06 December 2021: Database Analysis
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 InvolvementJaromir Kargol1ABCDEF*, Wojciech Rudnicki2CDE, Jakub Kenig3DE, Justyna Filipowska4BE, Ewa Kaznowska5BE, Tomasz Kluz6BE, Wiesław Guz4BE, Elżbieta Łuczyńska4ACDEF
Med Sci Monit 2021; 27:e934941
BACKGROUND: This retrospective study included 103 patients diagnosed with rectal adenocarcinoma at a single center in Poland who underwent preoperative diffusion-weighted magnetic resonance imaging (DWI) and aimed to determine whether the apparent diffusion coefficient (ADC) was an imaging marker for tumor invasion and regional lymph node involvement.
MATERIAL AND METHODS: We analyzed primary staging magnetic resonance examinations of the rectum of 103 consecutive patients with histologically proven non-mucinous adenocarcinoma who underwent surgical treatment. In 85 patients, surgery was preceded by long-course chemoradiotherapy (n=18) or short-course radiotherapy (n=67). The following DWI parameters were measured: ADC mean, minimum, maximum, and standard deviation in the region of interest (ADC SD-in-ROI). Values were compared between subgroups based on histological parameters from the report: tumor stage, lymph node stage, differentiation grade, the presence of extranodal tumor deposits, angioinvasion, and perineural invasion. Statistical analysis was performed using the Mann-Whitney U test and the unilateral t test.
RESULTS: ADC mean values were lower for cases in which postoperative histopathological examination lymph node invasion (P=0.04) and tumor deposits were found (P=0.04). Minimal ADC value was higher in cases in which tumor deposits were not found (P=0.009). ADC SD-in-ROI values were lower in cases in which lymph nodes invasion was confirmed (P=0.014). There were no statistically significant differences for other parameters.
CONCLUSIONS: The ADC values in pre-treatment DWI in patients with rectal adenocarcinoma were correlated with tumor invasion and regional lymph node metastases. Therefore, ADC values from the pre-treatment MRI may help plan adjuvant therapy in patients with rectal adenocarcinoma.
Keywords: Diffusion Magnetic Resonance Imaging, Rectal Neoplasms, Biomarkers, Tumor, Adenocarcinoma, Aged, Aged, 80 and over, Female, Humans, Lymph Nodes, Lymphatic Metastasis, Male, Middle Aged, Neoplasm Invasiveness, Rectum, Retrospective Studies
The incidence of rectal cancer is predicted to increase, both in men and women. This incidence is currently estimated at 125 000 cases per year (15–25 cases in a population of 100 000) in European Union countries . Basic diagnosis involves digital rectal examination followed by endoscopy with biopsy for histopathological confirmation. Other methods, including endorectal ultrasound (ERUS), magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET/CT), are applied in local and distant tumor staging . Both ERUS and MRI are useful for rectal cancer local staging. While ERUS is useful in treatment planning for early detected tumors, MRI has high accuracy in defining regional clinical staging of all rectal tumors . MRI is crucial in primary rectal cancer assessment because of its ability to provide high-resolution images of the tumor and other organs of the pelvis, including mesorectal fascia and peritoneal reflection for primary tumor (T) stage assessment and lymph node visualization for primary lymph node (N) staging . According to prospective multicenter study results, there are features of cancer aggressiveness that proved to predict outcome, including the circumferential resection margin, extramural vascular invasion (EMVI), depth of extramural invasion, extramural tumor deposits, mucin presence, and tumor regression grade to preoperative treatment [4,5]. The presence of these features influences overall and disease-free survival rates .
Histopathological examination remains the criterion standard in determining the effectiveness and completeness of treatment as well as in specifying important prognostic factors, and there are no imaging modalities available today that can determine the presence of prognostic factors identified in histopathological examination with 100% certainty .
