [16], the ROIs of DTA and DTD tissues were delineated on the corresponding axial DWI images. The ROIs covered more than half of the rectal wall, carefully excluding surrounding adipose tissue and luminal gas. Simultaneously, the ROIs for the tumor, DTA, and DTD tissues were automatically generated on the corresponding ADC maps. We obtained the mean ADC values of the tumor, DTA, and DTD tissues, which were recorded as ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003edta\u003c/sub\u003e, and ADC\u003csub\u003edtd\u003c/sub\u003e, respectively.\u0026nbsp;The ADC measurement was conducted three times for each tissue, and the final value was determined by computing the average of these three measurements. In addition, the ADC ratios were calculated to represent the relative change in ADC values between different tissues: ADC\u003csub\u003et/dta\u003c/sub\u003e = ADC\u003csub\u003et\u003c/sub\u003e/ADC\u003csub\u003edta\u003c/sub\u003e, ADC\u003csub\u003et/dtd\u003c/sub\u003e = ADC\u003csub\u003et\u003c/sub\u003e/ADC\u003csub\u003edtd\u003c/sub\u003e, and ADC\u003csub\u003edta/dtd\u003c/sub\u003e = ADC\u003csub\u003edta\u003c/sub\u003e/ADC\u003csub\u003edtd\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eThe ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003edta\u003c/sub\u003e and ADC\u003csub\u003edtd\u003c/sub\u003e values were independently measured by radiologists 1 and 2 to evaluate the interobserver agreement. Additionally, the previous measurement was repeated by radiologist 1 after one month to assess the intraobserver agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA). A P-value less than 0.05 was considered to indicate statistical significance. The intraclass correlation coefficient (ICC) was used to assess the inter- and intra-observer agreements for the ADC measurements. If both agreements were good (0.6 \u0026lt; ICC \u0026le; 0.8) or excellent (ICC \u0026gt; 0.8) [16], the initial measurements conducted by radiologist 1 would be utilized as the final values for subsequent analysis; otherwise, the average of three measurements conducted by radiologist 1 and 2 would be utilized as the final values for analysis. The Shapiro-Wilk test was used to examine the distribution pattern of continuous variables. Data that conformed to a normal distribution were described as mean \u0026plusmn; standard deviation, while data that did not follow it were presented using the median (25th percentile, 75th percentile).\u003c/p\u003e\n\u003cp\u003eThe ADCs of the tumor, DTA and DTD tissues were compared using the one-way repeated measures ANOVA (for normally distributed data) or Friedman test (for non-normally distributed data) with Bonferroni correction. The ADC parameters were analyzed using Student\u0026rsquo;s t-test (for normally distributed data) or Mann-Whitney U test (for non-normally distributed data) to compare differences between different groups. For variables showing statistically significant differences in ADC parameters between different groups, logistic regression analysis and receiver operating characteristic (ROC) curve analysis were used to evaluate the diagnostic performance of individual ADC parameters and combined ADC parameters in predicting tumor stage.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 134 patients with RA were finally included for analysis, with a median age of 65 years (interquartile range: 53\u0026ndash;72 years), as detailed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInter- and intra-observer agreements of ADC measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe interobserver agreements for ADC\u003csub\u003et\u003c/sub\u003e (ICC, 0.885; 95% confidence interval [CI], 0.836\u0026ndash;0.919), ADC\u003csub\u003edta\u003c/sub\u003e (ICC, 0.911; 95% CI, 0.877\u0026ndash;0.936), and ADC\u003csub\u003edtd\u003c/sub\u003e (ICC, 0.917; 95% CI, 0.885\u0026ndash;0.940) were found to be excellent in this study. Similarly, the intraobserver agreements for ADC\u003csub\u003et\u003c/sub\u003e (ICC, 0.900; 95% CI, 0.841\u0026ndash;0.935), ADC\u003csub\u003edta\u003c/sub\u003e (ICC, 0.953; 95% CI, 0.935\u0026ndash;0 .966), and ADC\u003csub\u003edtd\u003c/sub\u003e (ICC, 0.924; 95% CI, 0.895\u0026ndash;0.946) were also excellent. Therefore, the first measurements taken by radiologist 1 were repeatable and used as the final values for subsequent analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of ADCs between the tumor, DTA and DTD tissues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ADC values of the tumor, DTA and DTD tissues were presented as the median (25th percentile, 75th percentile), which were 0.987 (0.939, 1.044) \u0026times; 