Objectives:

The study aimed to retrospectively investigate the apparent diffusion coefficient (ADC) of primary cervical cancer to examine the recurrence correlations in patients treated with radiotherapy (RT).

Methods:

The ADC of 31 patients with cervical cancer treated with RT were analyzed as possible risk factors for recurrence. A receiver operating characteristic (ROC) curve of the mean ADC (ADCmean) for the recurrence was generated to determine the cut-off value that yielded optimal sensitivity and specificity. The patient population was subdivided according to the risk factors for recurrence, and the disease-free survival (DFS) was analyzed. The following were investigated to explore the risk factors for recurrence: age, performance status, stage, pelvic lymph node metastasis, histologic tumor grade, maximal diameter of the primary tumor, chemotherapy, and ADCmean.

Results:

The median follow-up duration of the patients was 25 months. The recurrence was recognized in 9 (29%) of the 31 cases. The ROC analysis of recurrence showed that the area under the ADCmean curve was 0.889 (95% CI, 0.771–1.000; p = 0.001). The cut-off value of ADC mean was 0.900 × 10− 3 mm2/s, with a sensitivity of 86.4% and a specificity of 88.9%. By univariate analysis, the ADCmean was the only factor significantly associated with recurrence.

Conclusion:

The ADCmean of the primary tumor is a potential predictive factor for the recurrence in of cervical cancer.

Advances in knowledge:

The ADCmean of the primary tumor is a predictor of recurrence in patients with pre-treatment cervical cancer evaluation.

Introduction

Cervical cancer is the second most common gynecological malignancy.1 The International Federation of Gynecology and Obstetrics (FIGO) reported that a 5 year recurrence rate of 28% and an overall mortality rate of 27.8% for females with cervical cancer.2 Depending on the FIGO stage and histological subtype, the primary treatment consists of surgery, radiotherapy (RT), chemotherapy, or concurrent chemoradiation therapy. RT consisting of external-beam RT (EBRT), cisplatin-based chemotherapy, and intracavitary brachytherapy is the recommended standard treatment for locally advanced cervical cancer.3 However, a substantial number of patients experience locoregional recurrence or distant metastasis despite treatment.4,5 Poor prognostic factors for cervical cancer include pelvic lymph node metastasis, parametrial involvement, positive surgical margins, large tumor diameter, deep stromal invasion and the presence of tumor in capillary lymphatic spaces.6 However, these parameters are not sufficient to accurately predict prognosis. It is now accepted that new approaches to cervical cancer are pivotal to improving this disease’s prognosis.

MRI has an essential role in diagnosing cervical cancer, particularly for local staging. Diffusion-weighted imaging (DWI) is a functional imaging technique that analyzes differences in extracellular water proton movement, allowing for discrimination between tissues with varying cellularity.7 Additionally, this technique allows quantification of diffusion by calculating the apparent diffusion coefficient (ADC) values. In malignant tumors, the increased cellular density restricts water diffusion in the interstitial space, thus, lowering the ADC. Some studies showed that low ADC values are related with recurrence and a poor survival rate,8,9 while some found low ADC values in patients with good treatment responses.10,11 Other studies concluded that there is insufficient evidence to use pre-treatment ADC to predict the treatment efficacy.12–14 Therefore, it has been suggested that the ADC may provide useful information on tumor cellularity, tumor aggressiveness, and subtype characterization.15–18

In this study, we investigated the ADC of primary squamous cell cervical cancer to examine its correlation to recurrence in patients treated with RT.

Methods and materials

Study design and patients

From May 2012 to December 2019, 41 consecutive patients with pathologically diagnosed squamous cell uterine cervical cancer were treated with definitive RT at Tokyo Medical University Hachioji Medical Center. All patients provided written informed consent, and the Ethical Review Board approved this study of the authors' institution. Of the 41 patients, 31 patients who underwent MRI taken by the same machine within 30 days prior to the start of treatment were selected in this retrospective analysis. No patients enrolled in this study received any neoadjuvant chemotherapy before RT.

Treatment

Three-dimensional conformal RT was planned and performed with the patient in the supine position. For treatment planning, all patients underwent pelvic CT at a 2.5 mm slice thickness. Typically, the patients underwent EBRT with a photon beam of 10 MV. RT consisted of a combination of whole pelvic (WP) EBRT and high-dose-rate intracavitary brachytherapy (HDR-ICBT). WP-EBRT was delivered for 5 days during a week to achieve a total dose of 50.4 Gy/28 fractions. The WP-EBRT was initially delivered without a midline block (MB) using a box technique. Subsequently, the next phase of WP-EBRT was administered through the same WP field with a MB width of 3 or 4 cm using anteroposterior opposite ports. The first HDR-ICBT was performed after the MB insertion. HDR-ICBT was performed once a week with a fraction dose of 6 Gy prescribed at point A using Ir-192 afterloading machines. HDR-ICBT was not allowed on the same day as the EBRT. The relationship between RT schedule and patient’s stage was shown in Table 1. The cumulative linear quadratic equivalent doses (EQD2)19 at point A, which were the summation of the EBRT doses without the MB and HDR-ICBT doses. For patients who had an inadequate response to EBRT or failed tandem insertion, additional WP-EBRT without the MB was allowed to a total dose of 50.4 Gy. The total HDR-ICBT dose was 12 Gy per 2 fractions at point A.

Table 1.

The relationship between RT schedule and patients’ stage

EBRTHDR-ICBTTotal EQD2 at point APatients’ stage
WPWP (MB)
30.6 Gy/17 Fr19.8 Gy/11 Fr24 Gy/4 Fr62 GyStage Ib/IIb
39.6 Gy/22 Fr10.8 Gy/6 Fr18 Gy/3 Fr63 GyStage IIIa/IVA
50.4 Gy/28 Fr0 y12 Gy/2 Fr66 Gy
EBRTHDR-ICBTTotal EQD2 at point APatients’ stage
WPWP (MB)
30.6 Gy/17 Fr19.8 Gy/11 Fr24 Gy/4 Fr62 GyStage Ib/IIb
39.6 Gy/22 Fr10.8 Gy/6 Fr18 Gy/3 Fr63 GyStage IIIa/IVA
50.4 Gy/28 Fr0 y12 Gy/2 Fr66 Gy

EBRT, external-beam radiotherapy; EQD2, equivalent dose in 2 Gy per fraction; HDR-ICBT, high-dose-rate intracavitary brachytherapy; MB, midline block; WP, whole pelvic radiotherapy.

Table 1.

The relationship between RT schedule and patients’ stage

EBRTHDR-ICBTTotal EQD2 at point APatients’ stage
WPWP (MB)
30.6 Gy/17 Fr19.8 Gy/11 Fr24 Gy/4 Fr62 GyStage Ib/IIb
39.6 Gy/22 Fr10.8 Gy/6 Fr18 Gy/3 Fr63 GyStage IIIa/IVA
50.4 Gy/28 Fr0 y12 Gy/2 Fr66 Gy
EBRTHDR-ICBTTotal EQD2 at point APatients’ stage
WPWP (MB)
30.6 Gy/17 Fr19.8 Gy/11 Fr24 Gy/4 Fr62 GyStage Ib/IIb
39.6 Gy/22 Fr10.8 Gy/6 Fr18 Gy/3 Fr63 GyStage IIIa/IVA
50.4 Gy/28 Fr0 y12 Gy/2 Fr66 Gy

EBRT, external-beam radiotherapy; EQD2, equivalent dose in 2 Gy per fraction; HDR-ICBT, high-dose-rate intracavitary brachytherapy; MB, midline block; WP, whole pelvic radiotherapy.