However, the study conducted almost 20 years ago by Brown et al showed that some surgical and pathological prognostic risk factors can be accurately identified with rectal MRI . Technological development of MRI devices brings constant improvement in spatial resolution and signal contrast of new sequences, simultaneously reducing examination time because of shortened sequence duration . Newly designed sequences enable the obtainment of functional or structural data related to a specific tissue . A growing role of diffusion-weighted imaging (DWI), as a standard sequence in MRI of the pelvis, has been noted over the past years . This advanced technique, based on quantifying the movement of water molecules at the cellular level, had been a well-established complement to standard sequences in neurological MRI and is currently also applied in abdominopelvic imaging . In preoperative staging, DWI proved to be effective in detecting lymph nodes [11,12]. During post-radiation reassessment, DWI helps to determine the presence of residual tumor in fibrotic tissues . Over the years, the focus of the role of DWI has moved from the qualitative, visual assessment of rectal cancer for staging or treatment response toward quantitative assessment . Many publications have been devoted to the application of the main DWI measure, the apparent diffusion coefficient (ADC) [14,15].
Defining the factors that indicate a high risk of fast progression or low treatment responsiveness poses another challenge. The search for new markers which may facilitate infiltration character recognition, prediction of treatment response, recurrence risk, tendency to adjacent tissue invasion, and probability of distant metastasis is ongoing . The present study investigated the significance of ADC values as imaging markers to identify aggressive rectal cancer, defined as a tumor with metastatic potential (lymph node metastasis and tumor deposits in adjacent fat tissue), and evaluated whether ADC values contribute to predicting lymph node metastasis.
The quantification of rectal tumor diffusion by measuring the ADC has proven reliable as an imaging biomarker [17,18]. Sun et al evaluated ADC as a potential imaging biomarker that reflects the biological features of rectal cancer, such as tumor stage, extranodal tumor deposits, and pre-treatment CEA or CA19-9 levels . Curvo-Semedo et al  and Rao et al  also verified the usefulness of DWI in rectal cancer and evaluated whether ADC can be used as a noninvasive marker of tumor aggressiveness.
We conducted this study to determine if the ADC values of mean, minimum, maximum, and standard deviation in the region of interest (ADC SD-in-ROI) depend on the features defined in a histopathological examination of postoperative material, namely histological tumor and node stage, histological grade, the presence of extranodal tumor deposits, angioinvasion, perineural invasion, and the depth of mesorectal invasion for T3 tumors.
Our study is similar to previous studies; however, we conducted this study in a larger group of patients and measured the additional ADC values of minimum, maximum, and ADC SD-in-ROI. We performed our measurement manually, without additional software. Therefore, our observations can be easily and widely applied in clinical practice. In contrast to previous studies, we also checked if there is a relationship of ADC values with perineural invasion and the depth of mesorectal invasion of over 5 mm for stage T3 tumors.
This retrospective study included 103 patients diagnosed with rectal adenocarcinoma who underwent preoperative DWI at a single center in Poland and aimed to determine whether the ADC was an imaging marker for tumor invasion and regional lymph node involvement.
Material and Methods
This study was conducted in accordance with the Declaration of Helsinki. Ethics approval from the Bioethical Committee at the Regional Medical Chamber in Rzeszów was obtained on May 24, 2021. Informed consent was obtained from all participants involved in the study.
STUDY DESIGN AND PATIENT SELECTION:
This was a single-center retrospective study. Clinical and imaging data were retrieved from the patient database. MRI images were obtained from the picture archiving and communication system. The medical records of 205 patients who underwent an MRI examination of the rectum between 2014 and 2020 were analyzed. Patients with incomplete MRI data (motion artefacts, lack of DWI sequences) or histopathological analyses were excluded. A total of 112 consecutive patients diagnosed with rectal cancer by colon biopsy who were surgically treated and had available histopathological specimen analysis results were selected.
Rectal cancer was defined as cancer that arose below the sigmoid take-off and in the distal 15 cm of the intestinal tract, as measured to or from the anal verge. Patients with cancers other than adenocarcinoma (n=2) and rectosigmoid cancers (n=4) were excluded from the study. We also excluded 3 patients with mucinous adenocarcinoma because of the controversial use of DWI in mucinous tumors . Finally, statistical analysis was performed in the group of 103 consecutive patients with histologically proven non-mucinous adenocarcinoma of the rectum, including 64 men (62%) and 39 women (38%). Most patients were over 60 years old (71%), with a median age of 64 years (range, 39–84 years).
