PURPOSE: In T1 tumors, the reported incidence of lymph-node metastases ranges from 21% to 35%. We analyzed the pathological parameters of T1 tumors for their association with the likelihood of axillary lymph-node metastases. Our objectives were to determine if standard pathologic factors can predict lymph-node metastases in T1 tumors and to provide a basis for patient selection for nonradical surgery. METHODS: Sixty-five patients with T1 unilateral invasive breast cancer were studied. All patients underwent axillary dissection from 1990 to 1999 at Masan Samsung Hospital, and the pathologic status of the nodes was reviewed. The associations between the incidence of axillary lymph-node metastases and pathologic factors, including age, size, histologic subtype, nuclear grade, hormone receptor status, and lymphatic/vascular invasion, were analyzed. RESULTS: Of the 65 patients, 21 (32.3%) had nodes that were positive for metastases. The independent predictor of lymph-node metastases in the multivariate logistic regression analyses was a tumor size larger than 1 cm (p<0.05). However, other predictors showed nonspecific findings. CONCLUSION: These results suggest that the characteristics of the primary tumor can help assess the risk for axillary lymph-node metastases. Axillary lymph-node dissection should be performed routinely for all patients with lesions with a tumor more than 1 cm in size. Although a routine axillary dissection or radiation therapy to the axilla might be spared in selected patients who are assessed to be at minimal risk, new prognostic factors for providing reliable assurance of the absences of axillary lymph-node metastases must be investigated.
Axilla ; Breast Neoplasms* ; Breast* ; Humans ; Incidence ; Logistic Models ; Neoplasm Metastasis* ; Patient Selection

Objective: For an accurate dynamic contrast-enhanced (DCE) MRI analysis, exact baseline T1 mapping is critical. The purpose of this study was to compare the pharmacokinetic parameters of DCE MRI using synthetic MRI with those using fixed baseline T1 values. Materials and Methods: This retrospective study included 102 patients who underwent both DCE and synthetic brain MRI. Two methods were set for the baseline T1: one using the fixed value and the other using the T1 map from synthetic MRI. The volume transfer constant (Ktrans ), volume of the vascular plasma space (vp), and the volume of the extravascular extracellular space (ve) were compared between the two methods. The interclass correlation coefficients and the Bland-Altman method were used to assess the reliability. Results: In normal-appearing frontal white matter (WM), the mean values of Ktrans , ve, and vp were significantly higher in the fixed value method than in the T1 map method. In the normal-appearing occipital WM, the mean values of ve and vp were significantly higher in the fixed value method. In the putamen and head of the caudate nucleus, the mean values of Ktrans , ve, and vp were significantly lower in the fixed value method. In addition, the T1 map method showed comparable interobserver agreements with the fixed baseline T1 value method. Conclusion The T1 map method using synthetic MRI may be useful for reflecting individual differences and reliable measurements in clinical applications of DCE MRI.

Objective: For an accurate dynamic contrast-enhanced (DCE) MRI analysis, exact baseline T1 mapping is critical. The purpose of this study was to compare the pharmacokinetic parameters of DCE MRI using synthetic MRI with those using fixed baseline T1 values. Materials and Methods: This retrospective study included 102 patients who underwent both DCE and synthetic brain MRI. Two methods were set for the baseline T1: one using the fixed value and the other using the T1 map from synthetic MRI. The volume transfer constant (Ktrans ), volume of the vascular plasma space (vp), and the volume of the extravascular extracellular space (ve) were compared between the two methods. The interclass correlation coefficients and the Bland-Altman method were used to assess the reliability. Results: In normal-appearing frontal white matter (WM), the mean values of Ktrans , ve, and vp were significantly higher in the fixed value method than in the T1 map method. In the normal-appearing occipital WM, the mean values of ve and vp were significantly higher in the fixed value method. In the putamen and head of the caudate nucleus, the mean values of Ktrans , ve, and vp were significantly lower in the fixed value method. In addition, the T1 map method showed comparable interobserver agreements with the fixed baseline T1 value method. Conclusion The T1 map method using synthetic MRI may be useful for reflecting individual differences and reliable measurements in clinical applications of DCE MRI.

Objective: To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs). Materials and Methods: We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm 1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared. Results: IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs. Conclusion We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.

Purpose: To evaluate whether the added value of contrast leakage information from dynamic susceptibility contrast magnetic resonance imaging (DSC MRI) is a better prognostic imaging biomarker than the cerebral blood volume (CBV) value in distinguishing true progression from pseudoprogression in glioblastoma patients. Materials and Methods: Forty-nine glioblastoma patients who had undergone MRI after concurrent chemoradiotherapy with temozolomide were enrolled in this retrospective study. Twenty features were extracted from the normalized relative CBV (nCBV) and extraction fraction (EF) map of the contrast-enhancing region in each patient. After univariable analysis, we used multivariable stepwise logistic regression analysis to identify significant predictors for differentiating between pseudoprogression and true progression. Receiver operating characteristic (ROC) analysis was employed to determine the best cutoff values for the nCBV and EF features. Finally, leave-one-out cross-validation was used to validate the best predictor in differentiating between true progression and pseudoprogression. Results: Multivariable stepwise logistic regression analysis showed that MGMT (O 6 -methylguanine-DNA methyltransferase) and EF max were independent differentiating variables (P = 0.004 and P = 0.02, respectively). ROC analysis yielded the best cutoff value of 95.75 for the EF max value for differentiating the two groups (sensitivity, 61%; specificity, 84.6%; AUC, 0.681 ± 0.08; 95% CI, 0.524-0.837; P = 0.03). In the leave-one-out cross-validation of the EF max value, the cross-validated values for predicting true progression and pseudoprogression accuracies were 69.4% and 71.4%,respectively. Conclusion We demonstrated that contrast leakage information parameter from DSC MRI showed significance in differentiating true progression from pseudoprogression in glioblastoma patients.