Weekly cisplatin at a dose of 40 mg/m2 was administered for five courses during the RT period. Of the 31 patients, 26 (84%) received concurrent cisplatin chemotherapy, however the remaining 5 (16%) patients did not receive concurrent chemotherapy due to the low stage or the presence of comorbidities.

MRI technique and image analysis

MRI was performed using a 1.5 T MR system (Magnetom Avanto; Siemens, Erlangen, Germany) with a 6-channel phased-array coil. Routine pelvic MRIs were acquired as follows: sagittal T1 weighted fast spin-echo (FSE) images [repetition time (TR)/echo time (TE), 550/11 ms; flip angle, 180°; section thickness/intersection gap, 4/0.4 mm; a field of view (FOV), 250 × 250; matrix size, 230 × 384; the number of excitation, 4], and axial, sagittal, and coronal T2 weighted FSE images [TR/TE, 4000/84 ms; flip angle, 150°; section thickness/intersection gap, 4/0.4 mm; FOV, 250 × 250; matrix size, 230 × 384; the number of excitation, 4]. Axial DW images were then obtained. Imaging parameters for DW imaging were as follows: TR/TE, 4000/75; flip angle, 90°; section thickness/intersection gap, 4/0.4 mm; FOV, 280 × 280 matrix size, 128 × 128; bandwidth, 2170 Hz/pixel; the number of excitation, 4, using a chemical shift-selective fat suppression technique. The corresponding b-values to the diffusion sensitizing gradient were 0 and 1000 s/mm2. The ADC values were calculated from the regions of interest (ROIs) by dividing the signal intensity by 1000 to obtain ADC values × 10−3 mm2/s. The ROI placements and ADC calculations were made in the tangible portions of the primary tumor’s maximum sectional diameter, avoiding cystic or necrotic portions. Polygonal ROIs were placed manually on the maximum axial section of the primary tumor on the ADC map. The mean ADC value (ADCmean) of all full pixels within the ROI was obtained. One radiation oncologist with 17 years of experience drew all ROIs referencing the T2 weighted images. A typical ROI placement for a tumor is shown in Figure 1.

A typical ROI placement for tumors. (a) T2 weighted sagittal image. The white line is the reference line for the axial image on (b–d.) Axial image for T2 weighted and DW image, ADC map. ROIs were drawn manually along the edge of the lesions to cover as much tumor area as possible on a slice of the largest tumor area without excluding cystic or necrotic areas. ADC, apparent diffusion coefficient; DWI, diffusion-weighted imaging; ROI, region of interest
Figure 1.

A typical ROI placement for tumors. (a) T2 weighted sagittal image. The white line is the reference line for the axial image on (b–d.) Axial image for T2 weighted and DW image, ADC map. ROIs were drawn manually along the edge of the lesions to cover as much tumor area as possible on a slice of the largest tumor area without excluding cystic or necrotic areas. ADC, apparent diffusion coefficient; DWI, diffusion-weighted imaging; ROI, region of interest

Evaluation of the local response and toxicity

Local response was estimated by physical examination at 1 month after completing RT. The regular follow-up visits were performed at 2–3 month intervals for the first 2 years, then every 4–6 months after that, in the absence of clinical symptoms. At each follow-up visit, evaluation consisted of medical history, physical examination, Papanicolaou smear, ultrasonography, CT scans, and tumor marker assessment. The toxicity data were collected retrospectively from patient files. In evaluating the acute or late effect, toxicity criteria of the Common Terminology Criteria for Adverse Events v. 3.0 was used.

Statistical analyses

The endpoint was disease-free survival (DFS), which was defined as the time from the start of RT to clinical progression or death for any cause. Statistical analyses were performed using the Mann–Whitney U test to compare the recurrence and non-recurrence followed by Fisher’s protected least significance test for all pairwise comparisons. The ROC curve of the ADCmean for the recurrence was generated to determine the cut-off value that yielded optimal sensitivity and specificity. The patient population was subdivided according to the risk factors for recurrence. Moreover, the DFS was analyzed using the Kaplan–Meier method. The log-rank tests were used to examine the differences between the survival curves. The following were investigated: age, performance status, stage, pelvic lymph node metastasis, histologic tumor grade, maximal diameter of the primary tumor, concurrent cisplatin chemotherapy, and ADCmean to explore the risk factors for recurrence. Univariate logistic regression analyses were performed to evaluate the data using IBM SPSS Statistics 20.0 (SPSS, Armonk, NY). Multivariate analysis was not performed owing to the limited data. A two-sided p-value < 0.05 was considered statistically significant for all statistical tests.

Results

Patient outcomes

The patients and tumor characteristics are presented in Table 2. The patients' median age was 62 (range, 25–87) years. Of the total, 94% of patients had Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1. The FIGO system defined the patients’ stage as follows: three stage Ib1 cancers; one stage Ib2 cancers; two stage IIa1 cancers; 15 stage IIb cancers; one stage IIIa cancers; six stage IIIb cancer; and, three stage IVa cancers. Three patients (10%) had double cancers. The patients' median follow-up duration was 25 months (range, 8–93). Overall survival probabilities at 1 and 3 years were 100 and 90%, respectively (Figure 2a). Two (6%) patients were identified with a cancer-related death at 21 and 25 months after RT. DFS probabilities at 1 and 3 years were 77 and 69%, respectively (Figure 2b). The recurrence was recognized in 9 (29%) of the 31 cases; local failure only in 3 cases, and local failure and distant metastasis in 2, distant metastasis only in 4. The median time for recurrence was 6 months (range, 3–21) after RT initiation.

Table 2.

Patient and tumor characteristics

No. of patients31
Age (years), median (range)62 (25–87)
Performance status
 027
 12
 22
FIGO stage
 Ib13 (10)
 Ib21 (3)
 IIa12 (6)
 IIb15 (48)
 IIIa1 (3)
 IIIb6 (19)
 IVa3 (10)
Pelvic lymph node metastasis (percentage)
 Yes15 (48)
 No16 (52)
Histologic tumor grade (percentage)
 Well differentiated2 (6)
 Moderate differentiated22 (71)
 Poor differentiated7 (23)
Size of primary tumor (percentage)
 ≤4 cm7 (23)
 >4 cm24 (77)
Chemotherapy (percentage)
 Yes26 (84)
 No5 (16)
No. of patients31
Age (years), median (range)62 (25–87)
Performance status
 027
 12
 22
FIGO stage
 Ib13 (10)
 Ib21 (3)
 IIa12 (6)
 IIb15 (48)
 IIIa1 (3)
 IIIb6 (19)
 IVa3 (10)
Pelvic lymph node metastasis (percentage)
 Yes15 (48)
 No16 (52)
Histologic tumor grade (percentage)
 Well differentiated2 (6)
 Moderate differentiated22 (71)
 Poor differentiated7 (23)
Size of primary tumor (percentage)
 ≤4 cm7 (23)
 >4 cm24 (77)
Chemotherapy (percentage)
 Yes26 (84)
 No5 (16)
Table 2.