MAGNETIC RESONANCE IMAGING:
All patients underwent a primary staging MRI with a 1.5T MRI machine (Avanto, Siemens) using a phased-array body coil. The patients did not receive any bowel preparation. To reduce artefacts from peristaltic movement, an intravenous bolus injection of 20 mg of butylscopolamine was administered. The standard imaging protocol included 2-dimensional T2-weighted image (T2WI) fast spin-echo sequences in 3 orthogonal planes. The tumor axis was identified on the sagittal scan. The transverse images were angled perpendicularly, and the coronal images were parallel to the tumor axis. An axial echo-planar imaging DWI sequence was angled on the same plane as the transverse T2WI. The DWI sequence was performed with spectral attenuated inversion recovery fat suppression with b values of 0, 300, 700, and 1000 s/mm2; TR/TE of 6000/86 ms; number of slices 30 to 35; and slice thickness 5 mm. ADC maps were automatically generated by the operating system using a mono-exponential decay model including all 4 b values.
ADC VALUE MEASUREMENT:
The assessment of radiological images was done independently by 2 experienced radiologists and a radiology trainee. Medixant RadiAnt DICOM Viewer (version 2020.2.3) software was used. No additional specialized software was needed for our measurements. The readers were blinded to the patients’ clinical data and pathology report results. The following DWI parameters were measured: ADC mean, minimum, maximum, and SD-in-ROI. The interobserver agreement was very good, and the deviations in measured values between observers did not exceed 5%. The almost perfect agreement between radiologists using DWI was reported in the study by Rosa et al . To simplify the calculations and statistical analysis, the mean of the measured values were assumed.
T2WIs were used for anatomical reference. To measure the ADC mean, maximum, and SD-in-ROI values on an MRI, the round ROI of about 1 cm2 (26–28 px) was drawn within the inner border of the tumor on the single axial DWI ADC map. Radiologists selected the appropriate cross-section to fit the entire ROI circle within the tumor tissue and to achieve the lowest possible SD value. The process is presented in Figure 1, where MRI T2WI shows the thickened rectal wall in the axial and sagittal planes. Axial DWI b=1000 s/mm2 images and corresponding ADC maps show restriction of water diffusion, the sign of malignancy. The ROI is placed within the tumor tissue and the ADC values are shown.
The region of minimum ADC was visually determined as the brightest region of the tumor on the axial (b=1000 s/mm2) image and by radiologists and was covered with a round- or oval-shaped ROI. Axial T2WIs were used to confirm the location within the tumor borders. The software automatically mapped the ROI onto the corresponding ADC map for minimum ADC value reading. The b value of 1000 s/mm2 was the highest available value for the pre-defined study protocol for rectal for our MRI system. Figure 2 presents the ROI placed within the tumor tissue in the visually indicated brightest tumor region. Software mapped the ROI onto the ADC map. The location within the tumor was confirmed on the sagittal T2WI. The methods of measurement used in our study were similar to those used by other investigators [18,22].
Histological examination of the resected surgical specimens was used as the standard evaluation for confirmation of tumor type, tumor grade, and as part of the staging process. In each case, the pathology reports were reviewed to confirm the tumor (T) and node (N) stage, differentiation grade, peritumoral-intravascular cancer emboli, the presence of extranodal tumor deposits, angioinvasion, and perineural invasion. The pathological TN-metastasis (M) stage was determined according to the 8th American Joint Committee on Cancer, with the assessment of the depth of mesorectal infiltration (T3 substages). Patients with stage T3 were divided into 2 groups based on whether the depth of mesorectal invasion exceeds 5 mm (T3 a/b vs c/d). Subclassification of T3 rectal cancer was obtained from the European Society for Medical Oncology guidelines  but was not validated or incorporated in any TNM versions. Based on histopathological analysis, the rectal cancers were divided into well- (G1), moderately (G2), and poorly (G3) differentiated.
MRI results were compared with the histopathology results. Values were compared between subgroups based on the statistical analysis, which was performed with Statistica software (version 13.3, TIBCO Software Inc). Depending on the presence of a specific feature, patients were divided into subgroups. First, conformity of particular variables to a normal distribution was tested. Normality was verified with the Kolmogorov-Smirnov and Shapiro-Wilk tests. The results are presented in Table 1. If the distribution appeared to be not normal (P≤0.05), nonparametric methods were applied to test hypotheses (variable comparison). The Mann-Whitney U test was used to define the relationships between ADC minimal values, ADC SD-in-ROI, and selected parameters. Values were compared between subgroups based on histological parameters obtained from the report. The unilateral t test was used to determine the relationship between mean ADC values. Due to heterogeneity of variances in particular groups, to verify the hypothesis of the relationship of ADC mean values with a histopathological grade of lesion, the Kruskal-Wallis test was used as a condition for the application of variance analysis. Statistical significance was defined as a P≤0.05.