10\u003csup\u003e\u0026minus;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s, 1.415 (1.263, 1.520) \u0026times; 10\u003csup\u003e\u0026minus;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s, and 1.550 (1.419, 1.644) \u0026times; 10\u003csup\u003e\u0026minus;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s respectively (Figure 2). The Friedman test with Bonferroni correction revealed statistically significant differences in ADCs between different tissues. The ADC value of tumor was significantly lower compared to both DTA and DTD tissues, and the ADC value of DTA tissue was lower than that of DTD tissue (all \u003cem\u003eP\u003c/em\u003e-values \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between ADC parameters and tumor stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ADC parameters were compared between pT\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage and pT\u003csub\u003e3\u0026ndash;4\u003c/sub\u003e stage, as well as between pN\u003csub\u003e0\u003c/sub\u003e stage and pN\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage. The corresponding results are presented in Table 2. Tumors with pT\u003csub\u003e3\u0026ndash;4\u003c/sub\u003e stage demonstrated significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.001), ADC\u003csub\u003et/dta\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.017), and ADC\u003csub\u003et/dtd\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.019) compared to those with pT\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage. Tumors with pN\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage exhibited significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.005) and ADC\u003csub\u003et/dta\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.021) compared to those with pN\u003csub\u003e0\u003c/sub\u003e stage. Additionally, both lymph node metastasis (LNM) and tumor deposit (TD) are recognized as N staging elements according to the 8th edition of the AJCC TNM staging system (19). Comparisons of ADC parameters were also conducted between LNM-negative and LNM-positive cases, as well as between TD-negative and TD-positive cases, as shown in Table 3. Patients with the presence of LNM showed significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.002),\u0026nbsp;ADC\u003csub\u003et/dta\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.005), and ADC\u003csub\u003et/dtd\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e-value = 0.023) compared to those without LNM. However, there was no significant association between the ADC parameters and TD (all \u003cem\u003eP\u003c/em\u003e-values \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROC analyses of ADC parameters to assess pT stage, pN stage, and LNM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the aforementioned results, ROC analysis was performed to evaluate the diagnostic performance of individual ADC parameters and combined ADC parameters in predicting pT stage, pN stage, and LNM.\u0026nbsp;The findings are displayed in Table 4 and Figure 3. The area under the ROC curves (AUCs) for the combined ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e (AUC = 0.720), as well as for the combined ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e (AUC = 0.721), exhibited higher values compared to other individual or combined ADC parameters when evaluating pT stage. The AUC of the combined ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e was highest when assessing pN stage (AUC = 0.672) and LNM (AUC = 0.711).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe ADC value serves as a potential imaging biomarker that reflects the biological characteristics of tissues [14]. Previous studies have demonstrated that ADC parameters of tumors were related to the pT stage [10-14] and pN stage [12, 15]. Furthermore, LNM and TD are recognized as N staging elements in accordance with the 8th edition of the AJCC TNM staging system [19]. In this study, we investigated the associations of ADC parameters obtained from both tumor and distal paracancerous tissues with pT stage, pN stage, LNM, and TD in resectable RA. Additionally, we evaluated the diagnostic performance of certain individual ADC parameters and combined ADC parameters in predicting the pathological stage.