Patient and tumor characteristics

No. of patients31
Age (years), median (range)62 (25–87)
Performance status
 027
 12
 22
FIGO stage
 Ib13 (10)
 Ib21 (3)
 IIa12 (6)
 IIb15 (48)
 IIIa1 (3)
 IIIb6 (19)
 IVa3 (10)
Pelvic lymph node metastasis (percentage)
 Yes15 (48)
 No16 (52)
Histologic tumor grade (percentage)
 Well differentiated2 (6)
 Moderate differentiated22 (71)
 Poor differentiated7 (23)
Size of primary tumor (percentage)
 ≤4 cm7 (23)
 >4 cm24 (77)
Chemotherapy (percentage)
 Yes26 (84)
 No5 (16)
No. of patients31
Age (years), median (range)62 (25–87)
Performance status
 027
 12
 22
FIGO stage
 Ib13 (10)
 Ib21 (3)
 IIa12 (6)
 IIb15 (48)
 IIIa1 (3)
 IIIb6 (19)
 IVa3 (10)
Pelvic lymph node metastasis (percentage)
 Yes15 (48)
 No16 (52)
Histologic tumor grade (percentage)
 Well differentiated2 (6)
 Moderate differentiated22 (71)
 Poor differentiated7 (23)
Size of primary tumor (percentage)
 ≤4 cm7 (23)
 >4 cm24 (77)
Chemotherapy (percentage)
 Yes26 (84)
 No5 (16)
Overall survival and disease-free survival probabilities. (a) Overall survival probabilities at 1 and 3 years were 100 and 90%, respectively. Two (6%) were diagnosed identified as with a cancer-related death, at 21 and 25 months after the start of RT. (b) Disease-free survival probabilities at 1 and 3 years were 77 and 69%, respectively. The recurrence was recognized in 9 (29%) of the 31 cases.
Figure 2.

Overall survival and disease-free survival probabilities. (a) Overall survival probabilities at 1 and 3 years were 100 and 90%, respectively. Two (6%) were diagnosed identified as with a cancer-related death, at 21 and 25 months after the start of RT. (b) Disease-free survival probabilities at 1 and 3 years were 77 and 69%, respectively. The recurrence was recognized in 9 (29%) of the 31 cases.

Association between ADC mean and recurrence

The average values of ADCmean for the primary tumor of cervical cancer with recurrence and non-recurrence were found to be 0.840 ± 0.064×10−3 mm2/s and 0.949 ± 0.082×10−3 mm2/s, respectively. The difference in ADCmean between the two groups was statistically significant (p < 0.001), calculated with the Mann–Whitney U test. ROC analysis of recurrence showed that the area under the ADCmean curve was 0.889 (95% CI, 0.771–1.000; p = 0.001) (Figure 3). The cut-off value of ADCmean was 0.900 × 10− 3 mm2/s, with a sensitivity of 86.4% and a specificity of 88.9%.

Receiver operating characteristic analysis of recurrence The area under the curve for ADCmean was 0.889 (95% CI, 0.771–1.000; p = 0.001). The cut-off value of ADCmean was 0.900 × 10−3 mm2/s, with a sensitivity of 86.4% and a specificity of 88.9%. ADC, apparent diffusion coefficient CI, confidence interval.
Figure 3.

Receiver operating characteristic analysis of recurrence The area under the curve for ADCmean was 0.889 (95% CI, 0.771–1.000; p = 0.001). The cut-off value of ADCmean was 0.900 × 10−3 mm2/s, with a sensitivity of 86.4% and a specificity of 88.9%. ADC, apparent diffusion coefficient CI, confidence interval.

Univariate analyses

The relationships between the risk factors and recurrence are summarized in Table 3. By univariate analysis, the ADCmean was the only factor significantly associated with recurrence (p < 0.001), calculated with the log-rank test. The 2-year DFS probabilities for patients with cervical cancer of ADCmean ≥ 0.900×10−3 mm2/s and <0.900 ×10−3 mm2/s were 95 and 24%, respectively (Figure 4). The DFS probability between these patients was calculated using the log-rank test and was found to be statistically significant (p < 0.001). The relationships between the ADCmean and the other risk factors, calculated with the Mann–Whitney U test, are shown in Table 4. ADCmean had been not related with the other risk factors.

Table 3.

Risk factors associated with recurrence

Recurrence n = 9p-value
Age (≤60 y vs. >60 y)15% (2/13) vs 39% (7/18)0.168
PS (0 vs. ≥1)30% (8/27) vs 25% (1/4)0.989
FIGO stage (Ib1/IIb vs IIIa/IVa)33% (7/21) vs 20% (2/10)0.484
Histologic tumor grade (well/moderate vs poor)33% (8/24) vs 14% (1/7)0.384
Pelvic lymph node metastasis (negative vs positive)25% (4/16) vs 33% (5/15)0.581
Maximal diameter of primary tumor (<4 cm vs. ≥4 cm)29% (2/7) vs 29% (7/24)0.893
Concurrent cisplatin chemotherapy (negative vs positive)40% (2/5) vs 27% (7/26)0.556
ADCmean × 10−3 mm2/s (<0.900 vs.≥0.900)73% (8/11) vs 5% (1/20)<0.001
Recurrence n = 9p-value
Age (≤60 y vs. >60 y)15% (2/13) vs 39% (7/18)0.168
PS (0 vs. ≥1)30% (8/27) vs 25% (1/4)0.989
FIGO stage (Ib1/IIb vs IIIa/IVa)33% (7/21) vs 20% (2/10)0.484
Histologic tumor grade (well/moderate vs poor)33% (8/24) vs 14% (1/7)0.384
Pelvic lymph node metastasis (negative vs positive)25% (4/16) vs 33% (5/15)0.581
Maximal diameter of primary tumor (<4 cm vs. ≥4 cm)29% (2/7) vs 29% (7/24)0.893
Concurrent cisplatin chemotherapy (negative vs positive)40% (2/5) vs 27% (7/26)0.556
ADCmean × 10−3 mm2/s (<0.900 vs.≥0.900)73% (8/11) vs 5% (1/20)<0.001

ADC, apparent diffusion coefficient;FIGO, International Federation of Gynecology and Obstetrics; PS, performance status.

Table 3.

Risk factors associated with recurrence

Recurrence n = 9p-value
Age (≤60 y vs. >60 y)15% (2/13) vs 39% (7/18)0.168
PS (0 vs. ≥1)30% (8/27) vs 25% (1/4)0.989
FIGO stage (Ib1/IIb vs IIIa/IVa)33% (7/21) vs 20% (2/10)0.484
Histologic tumor grade (well/moderate vs poor)33% (8/24) vs 14% (1/7)0.384
Pelvic lymph node metastasis (negative vs positive)25% (4/16) vs 33% (5/15)0.581
Maximal diameter of primary tumor (<4 cm vs. ≥4 cm)29% (2/7) vs 29% (7/24)0.893
Concurrent cisplatin chemotherapy (negative vs positive)40% (2/5) vs 27% (7/26)0.556
ADCmean × 10−3 mm2/s (<0.900 vs.≥0.900)73% (8/11) vs 5% (1/20)<0.001
Recurrence n = 9p-value
Age (≤60 y vs. >60 y)15% (2/13) vs 39% (7/18)0.168
PS (0 vs. ≥1)30% (8/27) vs 25% (1/4)0.989
FIGO stage (Ib1/IIb vs IIIa/IVa)33% (7/21) vs 20% (2/10)0.484
Histologic tumor grade (well/moderate vs poor)33% (8/24) vs 14% (1/7)0.384
Pelvic lymph node metastasis (negative vs positive)25% (4/16) vs 33% (5/15)0.581
Maximal diameter of primary tumor (<4 cm vs. ≥4 cm)29% (2/7) vs 29% (7/24)0.893
Concurrent cisplatin chemotherapy (negative vs positive)40% (2/5) vs 27% (7/26)0.556
ADCmean × 10−3 mm2/s (<0.900 vs.≥0.900)73% (8/11) vs 5% (1/20)<0.001

ADC, apparent diffusion coefficient;FIGO, International Federation of Gynecology and Obstetrics; PS, performance status.