Rectal cancer was diagnosed and treated with primary or secondary surgery in 103 patients. The initial tumor stage on MRI was cT1–2 in 30 (29%) patients, cT3 in 56 patients (54%), and cT4 in 17 patients (17%). Thirty-eight patients (37%) had stage cN0 and 65 (63%) had cN+. Fourteen patients (14%) had distant metastases. The MRI presence of EMVI was observed in 33 (32%) patients.
PATIENTS TREATMENT AND HISTOPATHOLOGICAL RESULTS:
Within the group, 85 patients with non-locally advanced tumors underwent surgery without neoadjuvant treatment (33 patients) or, immediately after surgery, received a short course of radiotherapy 5×5 Gy (52 patients). Eighteen patients with locally advanced disease underwent a long course of conformal radiotherapy (28×1.8 Gy radiotherapy with 2×825 mg/m2/d capecitabine). All 103 patients included in the study underwent surgery: 44 patients underwent the Miles procedure and 57 underwent the Hartmann/Dixon procedure. Histopathological analysis revealed that 35 (34%) patients had grade G1, 61 (59%) patients had grade G2, and 7 (7%) patients had grade G3. Perineural invasion on histopathology was found in 31 (30%) patients. Angioinvasion was diagnosed in 32 (31%) patients. Positive lymph nodes were found in 42 (41%) patients, while tumor deposits were present in 33 (32%) patients. Cancer T stage was determined as pT1 in 5 (5%) patients, pT2 in 25 (24%) patients, pT3 in 59 (57%) patients, and the highest, pT4, in 14 (14%) patients. For pT3 patients, depth of mesorectal invasion exceeding 5 mm was diagnosed in 22 (21%) patients, while it was lower than 5 mm in 37 (36%) patients.
RELATIONSHIP OF ADC VALUES WITH HISTOPATHOLOGICAL FINDINGS:
The analysis revealed a statistically significant relationship in which ADC mean values were lower for patients in whom postoperative histopathological examination tumor deposits were found (unilateral
The ADC minimal value was higher when tumor deposits were found in postoperative specimens than when tumor deposits were not found (Mann-Whitney U test=2.625, median 564.50×10−3 mm2/s vs 521.00×10−3 mm2/s, P=0.009). Higher ADC minimal values were associated with a smaller probability of tumor deposit presence. A subsequent relationship observed was that ADC SD-in-ROI values were lower in patients in whom lymph node invasion was confirmed (Mann-Whitney U test=−2.460, median 95.00 vs 114.00, P=0.014). The relationships described above are presented in Figure 3A–3D.
There were no other statistically significant differences in ADC mean, maximum, minimum, and ADC SD-in-ROI values for other investigated parameters. We did not find a dependence between ADC values and lesion histopathological grade (Figure 4A, 4B).
Lower ADC mean values within a distinguished part of the tumor were related to the presence of histopathologic features considered as adverse prognostic factors. Such a relationship occurred with vascular invasion (angioinvasion diagnosed on histopathological examination and EMVI diagnosed on MRI) and the invasion of the mesorectum of over 5 mm beyond the rectal wall for T3 cancers. In patients with perineural invasion, ADC mean values and ADC minimal values were higher than in patients in whom such a feature was not found. However, the difference was not statistically significant.
Based on ROC analysis, it can be stated that the ADC mean value may be used for prediction of mesorectal invasion status and cancer stage pT1–2 vs pT3–4 (P=0.041). When the ADC mean value was below 776×10−3 mm2/s, cancers of a higher stage were recognized with 60% sensitivity, 67.2% specificity, and 64.1% accuracy, with an area under the ROC curve (AUC) of 0.615. Based on maximum and minimum ADC values, and in accordance with ROC analysis, verification of lesion malignancy degree was not possible (P>0.09). The results are presented in Table 2.