\u003c/p\u003e\n\u003cp\u003eOur results indicated that the tumors exhibited significantly lower mean ADCs compared to DTA and DTD tissues, which can be explained by the irregular cell morphology and increased cellular density within the tumor, leading to distorted and narrower intercellular spaces that restrict the diffusion of water molecules [22]. In addition, the mean ADC of DTA tissue was significantly lower than that of DTD tissue, which is consistent with the previous research [16]. The likely reason for this phenomenon is that the tumor-adjacent tissue actively interacts with the tumor and exhibits numerous complex molecular changes, which are associated with various conditions such as tumorigenesis, fibrosis, and inflammatory inductions [20, 21, 23, 24]. Additionally, molecular changes that occur during tumorigenesis lead to abnormal increases in both water molecule mobility and quantity [25]. Du et al. [26] observed a negative correlation between the ADC value and the severity of intestinal inflammation and fibrosis. Therefore, water molecule diffusion is more restricted in DTA tissues compared with DTD tissues.\u003c/p\u003e\n\u003cp\u003eIn our study, tumors classified as pT\u003csub\u003e3\u0026ndash;4\u003c/sub\u003e stage exhibited significantly lower ADC\u003csub\u003et\u003c/sub\u003e values compared to those classified as pT\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage. Tumors categorized as pN\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage demonstrated significantly lower ADC\u003csub\u003et\u003c/sub\u003e values compared to those categorized as pN\u003csub\u003e0\u003c/sub\u003e stage. And, the presence of LNM was associated with significantly lower ADC\u003csub\u003et\u003c/sub\u003e values compared to cases without LNM. These findings of our research are in line with the results of prior studies [12, 13].\u0026nbsp;The observed trend could be explained by the fact that as tumors progress, there is a higher density of tumor cells and less extracellular space, which leads to greater hindrance in the diffusion of water molecules. Consequently, this results in lower ADC\u003csub\u003et\u003c/sub\u003e values for more advanced stage tumors. Several studies have shown that tumors with TD-positive exhibit significantly lower ADC values compared to tumors with TD-negative [13, 27]. But, our research suggested that there was no significant association between the ADC\u003csub\u003et\u003c/sub\u003e and TD, possibly due to the relatively small patient population of TD-positive.\u003c/p\u003e\n\u003cp\u003eAdditionally, tumor stage has been reported to potentially impact the length of tumor infiltration into adjacent tissue, and certain molecular changes in tumor-adjacent tissue vary at different stages of the tumor [4, 18, 23]. However, the results of our study showed no significant differences in ADC\u003csub\u003edta\u003c/sub\u003e and ADC\u003csub\u003edtd\u003c/sub\u003e between different tumor stages.\u0026nbsp;On one hand, various factors such as patient age, degree of fibrosis, inflammation, and tumor infiltration in distal paracancerous tissues may potentially influence ADC\u003csub\u003edta\u003c/sub\u003e and ADC\u003csub\u003edtd\u003c/sub\u003e; on other hand,\u0026nbsp;using different methods of ROI delineation for paracancerous tissues\u0026nbsp;could potentially\u0026nbsp;impact the outcomes of the study.\u0026nbsp;Currently, the research on the ADC of tumor-adjacent\u0026nbsp;rectal tissue\u0026nbsp;is limited, and we have employed the ROI delineation method as mentioned in previously published literature [16]. Further research is needed to determine whether different ROI delineation methods may produce different results.\u003c/p\u003e\n\u003cp\u003eADC, as an absolute value, can be influenced by various factors, such as imager vendors, field strength, imaging parameters, breathing patterns and demographic characteristics. In recent years, several studies have investigated the potential benefits of using the ADC ratio instead of absolute ADC values because it may partially reduce or eliminate some external effects [13, 28, 29]. We further investigated the relationship between ADC ratios (ADC\u003csub\u003et/dta\u003c/sub\u003e, ADC\u003csub\u003et/dtd\u003c/sub\u003e and ADC\u003csub\u003edta/dtd\u003c/sub\u003e) and tumor stage. We found that ADC\u003csub\u003et/dta\u003c/sub\u003e was associated with\u0026nbsp;pT stage,\u0026nbsp;pN stage, and\u0026nbsp;LNM, while\u0026nbsp;ADC\u003csub\u003et/dtd\u003c/sub\u003e was associated with\u0026nbsp;pT stage and\u0026nbsp;LNM.\u0026nbsp;Furthermore, both ADC\u003csub\u003et/dta\u003c/sub\u003e and ADC\u003csub\u003et/dtd\u003c/sub\u003e showed a certain degree of decreased diagnostic performance compared to ADC\u003csub\u003et\u003c/sub\u003e alone in assessing pT stage, pN stage, and LNM.\u0026nbsp;There are two possible reasons for this.