Disease-free survival probabilities associated with ADC mean The 2–year DFS probabilities for patients with cervical cancer of ADCmean ≥ 0.900×10−3 mm2/s and <0.900 ×10−3 mm2/s were 95 and 24%, respectively. DFS probability difference between these patients was calculated using the log–rank test and was found to be statistically significant (p < 0.001). ADC, apparent diffusion coefficient; DFS, disease-free survival
Figure 4.

Disease-free survival probabilities associated with ADC mean The 2–year DFS probabilities for patients with cervical cancer of ADCmean ≥ 0.900×10−3 mm2/s and <0.900 ×10−3 mm2/s were 95 and 24%, respectively. DFS probability difference between these patients was calculated using the log–rank test and was found to be statistically significant (p < 0.001). ADC, apparent diffusion coefficient; DFS, disease-free survival

Table 4.

Relationships between the ADC mean and the other risk factors

Median (range)ADC mean × 10−3 mm2/sp-value
Age0.779
 ≤60 y0.930 (0.692–1.018)
 >60 y0.943 (0.726–1.069)
PS0.616
 00.930 (0.692–1.069)
 ≥10.955 (0.831–1.000)
FIGO stage0.597
 Ib1/IIb0.930 (0.692–1.018)
 IIIa/IVa0.951 (0.726–1.069)
Histologic tumor grade0.171
 Well/moderate0.934 (0.692–1.069)
 Poor0.980 (0.834–1.058)
Pelvic lymph node metastasis0.635
 Negative0.943 (0.692–1.069)
 Positive0.930 (0.726–1.018)
Maximal diameter of primary tumor0.539
 <4 cm0.947 (0.692–1.069)
 ≥4 cm0.934 (0.726–1.058)
Median (range)ADC mean × 10−3 mm2/sp-value
Age0.779
 ≤60 y0.930 (0.692–1.018)
 >60 y0.943 (0.726–1.069)
PS0.616
 00.930 (0.692–1.069)
 ≥10.955 (0.831–1.000)
FIGO stage0.597
 Ib1/IIb0.930 (0.692–1.018)
 IIIa/IVa0.951 (0.726–1.069)
Histologic tumor grade0.171
 Well/moderate0.934 (0.692–1.069)
 Poor0.980 (0.834–1.058)
Pelvic lymph node metastasis0.635
 Negative0.943 (0.692–1.069)
 Positive0.930 (0.726–1.018)
Maximal diameter of primary tumor0.539
 <4 cm0.947 (0.692–1.069)
 ≥4 cm0.934 (0.726–1.058)

ADC, apparent diffusion coefficient;PS, performance status.

Table 4.

Relationships between the ADC mean and the other risk factors

Median (range)ADC mean × 10−3 mm2/sp-value
Age0.779
 ≤60 y0.930 (0.692–1.018)
 >60 y0.943 (0.726–1.069)
PS0.616
 00.930 (0.692–1.069)
 ≥10.955 (0.831–1.000)
FIGO stage0.597
 Ib1/IIb0.930 (0.692–1.018)
 IIIa/IVa0.951 (0.726–1.069)
Histologic tumor grade0.171
 Well/moderate0.934 (0.692–1.069)
 Poor0.980 (0.834–1.058)
Pelvic lymph node metastasis0.635
 Negative0.943 (0.692–1.069)
 Positive0.930 (0.726–1.018)
Maximal diameter of primary tumor0.539
 <4 cm0.947 (0.692–1.069)
 ≥4 cm0.934 (0.726–1.058)
Median (range)ADC mean × 10−3 mm2/sp-value
Age0.779
 ≤60 y0.930 (0.692–1.018)
 >60 y0.943 (0.726–1.069)
PS0.616
 00.930 (0.692–1.069)
 ≥10.955 (0.831–1.000)
FIGO stage0.597
 Ib1/IIb0.930 (0.692–1.018)
 IIIa/IVa0.951 (0.726–1.069)
Histologic tumor grade0.171
 Well/moderate0.934 (0.692–1.069)
 Poor0.980 (0.834–1.058)
Pelvic lymph node metastasis0.635
 Negative0.943 (0.692–1.069)
 Positive0.930 (0.726–1.018)
Maximal diameter of primary tumor0.539
 <4 cm0.947 (0.692–1.069)
 ≥4 cm0.934 (0.726–1.058)

ADC, apparent diffusion coefficient;PS, performance status.

Complications

Table 5 shows the acute and late complications of irradiation. 5 (25%) of 31 patients had Grade 2 acute diarrhea. One patient had Grade 2 late proctitis, and the other had Grade 2 hematuria. No patients showed Grade 3 or greater acute and late toxicities. The clinical data and risk factors for all cases are shown in Table 6.

Table 5.

Acute and late toxicities

Grade0 or 1234
Acute toxicities
 Cystitis31000
 Diarrhea26500
Late toxicities
 Proctitis30100
 Urinary retention31000
 Hematuria30100
Grade0 or 1234
Acute toxicities
 Cystitis31000
 Diarrhea26500
Late toxicities
 Proctitis30100
 Urinary retention31000
 Hematuria30100
Table 5.

Acute and late toxicities

Grade0 or 1234
Acute toxicities
 Cystitis31000
 Diarrhea26500
Late toxicities
 Proctitis30100
 Urinary retention31000
 Hematuria30100
Grade0 or 1234
Acute toxicities
 Cystitis31000
 Diarrhea26500
Late toxicities
 Proctitis30100
 Urinary retention31000
 Hematuria30100
Table 6.