There are several limitations in our study. First, it was a single-center study conducted on a relatively small group of patients. For routine use, the results need to be confirmed in a larger group of patients. Second, the measurements were performed on a single slice of tumor. The evaluation of the whole tumor volume would provide higher accuracy and repeatability across centers. Although our measurement method was simple, widely available, and easy to implement, it was operator-dependent, and thus result bias is possible. To ensure reproducible results, the study should be performed with automated tools. Third, our study group was heterogeneous and comprised patients who varied in terms of sex, age, and T stage. In the future, it would be worth checking if the results are consistent in a selected group of patients. Fourth, our study was a retrospective design, and the data availability was limited. A prospective study would allow for more MRI sequences to be performed; for example, the DWI sequence in the coronal plane. Finally, the length of time between MRI and surgery varied among patients. Some patients underwent surgical treatment a few days after preoperative examination, whereas others underwent neoadjuvant radiotherapy or radiochemotherapy. Only a few patients had MRI examinations for restaging after neoadjuvant treatment; therefore, the data for assessing the relationship between ADC values and treatment response, for example, was not available.
The findings from this retrospective study from a single center in Poland showed that ADC values in pre-treatment DWI in patients with rectal adenocarcinoma were correlated with tumor invasion and regional lymph node metastases. Therefore, ADC values from pre-treatment MRI may help plan adjuvant therapy in patients with rectal adenocarcinoma.
FiguresFigure 1. Magnetic resonance (MRI) scans of a 57-year-old man with rectal cancer. A thickened rectal wall on (A) axial and (B) sagittal T2-weighted image (long arrows). High signal on (C) diffusion-weighted image b=1000 s/mm2 and low signal on (D) corresponding apparent diffusion coefficient (ADC) map indicates the presence of water diffusion restriction, the feature of malignancy (short arrows). (D) Region of interest (ROI) of about 1 cm2 is placed within the borders of the tumor on the ADC map (circle). Measurement of mean ADC value and in-ROI ADC standard deviation. Medixant, RadiAnt DICOM Viewer (version 2020.2.3). Figure 2. Magnetic resonance (MRI) scans in a 63-year-old woman with rectal cancer. A thickened rectal wall on (A) axial MRI T2-weighted image (arrow). High signal on (B) diffusion weighted image b=1000 s/mm2, and (C) low signal on corresponding apparent diffusion coefficient (ADC) map indicates the presence water diffusion restriction, the feature of malignancy. The visually determined brightest region within the tumor on (B) axial b=1000 s/mm2 image (the circle) and (C) the reading of minimum ADC value on corresponding ADC map in the region of interest (ROI) (black arrow). Medixant, RadiAnt DICOM Viewer (version 2020.2.3). Figure 3. Statistically significant relationship between (A) apparent diffusion coefficient (ADC) mean and the presence of tumor deposits, (B) ADC mean and lymph node metastases, (C) ADC minimum value and the presence of tumor deposits, and (D) standard deviation in region of interest (SD-in-ROI) and lymph nodes metastases. TIBCO Software Inc, Statistica (version 13.3). Figure 4. (A) The relationship between apparent diffusion coefficient (ADC) mean value and histopathological tumor grade: well- (G1), moderately (G2), and poorly (G3) differentiated and (B) the relationship between ADC minimum values and histopathological tumor grade. TIBCO Software Inc, Statistica (version 13.3).
TablesTable 1. Conformity of particular variables to normal distribution. Apparent diffusion coefficient, the standard deviation in the region of interest. Microsoft Corporation, Microsoft Word 2013 (version 15.0.5389.1000). Table 2. Sensitivity, specificity, and accuracy with different apparent diffusion coefficient parameters and values and the respective area under curve. Microsoft Corporation, Microsoft Word 2013 (version 15.0.5389.1000).