\u0026nbsp;Firstly, various factors such as population characteristics, inflammatory cell infiltration and tumor infiltration can affect the ADC of distal paracancerous tissues. Secondly, Takatsu et al. [30] have demonstrated that the different slice positions can influence ADC. In this study, ROIs for ADC\u003csub\u003et\u003c/sub\u003e,\u0026nbsp;ADC\u003csub\u003edta\u003c/sub\u003e,\u0026nbsp;and ADC\u003csub\u003edtd\u003c/sub\u003e were located in different slices, and\u0026nbsp;ADC ratios\u0026nbsp;failed to eliminate the impact of slice positions. Combining any two or all three of ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e results in a slight improvement in the diagnostic efficacy for predicting pT stage, pN stage, and LNM compared to an individual ADC parameter. Moreover, the AUC of the combination involving ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e was higher when assessing pT stage, pN stage, and LNM. This could be attributed to the valuable information provided by DTA tissue or possibly due to the elimination of some external effects through the ratio of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edta\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eOur study had some limitations. Firstly, it was a single-center retrospective study with a relatively small number of patients, particularly in cases of TD-positive (11 of 134). Thus, future studies with a larger sample size are recommended. Secondly, we only investigated the mean ADC values of the tumor, DTA and DTD tissue without analyzing their additional parameters such as maximum and minimum ADC values; it is worth noting that exploring the ADC histogram parameters could potentially provide additional information. Therefore, we plan to conduct further relevant research in the near future.\u003c/p\u003e\n\u003cp\u003eIn conclusion,\u0026nbsp;our study revealed that RA with pT\u003csub\u003e3\u0026ndash;4\u003c/sub\u003e stage demonstrated lower ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e than with pT\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage, the tumor with pN\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage exhibited lower ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e than with pN\u003csub\u003e0\u003c/sub\u003e stage, and cases with LNM showed lower ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e than without LNM. Certain individual and combined ADC parameters could be helpful to some extent in preoperatively assessing pT stage, pN stage, and LNM, among which the combination involving ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e can be more helpful than that of individual ADC parameters. We hope that our findings can be helpful for better understanding of the diffusion of water molecules in RA and the distal paracancerous tissues.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRectal adenocarcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDWI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDiffusion-weighted imaging\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMagnetic resonance imaging\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eApparent diffusion coefficient\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAJCC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAmerican Joint Committee on Cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumor-node-metastasis () s\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eT\u003csub\u003e2\u003c/sub\u003eW\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e-weighted\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRepetition time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEcho time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFOV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eField of view\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNEX\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNumber of excitations\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDTA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDistal tumor-adjacent\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDTD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDistal tumor-distant\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRegion of interest\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003et\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eADC of tumor tissue\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003edta\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eADC of DTA tissue\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003edtd\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eADC of DTD tissue\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003et/dta\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRatio of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edta\u003c/sub\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003et/dtd\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRatio of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edtd\u003c/sub\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eADC\u003csub\u003edta/dtd\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRatio of ADC\u003csub\u003edta\u003c/sub\u003e to ADC\u003csub\u003edtd\u003c/sub\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntraclass correlation coefficient\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReceiver operating characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLNM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLymph node metastasis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumor deposit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eArea under the ROC curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors have no conflicts of interest to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe study was approved by the Ethical Committees of the Affiliated Hospital of North Sichuan Medical College (Number: 2024ER219-1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe Institutional Review Board waived the requirement for written informed consent due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuarantor of integrity of the entire study: Tian-wu Chen.\u003c/p\u003e\n\u003cp\u003eStudy concepts and design:\u0026nbsp;Hai-ying Zhou, Xiao-ming Zhang, and\u0026nbsp;Tian-wu Chen.\u003c/p\u003e\n\u003cp\u003eLiterature research: Yue-su Wang and\u0026nbsp;Hui-lin Qin.\u003c/p\u003e\n\u003cp\u003eClinical studies: Hui Luo, Yue-qin Gou,\u0026nbsp;and\u0026nbsp;Yue-su Wang.\u003c/p\u003e\n\u003cp\u003eExperimental studies/data analysis: Hui Luo and\u0026nbsp;Hui-lin Qin.\u003c/p\u003e\n\u003cp\u003eStatistical analysis: Hui Luo\u0026nbsp;and\u0026nbsp;Yue-qin Gou.\u003c/p\u003e\n\u003cp\u003eManuscript preparation: Hui Luo, Yue-qin Gou, Yue-su Wang, and Hui-lin Qin.\u003c/p\u003e\n\u003cp\u003eManuscript editing: Hui Luo, Hai-ying Zhou, Xiao-ming Zhang, and Tian-wu Chen.\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the manuscript.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no Funding for the submitted work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, et al. 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New York: Springer; 2017. pp. 251\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo H, Zeng W, Feng L, et al. Integrated transcriptomic analysis of distance-related field cancerization in rectal cancer patients. Oncotarget. 2017;8(37):61107\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShen L, Kondo Y, Rosner GL, et al. MGMT promoter methylation and field defect in sporadic colorectal cancer. J Natl Cancer Inst. 2005;97(18):1330\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSumi M, Van Cauteren M, Sumi T, Obara M, Ichikawa Y, Nakamura T. Salivary gland tumors: use of intravoxel incoherent motion MR imaging for assessment of diffusion and perfusion for the differentiation of benign from malignant tumors. Radiology. 2012;263(3):770\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBednarz-Misa I, Diakowska D, Krzystek-Korpacka M. Local and Systemic IL-7 Concentration in Gastrointestinal-Tract Cancers. Med (Kaunas). 2019;55(6).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao Y, Guo M, Zhao F, Liu Q, Wang X. Colonic stem cells from normal tissues adjacent to tumor drive inflammation and fibrosis in colorectal cancer. Cell Commun Signal. 2023;21(1):186.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarques MPM, Batista de Carvalho ALM, Mamede AP, Dopplapudi A, Garc\u0026iacute;a Sakai V, Batista de Carvalho LAE. Role of intracellular water in the normal-to-cancer transition in human cells-insights from quasi-elastic neutron scattering. Struct Dyn. 2020;7(5):054701.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDu JF, Lu BL, Huang SY, et al. A novel identification system combining diffusion kurtosis imaging with conventional magnetic resonance imaging to assess intestinal strictures in patients with Crohn's disease. Abdom Radiol (NY). 2021;46(3):936\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKargol J, Rudnicki W, Kenig J, et al. Diffusion-Weighted Magnetic Resonance Imaging of 103 Patients with Rectal Adenocarcinoma Identifies the Apparent Diffusion Coefficient as an Imaging Marker for Tumor Invasion and Regional Lymph Node Involvement. Med Sci Monit. 2021;27:e934941.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNadrljanski MM, Milosevic ZC. Relative apparent diffusion coefficient (rADC) in breast lesions of uncertain malignant potential (B3 lesions) and pathologically proven breast carcinoma (B5 lesions) following breast biopsy. Eur J Radiol. 