The clinical data and risk factors for all cases

No.AgePSFIGO stageHistologic tumor gradePelvic lymph node metastasisMaximal diameter of the primary tumor (cm)Concurrent cisplatin chemotherapyADC mean × 10−3 mm2/sLocal controlLocal control duration (M)
16404amoderatepositive8.5negative0.987control31
26002bmoderatenegative4.3positive0.960control93
36504amoderatenegative4.4positive0.892recurrence5
47002bmoderatenegative4.1positive0.100control71
58203bmoderatenegative3positive0.107control66
67703bpoornegative4.6positive0.106control79
76402bwellnegative5.1positive0.965control71
85701b1moderatenegative2.2positive0.692control63
96603bmoderatepositive5positive0.939control38
103502bmoderatepositive6positive0.942control28
116203bwellpositive6positive0.726recurrence10
126302bmoderatenegative3.5positive0.989control44
136002bpoornegative4.8positive0.917control39
147003bmoderatepositive5positive0.828control41
154402bpoorpositive5.5positive0.980control40
166202bmoderatenegative5.8positive0.767recurrence21
173502bmoderatenegative5.4positive0.940control20
185703bpoornegative5.5positive0.843control28
195401b2moderatepositive3.7positive0.918recurrence6
207202bpoornegative4.2positive0.894recurrence3
218612bmoderatenegative3.2negative0.831recurrence19
222502bmoderatepositive6.8positive0.906control21
235701b1poorpositive2positive0.102control22
244702bmoderatepositive4.4positive0.805recurrence6
253302bpoorpositive6.1positive0.101control15
267201b1moderatepositive5.3negative0.855recurrence7
278512a1moderatenegative2.8negative0.947control16
287924amoderatepositive5.9negative0.963control14
298723amoderatenegative6positive0.100control8
305902bmoderatepositive4.7positive0.930control13
316702a1moderatepositive4.2positive0.870recurrence5
No.AgePSFIGO stageHistologic tumor gradePelvic lymph node metastasisMaximal diameter of the primary tumor (cm)Concurrent cisplatin chemotherapyADC mean × 10−3 mm2/sLocal controlLocal control duration (M)
16404amoderatepositive8.5negative0.987control31
26002bmoderatenegative4.3positive0.960control93
36504amoderatenegative4.4positive0.892recurrence5
47002bmoderatenegative4.1positive0.100control71
58203bmoderatenegative3positive0.107control66
67703bpoornegative4.6positive0.106control79
76402bwellnegative5.1positive0.965control71
85701b1moderatenegative2.2positive0.692control63
96603bmoderatepositive5positive0.939control38
103502bmoderatepositive6positive0.942control28
116203bwellpositive6positive0.726recurrence10
126302bmoderatenegative3.5positive0.989control44
136002bpoornegative4.8positive0.917control39
147003bmoderatepositive5positive0.828control41
154402bpoorpositive5.5positive0.980control40
166202bmoderatenegative5.8positive0.767recurrence21
173502bmoderatenegative5.4positive0.940control20
185703bpoornegative5.5positive0.843control28
195401b2moderatepositive3.7positive0.918recurrence6
207202bpoornegative4.2positive0.894recurrence3
218612bmoderatenegative3.2negative0.831recurrence19
222502bmoderatepositive6.8positive0.906control21
235701b1poorpositive2positive0.102control22
244702bmoderatepositive4.4positive0.805recurrence6
253302bpoorpositive6.1positive0.101control15
267201b1moderatepositive5.3negative0.855recurrence7
278512a1moderatenegative2.8negative0.947control16
287924amoderatepositive5.9negative0.963control14
298723amoderatenegative6positive0.100control8
305902bmoderatepositive4.7positive0.930control13
316702a1moderatepositive4.2positive0.870recurrence5

ADC, apparent diffusion coefficient; FIGO, The International Federation of Gynecology and Obstetrics; PS, performance status.

Table 6.

The clinical data and risk factors for all cases

No.AgePSFIGO stageHistologic tumor gradePelvic lymph node metastasisMaximal diameter of the primary tumor (cm)Concurrent cisplatin chemotherapyADC mean × 10−3 mm2/sLocal controlLocal control duration (M)
16404amoderatepositive8.5negative0.987control31
26002bmoderatenegative4.3positive0.960control93
36504amoderatenegative4.4positive0.892recurrence5
47002bmoderatenegative4.1positive0.100control71
58203bmoderatenegative3positive0.107control66
67703bpoornegative4.6positive0.106control79
76402bwellnegative5.1positive0.965control71
85701b1moderatenegative2.2positive0.692control63
96603bmoderatepositive5positive0.939control38
103502bmoderatepositive6positive0.942control28
116203bwellpositive6positive0.726recurrence10
126302bmoderatenegative3.5positive0.989control44
136002bpoornegative4.8positive0.917control39
147003bmoderatepositive5positive0.828control41
154402bpoorpositive5.5positive0.980control40
166202bmoderatenegative5.8positive0.767recurrence21
173502bmoderatenegative5.4positive0.940control20
185703bpoornegative5.5positive0.843control28
195401b2moderatepositive3.7positive0.918recurrence6
207202bpoornegative4.2positive0.894recurrence3
218612bmoderatenegative3.2negative0.831recurrence19
222502bmoderatepositive6.8positive0.906control21
235701b1poorpositive2positive0.102control22
244702bmoderatepositive4.4positive0.805recurrence6
253302bpoorpositive6.1positive0.101control15
267201b1moderatepositive5.3negative0.855recurrence7
278512a1moderatenegative2.8negative0.947control16
287924amoderatepositive5.9negative0.963control14
298723amoderatenegative6positive0.100control8
305902bmoderatepositive4.7positive0.930control13
316702a1moderatepositive4.2positive0.870recurrence5
No.AgePSFIGO stageHistologic tumor gradePelvic lymph node metastasisMaximal diameter of the primary tumor (cm)Concurrent cisplatin chemotherapyADC mean × 10−3 mm2/sLocal controlLocal control duration (M)
16404amoderatepositive8.5negative0.987control31
26002bmoderatenegative4.3positive0.960control93
36504amoderatenegative4.4positive0.892recurrence5
47002bmoderatenegative4.1positive0.100control71
58203bmoderatenegative3positive0.107control66
67703bpoornegative4.6positive0.106control79
76402bwellnegative5.1positive0.965control71
85701b1moderatenegative2.2positive0.692control63
96603bmoderatepositive5positive0.939control38
103502bmoderatepositive6positive0.942control28
116203bwellpositive6positive0.726recurrence10
126302bmoderatenegative3.5positive0.989control44
136002bpoornegative4.8positive0.917control39
147003bmoderatepositive5positive0.828control41
154402bpoorpositive5.5positive0.980control40
166202bmoderatenegative5.8positive0.767recurrence21
173502bmoderatenegative5.4positive0.940control20
185703bpoornegative5.5positive0.843control28
195401b2moderatepositive3.7positive0.918recurrence6
207202bpoornegative4.2positive0.894recurrence3
218612bmoderatenegative3.2negative0.831recurrence19
222502bmoderatepositive6.8positive0.906control21
235701b1poorpositive2positive0.102control22
244702bmoderatepositive4.4positive0.805recurrence6
253302bpoorpositive6.1positive0.101control15
267201b1moderatepositive5.3negative0.855recurrence7
278512a1moderatenegative2.8negative0.947control16
287924amoderatepositive5.9negative0.963control14
298723amoderatenegative6positive0.100control8
305902bmoderatepositive4.7positive0.930control13
316702a1moderatepositive4.2positive0.870recurrence5

ADC, apparent diffusion coefficient; FIGO, The International Federation of Gynecology and Obstetrics; PS, performance status.

Discussion

In the present study, the average values of ADCmean for the primary tumor of the cervical cancer with the recurrence and non-recurrence were found to be 0.840 ± 0.064×10–3mm2/s and 0.949 ± 0.082×10–3 mm2/s, respectively. The difference in ADCmean between the two groups was statistically significant (p < 0.001). Additionally, the 2-year DFS probabilities for patients with cervical cancer of ADCmean ≥ 0.900×10–3 mm2/s and <0.900 ×10–3 mm2/s were 95% and 24%, respectively (Figure 3). The difference in the DFS probability between patients with cervical cancer of ADCmean ≥ 0.900×10–3 mm2/s and <0.900 ×10–3 mm2/s, calculated using the log–rank test, was statistically significant (p < 0.001).

Although RT is the optimal therapy for cervical cancer with an appreciable outcome, treatment for a tumor relapse remains tough. Thus, we consider it clinically essential to find patients with a high-risk for recurrence within a short time and who might benefit from additional or novel therapies, such as targeted agents with chemotherapy or adjuvant consolidation chemotherapy after RT.20,21 In previous studies, the stage, tumor size, histological type, histological grade, presence of lymphovascular space invasion and metastasis to regional lymph nodes at the time of treatment have been reported to be significant prognostic factors for cervical cancer.22–24 However, these parameters are not sufficient to accurately predict prognosis. It is challenging to predict the prognosis of patients treated with RT without performing histopathological retrieval. Therefore, additional markers would help determine a patient’s risk of recurrence or death. It is now accepted that new approaches for pre-treatment of cervical cancers are pivotal to further the disease’s favorable prognosis.