1. Glynne-Jones R, Wyrwicz L, Tiret E, Rectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up [published erratum appears in Ann Oncol. 2018;29(Suppl. 4):iv263]: Ann Oncol, 2017; 28(Suppl 4); iv22-iv40
2. Balyasnikova S, Brown G, Optimal imaging strategies for rectal cancer staging and ongoing management: Curr Treat Options Oncol, 2016; 17(6); 32
3. Kaur H, Choi H, You YN, MR imaging for preoperative evaluation of primary rectal cancer: Practical considerations: Radiographics, 2012; 32(2); 389-409
4. Taylor FG, Quirke P, Heald RJ, Preoperative magnetic resonance imaging assessment of circumferential resection margin predicts disease-free survival and local recurrence: 5-year follow-up results of the MERCURY study: J Clin Oncol, 2014; 32(1); 34-43
5. Smith NJ, Barbachano Y, Norman AR, Prognostic significance of magnetic resonance imaging-detected extramural vascular invasion in rectal cancer: Br J Surg, 2008; 95(2); 229-36
6. Canbey Göret C, Göret NE, Histopathological analysis of 173 consecutive patients with colorectal carcinoma: A pathologist’s view: Med Sci Monit, 2018; 24; 6809-15
7. Brown G, Radcliffe AG, Newcombe RG, Preoperative assessment of prognostic factors in rectal cancer using high-resolution magnetic resonance imaging: Br J Surg, 2003; 90(3); 355-64
8. Cotten A, Kermarrec E, Moraux A, New MRI sequences: Joint Bone Spine, 2009; 76(6); 588-90
9. Beets-Tan RGH, Lambregts DMJ, Maas M, Magnetic resonance imaging for clinical management of rectal cancer: Updated recommendations from the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus meeting [published erratum appears in Eur Radiol. 2018;28(6):2711]: Eur Radiol, 2018; 28(4); 1465-75
10. Boone D, Taylor SA, Halligan S, Diffusion weighted MRI: Overview and implications for rectal cancer management: Colorectal Dis, 2013; 15(6); 655-61
11. Mizukami Y, Ueda S, Mizumoto A, Diffusion-weighted magnetic resonance imaging for detecting lymph node metastasis of rectal cancer: World J Surg, 2011; 35(4); 895-99
12. Yasui O, Sato M, Kamada A, Diffusion-weighted imaging in the detection of lymph node metastasis in colorectal cancer: Tohoku J Exp Med, 2009; 218(3); 177-83
13. Schurink NW, Lambregts DMJ, Beets-Tan RGH, Diffusion-weighted imaging in rectal cancer: Current applications and future perspectives: Br J Radiol, 2019; 92(1096); 20180655
14. Nerad E, Delli Pizzi A, Lambregts DMJ, The Apparent Diffusion Coefficient (ADC) is a useful biomarker in predicting metastatic colon cancer using the ADC-value of the primary tumor: PLoS One, 2019; 14(2); e0211830
15. Delli Pizzi A, Cianci R, Genovesi D, Performance of diffusion-weighted magnetic resonance imaging at 3.0T for early assessment of tumor response in locally advanced rectal cancer treated with preoperative chemoradiation therapy: Abdom Radiol (NY), 2018; 43(9); 2221-30
16. Maguire A, Sheahan K, Controversies in the pathological assessment of colorectal cancer: World J Gastroenterol, 2014; 20(29); 9850-61
17. Sun Y, Tong T, Cai S, Apparent Diffusion Coefficient (ADC) value: A potential imaging biomarker that reflects the biological features of rectal cancer: PLoS One, 2014; 9(10); e109371
18. Curvo-Semedo L, Lambreqts DM, Mass M, Diffusion-weight MRI in rectal cancer: Apparent diffusion coefficient as a potential noninvasive marker of tumor aggressiveness: J Magn Reson Imaging, 2012; 35; 1365-67
19. Rao SX, Zeng MS, Chen CZ, The value of diffusion-weighted imaging in combination with T2-weighted imaging for rectal cancer detection: Eur J Radiol, 2008; 65(2); 299-303
20. Nasu K, Kuroki Y, Minami M, Diffusion-weighted imaging findings of mucinous carcinoma arising in the ano-rectal region: Comparison of apparent diffusion coefficient with that of tubular adenocarcinoma: Jpn J Radiol, 2012; 30(2); 120-27
21. Rosa C, Caravatta L, Delli Pizzi A, Reproducibility of rectal tumor volume delineation using diffusion-weighted MRI: Agreement on volumes between observers: Cancer Radiother, 2019; 23(3); 216-21