2020;124:108854.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYe Z, Yao S, Yang T, Li Q, Li Z, Song B. Abdominal Diffusion-Weighted MRI With Simultaneous Multi-Slice Acquisition: Agreement and Reproducibility of Apparent Diffusion Coefficients Measurements. J Magn Reson Imaging. 2024;59(4):1170\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTakatsu Y, Nakamura M, Suzuki Y, Miyati T. Dependence of apparent diffusion coefficient on slice position in magnetic resonance diffusion imaging. Magn Reson Imaging. 2023;99:41\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diffusion-weighted imaging, Apparent diffusion coefficient, Rectal adenocarcinoma, Paracancerous tissue, Tumor stage","lastPublishedDoi":"10.21203/rs.3.rs-7767461/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7767461/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eTo determine whether the apparent diffusion coefficient (ADC) parameters of tumor and distal paracancerous tissues in rectal adenocarcinoma (RA) derived from diffusion weighted imaging (DWI) can be associated with the tumor stages.\u003c/p\u003e\u003ch2\u003eMaterials and methods\u003c/h2\u003e\u003cp\u003e134 consecutive patients with RA underwent preoperative DWI (b\u0026thinsp;=\u0026thinsp;0, 1000 s/mm\u003csup\u003e2\u003c/sup\u003e). ADC values of the tumor, distal tumor-adjacent and tumor-distant tissues were measured (recorded as ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003edta\u003c/sub\u003e and ADC\u003csub\u003edtd\u003c/sub\u003e, respectively). Additionally, ratios of ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edta\u003c/sub\u003e (ADC\u003csub\u003et/dta\u003c/sub\u003e), ADC\u003csub\u003et\u003c/sub\u003e to ADC\u003csub\u003edtd\u003c/sub\u003e (ADC\u003csub\u003et/dtd\u003c/sub\u003e), and ADC\u003csub\u003edta\u003c/sub\u003e to ADC\u003csub\u003edtd\u003c/sub\u003e (ADC\u003csub\u003edta/dtd\u003c/sub\u003e) were calculated. Student\u0026rsquo;s t-test or Mann-Whitney U test were performed to compare the differences in the aforementioned ADC parameters between different tumor stages. The diagnostic efficacy of individual ADC and combined ADC parameters was evaluated using logistic regression analysis and receiver operating characteristic (ROC) analysis to predict tumor stages.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTumors with pT\u003csub\u003e3\u0026ndash;4\u003c/sub\u003e stage demonstrated significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e compared to those with pT\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage; tumors with pN\u003csub\u003e1\u0026ndash;2\u003c/sub\u003e stage exhibited significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e compared to those with pN\u003csub\u003e0\u003c/sub\u003e stage; and cases with lymph node metastasis (LNM) showed significantly lower values of ADC\u003csub\u003et\u003c/sub\u003e, ADC\u003csub\u003et/dta\u003c/sub\u003e, and ADC\u003csub\u003et/dtd\u003c/sub\u003e compared to those without LNM (all \u003cem\u003eP\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Area under the ROC curves (AUC) of the combination involving ADC\u003csub\u003et\u003c/sub\u003e and ADC\u003csub\u003et/dta\u003c/sub\u003e was higher than that of individual ADC parameters when assessing pT stage, pN stage, and LNM.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe ADC parameters of tumor and distal paracancerous tissues could be somewhat helpful in preoperatively assessing pT stage, pN stage, and LNM in RA.\u003c/p\u003e","manuscriptTitle":"Apparent diffusion coefficients of resectable rectal adenocarcinoma and distal paracancerous tissues derived from diffusion weighted imaging: association with tumor stage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 14:24:30","doi":"10.21203/rs.3.rs-7767461/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c77e4542-06cf-40b4-afe5-7b75b88f02ce","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:15:37+00:00","versionOfRecord":{"articleIdentity":"rs-7767461","link":"https://doi.org/10.1007/s42058-025-00213-z","journal":{"identity":"chinese-journal-of-academic-radiology","isVorOnly":false,"title":"Chinese Journal of Academic Radiology"},"publishedOn":"2026-01-06 15:58:25","publishedOnDateReadable":"January 6th, 2026"},"versionCreatedAt":"2025-10-20 14:24:30","video":"","vorDoi":"10.1007/s42058-025-00213-z","vorDoiUrl":"https://doi.org/10.1007/s42058-025-00213-z","workflowStages":[]},"version":"v1","identity":"rs-7767461","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7767461","identity":"rs-7767461","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}