Quantitative assessment is possible by calculating the ADC, which is measured by DWI.25 It has been suspected that the decreased ADC values in malignant tumors may be caused by their increased tissue cellularity or cell density, larger nuclei with more abundant macromolecular proteins, and less extracellular space.26–28Table 7 summarizes published reports of the risk factor for primary cervical cancer recurrence associated with ADC. A few previous studies have reported that DWI has the potential for predicting disease control or survival in cervical cancer patients treated with curative intent.11,29–34 Payne et al reported that the ADC values are expected to decrease when considering increasing tumor grades, as higher-grade tumors typically have a higher cellular density, resulting in restricted water diffusion in cervical cancer. Lower pre-treatment ADC values were associated with worse DFS in early-stage cervical cancer patients treated mostly with surgery.11 Regarding patients treated with RT, a previous study demonstrated that a lower pre-treatment 95th percentile ADC was associated with worse DFS.34 Ho et al found that pre-treatment ADC was an independent predictor of DFS in cervical cancer patients treated with RT.32 Onal et al demonstrated that pre-treatment ADC in cervical cancer patients treated with RT was an independent prognostic factor for DFS and OS.29 Although several values of ADC have been used for prognostic factors in cervical cancer, the complicated calculation methods were used for some factors. The method of calculation for prognostic factors should be possibly uncomplicated in daily clinical task. We consider that the measurement of ADCmean was uncomplicated method, and ADCmean was appropriate for prognostic factors in cervical cancer.

Table 7.

The summary for published reports of the risk factor for primary cervical cancer recurrence associated with ADC

Firsrt AuthorPt NoMedian follow-upTiming of MRIHistologyEndpointPrognostic factorcut-off valuep
Nakamura K (36)80pts32.0MPretreatmentSquamous cell carcinoma, allDFSADCmean0.852 × 10−3 mm2/s<0.001
ADCmin0.670 × 10−3 mm2/s0.0210
Onal C (29)44pts25.0MPretreatment PosttreatmentSquamous cell carcinoma, allDFS OSADCmeanDFS, 0.878 × 10−3 mm2/s0.006
OS, 0.878 × 10−3 mm2/s0.006
Park JJ (31)67pts32.4MPretreatment During treatmentSquamous cell carcinoma, 59pts Non-Squamous cell carcinoma, 8ptsDFSPre - during treatment /pretreatment ADCmean x 10035.1%<0.001
Gu KW (33)124pts43.5MPretreatment PosttreatmentSquamous cell carcinoma, 103pts Adenocarcinoma/other, 21ptsDFS CSS OSPost - pretreatment /pretreatment ADCmean x 100DFS, 27.8%0.001
CSS, 16.1%0.002
OS, 16.1%<0.001
Ho JC (32)69pts16.7MPretreatmentSquamous cell carcinoma, 48pts Adenocarcinoma/other, 21ptsDFSADCmean0.940 × 10−3 mm2/s0.02
Our study31pts25MPretreatmentSquamous cell carcinoma, allDFSADCmean0.900 × 10−3 mm2/s<0.001
Firsrt AuthorPt NoMedian follow-upTiming of MRIHistologyEndpointPrognostic factorcut-off valuep
Nakamura K (36)80pts32.0MPretreatmentSquamous cell carcinoma, allDFSADCmean0.852 × 10−3 mm2/s<0.001
ADCmin0.670 × 10−3 mm2/s0.0210
Onal C (29)44pts25.0MPretreatment PosttreatmentSquamous cell carcinoma, allDFS OSADCmeanDFS, 0.878 × 10−3 mm2/s0.006
OS, 0.878 × 10−3 mm2/s0.006
Park JJ (31)67pts32.4MPretreatment During treatmentSquamous cell carcinoma, 59pts Non-Squamous cell carcinoma, 8ptsDFSPre - during treatment /pretreatment ADCmean x 10035.1%<0.001
Gu KW (33)124pts43.5MPretreatment PosttreatmentSquamous cell carcinoma, 103pts Adenocarcinoma/other, 21ptsDFS CSS OSPost - pretreatment /pretreatment ADCmean x 100DFS, 27.8%0.001
CSS, 16.1%0.002
OS, 16.1%<0.001
Ho JC (32)69pts16.7MPretreatmentSquamous cell carcinoma, 48pts Adenocarcinoma/other, 21ptsDFSADCmean0.940 × 10−3 mm2/s0.02
Our study31pts25MPretreatmentSquamous cell carcinoma, allDFSADCmean0.900 × 10−3 mm2/s<0.001

ADC, apparent diffusion coefficient; CSS, cancer Specific Survival; DFS, disease-free survival; OS, overall survival.

Table 7.

The summary for published reports of the risk factor for primary cervical cancer recurrence associated with ADC

Firsrt AuthorPt NoMedian follow-upTiming of MRIHistologyEndpointPrognostic factorcut-off valuep
Nakamura K (36)80pts32.0MPretreatmentSquamous cell carcinoma, allDFSADCmean0.852 × 10−3 mm2/s<0.001
ADCmin0.670 × 10−3 mm2/s0.0210
Onal C (29)44pts25.0MPretreatment PosttreatmentSquamous cell carcinoma, allDFS OSADCmeanDFS, 0.878 × 10−3 mm2/s0.006
OS, 0.878 × 10−3 mm2/s0.006
Park JJ (31)67pts32.4MPretreatment During treatmentSquamous cell carcinoma, 59pts Non-Squamous cell carcinoma, 8ptsDFSPre - during treatment /pretreatment ADCmean x 10035.1%<0.001
Gu KW (33)124pts43.5MPretreatment PosttreatmentSquamous cell carcinoma, 103pts Adenocarcinoma/other, 21ptsDFS CSS OSPost - pretreatment /pretreatment ADCmean x 100DFS, 27.8%0.001
CSS, 16.1%0.002
OS, 16.1%<0.001
Ho JC (32)69pts16.7MPretreatmentSquamous cell carcinoma, 48pts Adenocarcinoma/other, 21ptsDFSADCmean0.940 × 10−3 mm2/s0.02
Our study31pts25MPretreatmentSquamous cell carcinoma, allDFSADCmean0.900 × 10−3 mm2/s<0.001
Firsrt AuthorPt NoMedian follow-upTiming of MRIHistologyEndpointPrognostic factorcut-off valuep
Nakamura K (36)80pts32.0MPretreatmentSquamous cell carcinoma, allDFSADCmean0.852 × 10−3 mm2/s<0.001
ADCmin0.670 × 10−3 mm2/s0.0210
Onal C (29)44pts25.0MPretreatment PosttreatmentSquamous cell carcinoma, allDFS OSADCmeanDFS, 0.878 × 10−3 mm2/s0.006
OS, 0.878 × 10−3 mm2/s0.006
Park JJ (31)67pts32.4MPretreatment During treatmentSquamous cell carcinoma, 59pts Non-Squamous cell carcinoma, 8ptsDFSPre - during treatment /pretreatment ADCmean x 10035.1%<0.001
Gu KW (33)124pts43.5MPretreatment PosttreatmentSquamous cell carcinoma, 103pts Adenocarcinoma/other, 21ptsDFS CSS OSPost - pretreatment /pretreatment ADCmean x 100DFS, 27.8%0.001
CSS, 16.1%0.002
OS, 16.1%<0.001
Ho JC (32)69pts16.7MPretreatmentSquamous cell carcinoma, 48pts Adenocarcinoma/other, 21ptsDFSADCmean0.940 × 10−3 mm2/s0.02
Our study31pts25MPretreatmentSquamous cell carcinoma, allDFSADCmean0.900 × 10−3 mm2/s<0.001

ADC, apparent diffusion coefficient; CSS, cancer Specific Survival; DFS, disease-free survival; OS, overall survival.