22. Lambregts DMJ, Beets GL, Maas M, Tumour ADC measurements in rectal cancer: Effect of ROI methods on ADC values and interobserver variability: Eur Radiol, 2011; 21; 2567-74
23. Lu W, Jing H, Ju-Mei Z, Intravoxel incoherent motion diffusion-weighted imaging for discriminating the pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: Sci Rep, 2017; 7(1); 8496
24. Kim JH, Beets GL, Kim MJ, High-resolution MR imaging for nodal staging in rectal cancer: Are there any criteria in addition to the size?: Eur J Radiol, 2004; 52(1); 78-83
25. Haak HE, Maas M, Lahaye MJ, Selection of patients for organ preservation after chemoradiotherapy: MRI identifies poor responders who can go straight to surgery: Ann Surg Oncol, 2020; 27(8); 2732-39
26. Cianci R, Cristel G, Agostini A, MRI for rectal cancer primary staging and restaging after neoadjuvant chemoradiation therapy: How to do it during daily clinical practice: Eur J Radiol, 2020; 131; 109238
27. Lu ZH, Hu CH, Qian WX, Preoperative diffusion-weighted imaging value of rectal cancer: Preoperative T staging and correlations with histological T stage: Clin Imaging, 2016; 40(3); 563-68
28. Ichikawa T, Erturk SM, Motosugi U, High-B-value diffusion-weighted MRI in colorectal cancer: Am J Roentgenol, 2006; 187(1); 181-84
29. Peng Y, Tang H, Meng X, Histological grades of rectal cancer: Whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging: Quant Imaging Med Surg, 2020; 10(1); 243-56
30. Delli Pizzi A, Caposiena D, Mastrodicasa D, Tumor detectability and conspicuity comparison of standard b1000 and ultrahigh b2000 diffusion-weighted imaging in rectal cancer: Abdom Radiol (NY), 2019; 44(11); 3595-605
31. Roth Y, Tichler T, Kostenich G, High-b-value diffusion-weighted MR imaging for pretreatment prediction and early monitoring of tumor response to therapy in mice: Radiology, 2004; 232(3); 685-92
32. Chen XL, Chen GW, Pu H, DWI and T2-Weighted MRI volumetry in resectable rectal cancer: Correlation with lymphovascular invasion and lymph node metastases: Am J Roentgenol, 2019 [Online ahead of print]
33. Nougaret S, Vargas HA, Lakhman Y, Intravoxel incoherent motion-derived histogram metrics for assessment of response after combined chemotherapy and radiation therapy in rectal cancer: Initial experience and comparison between single-section and volumetric analyses: Radiology, 2016; 280(2); 446-54
19 January 2023 : Clinical ResearchEvaluation of Health-Related Quality of Life and Mental Health in 729 Medical Students in Indonesia During ...
Med Sci Monit In Press; DOI: 10.12659/MSM.938892
19 January 2023 : Clinical ResearchDetermining the Impact of the COVID-19 Pandemic on Dental Care in the Serbian Adult Population: An Online Q...
Med Sci Monit 2023; 29:e939238
27 December 2022 : Clinical ResearchEffect of Physiotherapy to Correct Rounded Shoulder Posture in 30 Patients During the COVID-19 Pandemic in ...
Med Sci Monit 2022; 28:e938926
06 Feb 2023 : Clinical ResearchDouble C-Arm Digital Subtraction Angiography Guidance During Transjugular Intrahepatic Portosystemic Shunt ...
Med Sci Monit In Press; DOI: 10.12659/MSM.938912
06 Feb 2023 : Review articleEvolution of Hybrid Intelligence and Its Application in Evidence-Based Medicine: A Review
Med Sci Monit In Press; DOI: 10.12659/MSM.939366
03 Feb 2023 : Clinical ResearchTreatment of Gingival Recession Defects with Pouch and Tunnel Technique Using Connective Tissue Graft and L...
Med Sci Monit In Press; DOI: 10.12659/MSM.938865
Most Viewed Current Articles
13 Nov 2021 : Clinical ResearchAcceptance of COVID-19 Vaccination and Its Associated Factors Among Cancer Patients Attending the Oncology ...
Med Sci Monit 2021; 27:e932788
30 Dec 2021 : Clinical ResearchRetrospective Study of Outcomes and Hospitalization Rates of Patients in Italy with a Confirmed Diagnosis o...
Med Sci Monit 2021; 27:e935379
08 Mar 2022 : Review articleA Review of the Potential Roles of Antioxidant and Anti-Inflammatory Pharmacological Approaches for the Man...
Med Sci Monit 2022; 28:e936292