The most common histopathology subtype is squamous cell carcinoma, while adenocarcinoma is relatively rare.35 However, adenocarcinoma has the propensity to have a higher ADC than squamous cell carcinoma.36 Therefore, we assessed the ADC values exclusively in patients with squamous cell carcinoma. Although ADCmean was selected as a risk factor for the recurrence in this study, the other values of such as minimum and maximum values of ADC were used for risk factors in the other studies. Because the minimum or maximum values of ADC are measured as very low or high for hematoma, cystic or necrotic portions of cervical tumor, measurement errors can occur. Nakamura et al reported that the ADC mean of primary cervical cancer was an independent predictive factor for disease recurrence by multivariate analysis due to evaluating whether pre-treatment ADCmax, ADCmean, ADCmin on MRI predicted the risk group of recurrence.37 Therefore, we selected the ADC mean as a risk factor for recurrence.

We acknowledge that there are some limitations to our study. First, our study could not be free of measurement errors because ADC values were derived from manually drawn ROIs. Second, our study was a retrospective study in a single-center, with a relatively small patient population and a relatively short follow-up period. A larger number of patients and long-term follow-up would support the strength of our data, and further confirmation by a prospective trial could reinforce our findings.

Conclusion

Our findings suggest that ADCmean values of the primary tumor could serve as an indicator for the risk of disease recurrence in patients with pre-treatment assessment of cervical cancer.

REFERENCES

1.

Siegel
R
,
Naishadham
D
,
Jemal
A
.
Cancer statistics, 2012
.
CA Cancer J Clin
2012
;
62
:
10
29
. doi: https://doi.org/10.3322/caac.20138

2.

Benedet
JL
,
Odicino
F
,
Maisonneuve
P
,
Beller
U
,
Creasman
WT
,
Heintz
AP
et al. .
Carcinoma of the cervix uteri
.
J Epidemiol Biostat
2001
;
6
:
7
43
.

3.

Marth
C
,
Landoni
F
,
Mahner
S
,
McCormack
M
,
Gonzalez-Martin
A
,
Colombo
N
et al. .
Cervical cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up
.
Ann Oncol
2017
;
28
(
suppl_4
):
iv72
83
. doi: https://doi.org/10.1093/annonc/mdx220

4.

Friedlander
M
,
Grogan
M
, .
U.S. Preventative Services Task Force
Guidelines for the treatment of recurrent and metastatic cervical cancer
.
Oncologist
2002
;
7
:
342
7
. doi: https://doi.org/10.1634/theoncologist.2002-0342

5.

Rose
PG
,
Bundy
BN
,
Watkins
EB
,
Thigpen
JT
,
Deppe
G
,
Maiman
MA
et al. .
Concurrent cisplatin-based radiotherapy and chemotherapy for locally advanced cervical cancer
.
N Engl J Med
1999
;
340
:
1144
53
. doi: https://doi.org/10.1056/NEJM199904153401502

6.

Delgado
G
,
Bundy
BN
,
Fowler
WC
,
Stehman
FB
,
Sevin
B
,
Creasman
WT
et al. .
A prospective surgical pathological study of stage I squamous carcinoma of the cervix: a gynecologic Oncology Group study
.
Gynecol Oncol
1989
;
35
:
314
20
. doi: https://doi.org/10.1016/0090-8258(89)90070-X

7.

Bammer
R
.
Basic principles of diffusion-weighted imaging
.
Eur J Radiol
2003
;
45
:
169
84
. doi: https://doi.org/10.1016/S0720-048X(02)00303-0

8.

Kuang
F
,
Ren
J
,
Zhong
Q
,
Liyuan
F
,
Huan
Y
,
Chen
Z
.
The value of apparent diffusion coefficient in the assessment of cervical cancer
.
Eur Radiol
2013
;
23
:
1050
8
. doi: https://doi.org/10.1007/s00330-012-2681-1

9.

Miccò
M
,
Vargas
HA
,
Burger
IA
,
Kollmeier
MA
,
Goldman
DA
,
Park
KJ
et al. .
Combined pre-treatment MRI and 18F-FDG PET/CT parameters as prognostic biomarkers in patients with cervical cancer
.
Eur J Radiol
2014
;
83
:
1169
76
. doi: https://doi.org/10.1016/j.ejrad.2014.03.024

10.

Liu
Y
,
Bai
R
,
Sun
H
,
Liu
H
,
Zhao
X
,
Li
Y
.
Diffusion-Weighted imaging in predicting and monitoring the response of uterine cervical cancer to combined chemoradiation
.
Clin Radiol
2009
;
64
:
1067
74
. doi: https://doi.org/10.1016/j.crad.2009.07.010

11.

Himoto
Y
,
Fujimoto
K
,
Kido
A
,
Baba
T
,
Tanaka
S
,
Morisawa
N
et al. .
Pretreatment mean apparent diffusion coefficient is significantly correlated with event-free survival in patients with international Federation of gynecology and obstetrics stage Ib to IIIB cervical cancer
.
Int J Gynecol Cancer
2015
;
25
:
1079
85
. doi: https://doi.org/10.1097/IGC.0000000000000445

12.

Zhang
Y
,
Chen
J-Y
,
Xie
C-M
,
Mo
Y-X
,
Liu
X-W
,
Liu
Y
et al. .
Diffusion-Weighted magnetic resonance imaging for prediction of response of advanced cervical cancer to chemoradiation
.
J Comput Assist Tomogr
2011
;
35
:
102
7
. doi: https://doi.org/10.1097/RCT.0b013e3181f6528b

13.

Rizzo
S
,
Summers
P
,
Raimondi
S
,
Belmonte
M
,
Maniglio
M
,
Landoni
F
et al. .
Diffusion-Weighted MR imaging in assessing cervical tumour response to nonsurgical therapy
.
Radiol Med
2011
;
116
:
766
80
. doi: https://doi.org/10.1007/s11547-011-0650-4

14.

Harry
VN
,
Gilbert
FJ
,
Parkin
DE
.
Predicting the response of advanced cervical and ovarian tumors to therapy
.
Obstet Gynecol Surv
2009
;
64
:
548
60
. doi: https://doi.org/10.1097/OGX.0b013e3181abc114

15.

Zhang
J
,
Tehrani
YM
,
Wang
L
,
Ishill
NM
,
Schwartz
LH
,
Hricak
H
.
Renal masses: characterization with diffusion-weighted MR imaging--a preliminary experience
.
Radiology
2008
;
247
:
458
64
. doi: https://doi.org/10.1148/radiol.2472070823

16.

Hayashida
Y
,
Hirai
T
,
Morishita
S
,
Kitajima
M
,
Murakami
R
,
Korogi
Y
et al. .
Diffusion-Weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity
.
AJNR Am J Neuroradiol
2006
;
27
:
1419
25
.

17.

Kanauchi
N
,
Oizumi
H
,
Honma
T
,
Kato
H
,
Endo
M
,
Suzuki
J
et al. .
Role of diffusion-weighted magnetic resonance imaging for predicting of tumor invasiveness for clinical stage Ia non-small cell lung cancer
.
Eur J Cardiothorac Surg
2009
;
35
:
706
11
. doi: https://doi.org/10.1016/j.ejcts.2008.12.039

18.

Taouli
B
,
Thakur
RK
,
Mannelli
L
,
Babb
JS
,
Kim
S
,
Hecht
EM
et al. .
Renal lesions: characterization with diffusion-weighted imaging versus contrast-enhanced MR imaging
.
Radiology
2009
;
251
:
398
407
. doi: https://doi.org/10.1148/radiol.2512080880

19.

Pötter
R
,
Haie-Meder
C
,
Van Limbergen
E
,
Barillot
I
,
De Brabandere
M
,
Dimopoulos
J
et al. .
Recommendations from gynaecological (GYN) GEC ESTRO Working Group (II): concepts and terms in 3D image-based treatment planning in cervix cancer brachytherapy-3D dose volume parameters and aspects of 3D image-based anatomy, radiation physics, radiobiology
.
Radiother Oncol
2006
;
78
:
67
77
. doi: https://doi.org/10.1016/j.radonc.2005.11.014

20.

Dueñas-González
A
,
Zarbá
JJ
,
Patel
F
,
Alcedo
JC
,
Beslija
S
,
Casanova
L
et al. .
Phase III, open-label, randomized study comparing concurrent gemcitabine plus cisplatin and radiation followed by adjuvant gemcitabine and cisplatin versus concurrent cisplatin and radiation in patients with stage IIb to IVA carcinoma of the cervix
.
J Clin Oncol
2011
;
29
:
1678
85
. doi: https://doi.org/10.1200/JCO.2009.25.9663

21.

Yavas
G
,
Yavas
C
,
Sen
E
,
Oner
I
,
Celik
C
,
Ata
O
.
Adjuvant carboplatin and paclitaxel after concurrent cisplatin and radiotherapy in patients with locally advanced cervical cancer
.
Int J Gynecol Cancer
2019
;
29
:
42
7
. doi: https://doi.org/10.1136/ijgc-2018-000022

22.

Boyce
J
,
Fruchter
RG
,
Nicastri
AD
,
Ambiavagar
PC
,
Reinis
MS
,
Nelson
JH
.
Prognostic factors in stage I carcinoma of the cervix
.
Gynecol Oncol
1981
;
12
(
2 Pt 1
):
154
65
. doi: https://doi.org/10.1016/0090-8258(81)90145-1

23.

Burghardt
E
,
Pickel
H
,
Haas
J
,
Lahousen
M
.
Prognostic factors and operative treatment of stages Ib to IIb cervical cancer
.
Am J Obstet Gynecol
1987
;
156
:
988
96
. doi: https://doi.org/10.1016/0002-9378(87)90374-7

24.

van Bommel
PF
,
van Lindert
AC
,
Kock
HC
,
Leers
WH
,
Neijt
JP
.
A review of prognostic factors in early-stage carcinoma of the cervix (FIGO I B and II a) and implications for treatment strategy
.
Eur J Obstet Gynecol Reprod Biol
1987
;
26
:
69
84
. doi: https://doi.org/10.1016/0028-2243(87)90010-4

25.

Provenzale
JM
,
Mukundan
S
,
Barboriak
DP
.
Diffusion-Weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response
.
Radiology
2006
;
239
:
632
49
. doi: https://doi.org/10.1148/radiol.2393042031

26.

Matsushima
N
,
Maeda
M
,
Takamura
M
,
Takeda
K
.
Apparent diffusion coefficients of benign and malignant salivary gland tumors. Comparison to histopathological findings
.
J Neuroradiol
2007
;
34
:
183
9
. doi: https://doi.org/10.1016/j.neurad.2007.04.002

27.

Abdel Razek
AAK
,
Soliman
NY
,
Elkhamary
S
,
Alsharaway
MK
,
Tawfik
A
.
Role of diffusion-weighted MR imaging in cervical lymphadenopathy
.
Eur Radiol
2006
;
16
:
1468
77
. doi: https://doi.org/10.1007/s00330-005-0133-x

28.

Humphries
PD
,
Sebire
NJ
,
Siegel
MJ
,
Olsen
Øystein E
,
Olsen Ø
E
.
Tumors in pediatric patients at diffusion-weighted MR imaging: apparent diffusion coefficient and tumor cellularity
.
Radiology
2007
;
245
:
848
54
. doi: https://doi.org/10.1148/radiol.2452061535

29.

Onal
C
,
Erbay
G
,
Guler
OC
.
Treatment response evaluation using the mean apparent diffusion coefficient in cervical cancer patients treated with definitive chemoradiotherapy
.
J Magn Reson Imaging
2016
;
44
:
1010
9
. doi: https://doi.org/10.1002/jmri.25215

30.

Payne
GS
,
Schmidt
M
,
Morgan
VA
,
Giles
S
,
Bridges
J
,
Ind
T
et al. .
Evaluation of magnetic resonance diffusion and spectroscopy measurements as predictive biomarkers in stage 1 cervical cancer
.
Gynecol Oncol
2010
;
116
:
246
52
. doi: https://doi.org/10.1016/j.ygyno.2009.09.044

31.

Park
JJ
,
Kim
CK
,
Park
BK
.
Prognostic value of diffusion-weighted magnetic resonance imaging and 18F-fluorodeoxyglucose-positron emission tomography/computed tomography after concurrent chemoradiotherapy in uterine cervical cancer
.
Radiother Oncol
2016
;
120
:
507
11
. doi: https://doi.org/10.1016/j.radonc.2016.02.014

32.

Ho
JC
,
Allen
PK
,
Bhosale
PR
,
Rauch
GM
,
Fuller
CD
,
Mohamed
ASR
et al. .
Diffusion-Weighted magnetic resonance imaging as a predictor of outcome in cervical cancer after chemoradiation
.
Int J Radiat Oncol Biol Phys
2017
;
97
:
546
53
. doi: https://doi.org/10.1016/j.ijrobp.2016.11.015

33.

Gu
K-W
,
Kim
CK
,
Choi
CH
,
Yoon
YC
,
Park
W
.
Prognostic value of ADC quantification for clinical outcome in uterine cervical cancer treated with concurrent chemoradiotherapy
.
Eur Radiol
2019
;
29
:
6236
44
. doi: https://doi.org/10.1007/s00330-019-06204-w

34.

Gladwish
A
,
Milosevic
M
,
Fyles
A
,
Xie
J
,
Halankar
J
,
Metser
U
et al. .
Association of apparent diffusion coefficient with disease recurrence in patients with locally advanced cervical cancer treated with radical chemotherapy and radiation therapy
.
Radiology
2016
;
279
:
158
66
. doi: https://doi.org/10.1148/radiol.2015150400

35.

Intaraphet
S
,
Kasatpibal
N
,
Siriaunkgul
S
,
Sogaard
M
,
Patumanond
J
,
Khunamornpong
S
et al. .
Prognostic impact of histology in patients with cervical squamous cell carcinoma, adenocarcinoma and small cell neuroendocrine carcinoma
.
Asian Pac J Cancer Prev
2013
;
14
:
5355
60
. doi: https://doi.org/10.7314/APJCP.2013.14.9.5355

36.

Liu
Y
,
Bai
R
,
Sun
H
,
Liu
H
,
Wang
D
.
Diffusion-Weighted magnetic resonance imaging of uterine cervical cancer
.
J Comput Assist Tomogr
2009
;
33
:
858
62
. doi: https://doi.org/10.1097/RCT.0b013e31819e93af

37.

Nakamura
K
,
Joja
I
,
Nagasaka
T
,
Fukushima
C
,
Kusumoto
T
,
Seki
N
et al. .
The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence
.
Gynecol Oncol
2012
;
127
:
478
83
. doi: https://doi.org/10.1016/j.ygyno.2012.07.123

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